Amazon EC2 Container Service Developer Guide AWS

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Amazon EC2 Container Service
Developer Guide
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Amazon EC2 Container Service Developer Guide
Amazon EC2 Container Service: Developer Guide
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Amazon EC2 Container Service Developer Guide
Table of Contents
What is Amazon ECS? ......................................................................................................................... 1
Features of Amazon ECS ............................................................................................................. 1
Containers and Images ....................................................................................................... 3
Task Definitions ................................................................................................................. 3
Tasks and Scheduling ......................................................................................................... 4
Clusters ............................................................................................................................. 4
Container Agent ................................................................................................................. 4
How to Get Started with Amazon ECS .......................................................................................... 5
Related Services ......................................................................................................................... 5
Accessing Amazon ECS ................................................................................................................ 6
Pricing ...................................................................................................................................... 7
Setting Up ........................................................................................................................................ 8
Sign Up for AWS ........................................................................................................................ 8
Create an IAM User .................................................................................................................... 9
Create an IAM Role for your Container Instances and Services ........................................................ 10
Create a Key Pair ..................................................................................................................... 10
(Optional) Install the Amazon ECS Command Line Interface (CLI) .................................................... 12
Docker Basics ................................................................................................................................... 13
Installing Docker ...................................................................................................................... 13
(Optional) Sign up for a Docker Hub Account ............................................................................... 14
(Optional) Amazon EC2 Container Registry .................................................................................. 14
Create a Docker Image and Upload it to Docker Hub .................................................................... 15
Next Steps ............................................................................................................................... 17
Getting Started ................................................................................................................................ 20
Cleaning Up ..................................................................................................................................... 24
Scale Down Services ................................................................................................................. 24
Delete Services ........................................................................................................................ 25
Deregister Container Instances ................................................................................................... 25
Delete a Cluster ....................................................................................................................... 25
Delete the AWS CloudFormation Stack ........................................................................................ 26
Clusters ........................................................................................................................................... 27
Cluster Concepts ...................................................................................................................... 27
Creating a Cluster .................................................................................................................... 27
Scaling a Cluster ...................................................................................................................... 29
Deleting a Cluster .................................................................................................................... 30
Container Instances .......................................................................................................................... 32
Container Instance Concepts ...................................................................................................... 32
Container Instance Lifecycle ....................................................................................................... 33
Check the Instance Role for Your Account ................................................................................... 34
Container Instance AMIs ............................................................................................................ 34
Amazon ECS-Optimized AMI .............................................................................................. 34
Launching a Container Instance .................................................................................................. 42
Bootstrap Container Instances .................................................................................................... 45
Amazon ECS Container Agent ............................................................................................ 46
Docker Daemon ............................................................................................................... 46
cloud-init-per Utility ........................................................................................................ 46
MIME Multi Part Archive .................................................................................................... 47
Example User Data Scripts ................................................................................................. 48
Connect to Your Container Instance ............................................................................................ 51
CloudWatch Logs ..................................................................................................................... 52
CloudWatch Logs IAM Policy .............................................................................................. 52
Installing the CloudWatch Logs Agent ................................................................................. 53
Configuring and Starting the CloudWatch Logs Agent ........................................................... 53
Viewing CloudWatch Logs ................................................................................................. 56
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Configuring CloudWatch Logs at Launch with User Data ........................................................ 57
Container Instance Draining ....................................................................................................... 59
Draining Instances ............................................................................................................ 59
Managing Container Instances Remotely ..................................................................................... 60
Run Command IAM Policy ................................................................................................. 60
Installing the SSM Agent on the Amazon ECS-optimized AMI ................................................. 61
Using Run Command ........................................................................................................ 61
Starting a Task at Container Instance Launch Time ....................................................................... 63
Deregister Container Instance .................................................................................................... 65
Container Agent ............................................................................................................................... 68
Installing the Amazon ECS Container Agent ................................................................................. 68
Container Agent Versions .......................................................................................................... 71
Amazon ECS-Optimized AMI Container Agent Versions .......................................................... 72
Updating the Amazon ECS Container Agent ................................................................................. 73
Checking Your Amazon ECS Container Agent Version ............................................................ 73
Updating the Amazon ECS Container Agent on the Amazon ECS-Optimized AMI ....................... 75
Manually Updating the Amazon ECS Container Agent (for Non-Amazon ECS-optimized AMIs) ...... 77
Amazon ECS Container Agent Configuration ................................................................................ 79
Available Parameters ........................................................................................................ 80
Storing Container Instance Configuration in Amazon S3 ........................................................ 84
Automated Task and Image Cleanup ........................................................................................... 85
Tunable Parameters .......................................................................................................... 86
Cleanup Workflow ............................................................................................................ 86
Private Registry Authentication .................................................................................................. 86
Authentication Formats ..................................................................................................... 87
Enabling Private Registries ................................................................................................ 88
Amazon ECS Container Agent Introspection ................................................................................. 90
HTTP Proxy Configuration ......................................................................................................... 91
Task Definitions ................................................................................................................................ 93
Application Architecture ............................................................................................................ 94
Creating a Task Definition ......................................................................................................... 95
Task Definition Template ................................................................................................... 96
Task Definition Parameters ........................................................................................................ 98
Family ............................................................................................................................. 98
Task Role ........................................................................................................................ 98
Network Mode ................................................................................................................. 99
Container Definitions ........................................................................................................ 99
Task Placement Constraints ............................................................................................. 111
Volumes ........................................................................................................................ 111
Using Data Volumes in Tasks ................................................................................................... 112
Using the awslogs Log Driver ................................................................................................... 117
Enabling the awslogs Log Driver on your Container Instances ............................................... 117
Creating Your Log Groups ................................................................................................ 117
Available awslogs Log Driver Options ................................................................................ 118
Specifying a Log Configuration in your Task Definition ........................................................ 119
Viewing awslogs Container Logs in CloudWatch Logs .......................................................... 120
Example Task Definitions ......................................................................................................... 122
WordPress and MySQL .................................................................................................... 122
awslogs Log Driver ......................................................................................................... 123
Amazon ECR Image and Task Definition IAM Role ............................................................... 124
Entrypoint with Command ............................................................................................... 124
Updating a Task Definition ...................................................................................................... 125
Deregistering Task Definitions .................................................................................................. 125
Scheduling Tasks ............................................................................................................................ 126
Running Tasks ........................................................................................................................ 127
Task Placement ...................................................................................................................... 128
Task Placement Strategies ............................................................................................... 129
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Task Placement Constraints ............................................................................................. 130
Cluster Query Language .................................................................................................. 134
Task Life Cycle ....................................................................................................................... 136
Services ......................................................................................................................................... 138
Service Concepts .................................................................................................................... 138
Service Definition Parameters .................................................................................................. 139
Service Load Balancing ............................................................................................................ 141
Load Balancing Concepts ................................................................................................. 144
Check the Service Role for your Account ........................................................................... 144
Creating a Load Balancer ................................................................................................. 145
Service Auto Scaling ............................................................................................................... 152
Service Auto Scaling Required IAM Permissions .................................................................. 153
Service Auto Scaling Concepts ......................................................................................... 153
Amazon ECS Console Experience ...................................................................................... 154
AWS CLI and SDK Experience ........................................................................................... 154
Tutorial: Service Auto Scaling ........................................................................................... 154
Creating a Service ................................................................................................................... 160
Configuring Basic Service Parameters ................................................................................ 160
(Optional) Configuring Your Service to Use a Load Balancer ................................................. 161
(Optional) Configuring Your Service to Use Service Auto Scaling ........................................... 163
Review and Create Your Service ....................................................................................... 165
Updating a Service ................................................................................................................. 165
Deleting a Service .................................................................................................................. 166
Repositories ................................................................................................................................... 168
Using Amazon ECR Images with Amazon ECS ............................................................................. 169
Monitoring ..................................................................................................................................... 170
Monitoring Tools .................................................................................................................... 171
Automated Tools ............................................................................................................ 171
Manual Tools ................................................................................................................. 171
CloudWatch Metrics ................................................................................................................ 172
Enabling CloudWatch Metrics ........................................................................................... 172
Available Metrics and Dimensions ..................................................................................... 172
Cluster Reservation ......................................................................................................... 175
Cluster Utilization ........................................................................................................... 176
Service Utilization ........................................................................................................... 177
Service RUNNING Task Count ............................................................................................. 177
Viewing Amazon ECS Metrics ........................................................................................... 178
Tutorial: Scaling with CloudWatch Alarms .......................................................................... 182
CloudWatch Events ................................................................................................................. 187
Amazon ECS Events ........................................................................................................ 187
Handling Events ............................................................................................................. 192
Tutorial: Listening for Amazon ECS CloudWatch Events ....................................................... 194
Tutorial: Sending Amazon Simple Notification Service Alerts for Task Stopped Events .............. 195
IAM Policies, Roles, and Permissions ................................................................................................. 198
Policy Structure ...................................................................................................................... 199
Policy Syntax ................................................................................................................. 199
Actions for Amazon ECS .................................................................................................. 200
Amazon Resource Names for Amazon ECS ......................................................................... 200
Condition Keys for Amazon ECS ....................................................................................... 201
Testing Permissions ........................................................................................................ 202
Supported Resource-Level Permissions ...................................................................................... 203
Creating IAM Policies .............................................................................................................. 205
Managed Policies .................................................................................................................... 205
Amazon ECS Managed Policies ......................................................................................... 206
Amazon ECR Managed Policies ......................................................................................... 208
Amazon ECS Container Instance IAM Role .................................................................................. 210
Adding Amazon S3 Read-only Access to your Container Instance Role .................................... 212
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Amazon ECS Service Scheduler IAM Role ................................................................................... 212
Amazon ECS Service Auto Scaling IAM Role ............................................................................... 214
Amazon EC2 Container Service Task Role ................................................................................ 215
IAM Roles for Tasks ................................................................................................................ 216
Benefits of Using IAM Roles for Tasks ............................................................................... 217
Enabling Task IAM Roles on your Container Instances .......................................................... 217
Creating an IAM Role and Policy for your Tasks .................................................................. 218
Using a Supported AWS SDK ........................................................................................... 219
Specifying an IAM Role for your Tasks ............................................................................... 219
Amazon ECS IAM Policy Examples ............................................................................................ 220
Amazon ECS First Run Wizard .......................................................................................... 220
Clusters ......................................................................................................................... 222
Container Instances ......................................................................................................... 223
Task Definitions .............................................................................................................. 224
Run Tasks ...................................................................................................................... 225
Start Tasks ..................................................................................................................... 225
List and Describe Tasks ................................................................................................... 226
Create Services ............................................................................................................... 226
Update Services ............................................................................................................. 227
Using the ECS CLI ........................................................................................................................... 228
Installing the Amazon ECS CLI ................................................................................................. 228
Configuring the Amazon ECS CLI .............................................................................................. 229
Amazon ECS CLI Tutorial ......................................................................................................... 230
Step 1: Create your Cluster .............................................................................................. 230
Step 2: Create a Compose File ......................................................................................... 231
Step 3: Deploy the Compose File to a Cluster ..................................................................... 232
Step 4: View the Running Containers on a Cluster .............................................................. 232
Step 5: Scale the Tasks on a Cluster ................................................................................. 233
Step 6: Create an ECS Service from a Compose File ............................................................ 233
Step 7: Clean Up ............................................................................................................ 234
Amazon ECS Command Line Reference ..................................................................................... 235
ecs-cli ........................................................................................................................... 235
ecs-cli configure ............................................................................................................. 237
ecs-cli up ....................................................................................................................... 240
ecs-cli down ................................................................................................................... 243
ecs-cli scale ................................................................................................................... 244
ecs-cli ps ....................................................................................................................... 244
ecs-cli push .................................................................................................................... 245
ecs-cli pull ..................................................................................................................... 246
ecs-cli images ................................................................................................................ 247
ecs-cli license ................................................................................................................. 249
ecs-cli compose .............................................................................................................. 250
ecs-cli compose service ................................................................................................... 252
Using the AWS CLI ......................................................................................................................... 259
Step 1: (Optional) Create a Cluster ........................................................................................... 259
Step 2: Launch an Instance with the Amazon ECS AMI ................................................................. 260
Step 3: List Container Instances ................................................................................................ 261
Step 4: Describe your Container Instance ................................................................................... 261
Step 5: Register a Task Definition ............................................................................................. 263
Step 6: List Task Definitions ..................................................................................................... 264
Step 7: Run a Task ................................................................................................................. 265
Step 8: List Tasks ................................................................................................................... 265
Step 9: Describe the Running Task ............................................................................................ 266
Common Use Cases ........................................................................................................................ 267
Microservices .......................................................................................................................... 267
Auto Scaling .................................................................................................................. 268
Service Discovery ............................................................................................................ 268
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Authorization and Secrets Management ............................................................................ 268
Logging ......................................................................................................................... 268
Continuous Integration and Continuous Deployment ........................................................... 269
Batch Jobs ............................................................................................................................. 269
Service Limits ................................................................................................................................. 270
CloudTrail Logging .......................................................................................................................... 271
Amazon ECS Information in CloudTrail ...................................................................................... 271
Understanding Amazon ECS Log File Entries .............................................................................. 272
Troubleshooting ............................................................................................................................. 273
Checking Stopped Tasks for Errors ............................................................................................ 273
Service Event Messages ........................................................................................................... 275
CannotCreateContainerError: API error (500): devmapper ..................................................... 277
Troubleshooting Service Load Balancers .................................................................................... 278
Enabling Docker Debug Output ................................................................................................ 280
Amazon ECS Log File Locations ................................................................................................ 281
Amazon ECS Container Agent Log .................................................................................... 281
Amazon ECS ecs-init Log .............................................................................................. 281
IAM Roles for Tasks Credential Audit Log ........................................................................... 281
Amazon ECS Logs Collector ..................................................................................................... 282
Agent Introspection Diagnostics ............................................................................................... 283
Docker Diagnostics ................................................................................................................. 284
List Docker Containers .................................................................................................... 284
View Docker Logs ........................................................................................................... 285
Inspect Docker Containers ............................................................................................... 285
API failures Error Messages ................................................................................................... 286
Windows Containers (Beta) .............................................................................................................. 288
Windows Container Caveats ..................................................................................................... 288
Windows Containers AWS CloudFormation Template ................................................................... 289
Getting Started with Windows Containers ................................................................................. 302
Step 1: Create a Windows Cluster ..................................................................................... 302
Step 2: Launching a Windows Container Instance into your Cluster ........................................ 302
Step 3: Register a Windows Task Definition ........................................................................ 305
Step 4: Create a Service with Your Task Definition .............................................................. 307
Step 5: View Your Service ................................................................................................ 307
Windows Task Definitions ........................................................................................................ 308
Windows Task Definition Parameters ................................................................................. 308
Windows Sample Task Definitions ..................................................................................... 311
Windows IAM Roles for Tasks ................................................................................................... 311
IAM Roles for Task Container Bootstrap Script .................................................................... 312
Pushing Windows Images to Amazon ECR .................................................................................. 312
AWS Glossary ................................................................................................................................. 314
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Features of Amazon ECS
What is Amazon EC2 Container
Service?
Amazon EC2 Container Service (Amazon ECS) is a highly scalable, fast, container management service
that makes it easy to run, stop, and manage Docker containers on a cluster of Amazon Elastic Compute
Cloud (Amazon EC2) instances. Amazon ECS lets you launch and stop container-based applications with
simple API calls, allows you to get the state of your cluster from a centralized service, and gives you
access to many familiar Amazon EC2 features.
You can use Amazon ECS to schedule the placement of containers across your cluster based on your
resource needs, isolation policies, and availability requirements. Amazon ECS eliminates the need for
you to operate your own cluster management and configuration management systems or worry about
scaling your management infrastructure.
Amazon ECS can be used to create a consistent deployment and build experience, manage and scale
batch and Extract-Transform-Load (ETL) workloads, and build sophisticated application architectures on
a microservices model. For more information about Amazon ECS use cases and scenarios, see Container
Use Cases.
AWS Elastic Beanstalk can also be used to rapidly develop, test, and deploy Docker containers in
conjunction with other components of your application infrastructure; however, using Amazon ECS
directly provides more fine-grained control and access to a wider set of use cases. For more information,
see the AWS Elastic Beanstalk Developer Guide.
Features of Amazon ECS
Amazon ECS is a regional service that simplifies running application containers in a highly available
manner across multiple Availability Zones within a region. You can create Amazon ECS clusters within a
new or existing VPC. After a cluster is up and running, you can define task definitions and services that
specify which Docker container images to run across your clusters. Container images are stored in and
pulled from container registries, which may exist within or outside of your AWS infrastructure.
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Containers and Images
The following sections dive into these individual elements of the Amazon ECS architecture in more
detail.
Containers and Images
To deploy applications on Amazon ECS, your application components must be architected to run in
containers. A Docker container is a standardized unit of software development, containing everything
that your software application needs to run: code, runtime, system tools, system libraries, etc. Containers
are created from a read-only template called an image.
Images are typically built from a Dockerfile, a plain text file that specifies all of the components that are
included in the container. These images are then stored in a registry from which they can be downloaded
and run on your container instances. For more information about container technology, see Docker
Basics (p. 13).
Task Definitions
To prepare your application to run on Amazon ECS, you create a task definition. The task definition
is a text file in JSON format that describes one or more containers that form your application. It can
be thought of as a blueprint for your application. Task definitions specify various parameters for your
application, such as which containers to use and the repositories in which they are located, which ports
should be opened on the container instance for your application, and what data volumes should be used
with the containers in the task. For more information about creating task definitions, see Amazon ECS
Task Definitions (p. 93).
The following is an example of a simple task definition containing a single container that runs an
Nginx web server. For a more extended example demonstrating the use of multiple containers in a task
definition, see Example Task Definitions (p. 122).
{
"family": "webserver",
"containerDefinitions": [
{
"name": "web",
"image": "nginx",
"cpu": 99,
"memory": 100,
"portMappings": [{
"containerPort": 80,
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Tasks and Scheduling
"hostPort": 80
}]
}]
}
Tasks and Scheduling
A task is the instantiation of a task definition on a container instance within your cluster. After you have
created a task definition for your application within Amazon ECS, you can specify the number of tasks
that will run on your cluster.
The Amazon ECS task scheduler is responsible for placing tasks on container instances. There are several
different scheduling options available. For example, you can define a service that runs and maintains a
specified number of tasks simultaneously. For more information about the different scheduling options
available, see Scheduling Amazon ECS Tasks (p. 126).
Clusters
When you run tasks using Amazon ECS, you place them on a cluster, which is a logical grouping of EC2
instances. Amazon ECS downloads your container images from a registry that you specify, and runs those
images on the container instances within your cluster.
For more information about creating clusters, see Amazon ECS Clusters (p. 27). For more information
about creating container instances, see Amazon ECS Container Instances (p. 32).
Container Agent
The container agent runs on each instance within an Amazon ECS cluster. It sends information about
the instance's current running tasks and resource utilization to Amazon ECS, and starts and stops tasks
whenever it receives a request from Amazon ECS. For more information, see Amazon ECS Container
Agent (p. 68).
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How to Get Started with Amazon ECS
How to Get Started with Amazon ECS
If you are using Amazon ECS for the first time, the AWS Management Console for Amazon ECS provides a
first-run wizard that steps you through defining a task definition for a web server, configuring a service,
and launching your first cluster. The first-run wizard is highly recommended for users who have no prior
experience with Amazon ECS. For more information, see the Getting Started with Amazon ECS (p. 20)
tutorial.
Alternatively, you can install the AWS Command Line Interface (AWS CLI) to use Amazon ECS. For more
information, see Setting Up with Amazon ECS (p. 8).
Related Services
Amazon ECS can be used in conjunction with the following AWS services:
AWS Identity and Access Management
IAM is a web service that helps you securely control access to AWS resources for your users. Use
IAM to control who can use your AWS resources (authentication) and what resources they can use
in which ways (authorization). In Amazon ECS, IAM can be used to control access at the container
instance level using IAM roles, and at the task level using IAM task roles. For more information, see
Amazon ECS IAM Policies, Roles, and Permissions (p. 198).
Auto Scaling
Auto Scaling is a web service that enables you to automatically launch or terminate EC2 instances
based on user-defined policies, health status checks, and schedules. You can use Auto Scaling to
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Accessing Amazon ECS
scale out and scale in the container instances within a cluster in response to a number of metrics. For
more information, see Tutorial: Scaling Container Instances with CloudWatch Alarms (p. 182).
Elastic Load Balancing
Elastic Load Balancing automatically distributes incoming application traffic across multiple
EC2 instances in the cloud. It enables you to achieve greater levels of fault tolerance in your
applications, seamlessly providing the required amount of load balancing capacity needed to
distribute application traffic. You can use Elastic Load Balancing to create an endpoint that balances
traffic across services in a cluster. For more information, see Service Load Balancing (p. 141).
Amazon EC2 Container Registry
Amazon ECR is a managed AWS Docker registry service that is secure, scalable, and reliable. Amazon
ECR supports private Docker repositories with resource-based permissions using IAM so that specific
users or EC2 instances can access repositories and images. Developers can use the Docker CLI to
push, pull, and manage images. For more information, see the Amazon EC2 Container Registry User
Guide.
AWS CloudFormation
AWS CloudFormation gives developers and systems administrators an easy way to create and
manage a collection of related AWS resources, provisioning and updating them in an orderly and
predictable fashion. You can define clusters, task definitions, and services as entities in an AWS
CloudFormation script. For more information, see AWS CloudFormation Template Reference.
Accessing Amazon ECS
You can work with Amazon ECS in any of the following ways:
AWS Management Console
The console is a browser-based interface to manage Amazon ECS resources. For a tutorial that
guides you through the console, see Getting Started with Amazon ECS (p. 20).
AWS command line tools
You can use the AWS command line tools to issue commands at your system's command line to
perform Amazon ECS and AWS tasks; this can be faster and more convenient than using the console.
The command line tools are also useful for building scripts that perform AWS tasks.
AWS provides two sets of command line tools: the AWS Command Line Interface (AWS CLI) and the
AWS Tools for Windows PowerShell. For more information, see the AWS Command Line Interface
User Guide and the AWS Tools for Windows PowerShell User Guide.
Amazon ECS CLI
In addition to using the AWS CLI to access Amazon ECS resources, you can use the Amazon ECS CLI,
which provides high-level commands to simplify creating, updating, and monitoring clusters and
tasks from a local development environment using Docker Compose. For more information, see
Using the Amazon ECS Command Line Interface (p. 228).
AWS SDKs
We also provide SDKs that enable you to access Amazon ECS from a variety of programming
languages. The SDKs automatically take care of tasks such as:
• Cryptographically signing your service requests
• Retrying requests
• Handling error responses
For more information about available SDKs, see Tools for Amazon Web Services.
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Pricing
Pricing
There is no additional charge for using Amazon ECS beyond the underlying AWS resources used to host
your applications. For more information, see Amazon EC2 Container Service Pricing.
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Sign Up for AWS
Setting Up with Amazon ECS
If you've already signed up for Amazon Web Services (AWS) and have been using Amazon Elastic
Compute Cloud (Amazon EC2), you are close to being able to use Amazon ECS. The set up process for
the two services is very similar, as Amazon ECS uses EC2 instances in the clusters. The following guide
prepares you for launching your first cluster using either the Amazon ECS first-run wizard or the Amazon
ECS Command Line Interface (CLI).
Note
Because Amazon ECS uses many components of Amazon EC2, you use the Amazon EC2 console
for many of these steps.
Complete the following tasks to get set up for Amazon ECS. If you have already completed any of these
steps, you may skip them and move on to installing the custom AWS CLI.
1. Sign Up for AWS (p. 8)
2. Create an IAM User (p. 9)
3. Create an IAM Role for your Container Instances and Services (p. 10)
4. Create a Key Pair (p. 10)
5. (Optional) Install the Amazon ECS Command Line Interface (CLI) (p. 12)
Sign Up for AWS
When you sign up for AWS, your AWS account is automatically signed up for all services, including
Amazon EC2 and Amazon ECS. You are charged only for the services that you use.
If you have an AWS account already, skip to the next task. If you don't have an AWS account, use the
following procedure to create one.
To create an AWS account
1. Open https://aws.amazon.com/, and then choose Create an AWS Account.
2. Follow the online instructions.
Part of the sign-up procedure involves receiving a phone call and entering a PIN using the phone
keypad.
Note your AWS account number, because you'll need it for the next task.
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Create an IAM User
Create an IAM User
Services in AWS, such as Amazon EC2 and Amazon ECS, require that you provide credentials when you
access them, so that the service can determine whether you have permission to access its resources. The
console requires your password. You can create access keys for your AWS account to access the command
line interface or API. However, we don't recommend that you access AWS using the credentials for your
AWS account; we recommend that you use AWS Identity and Access Management (IAM) instead. Create
an IAM user, and then add the user to an IAM group with administrative permissions or and grant this
user administrative permissions. You can then access AWS using a special URL and the credentials for the
IAM user.
If you signed up for AWS but have not created an IAM user for yourself, you can create one using the IAM
console.
To create an IAM user for yourself and add the user to an Administrators group
1. Sign in to the IAM console at https://console.aws.amazon.com/iam/.
2. In the navigation pane, choose Users, and then choose Add user.
3. For User name, type a user name, such as Administrator. The name can consist of letters, digits,
and the following characters: plus (+), equal (=), comma (,), period (.), at (@), underscore (_), and
hyphen (-). The name is not case sensitive and can be a maximum of 64 characters in length.
4. Select the check box next to AWS Management Console access, select Custom password, and then
type the new user's password in the text box. You can optionally select Require password reset to
force the user to select a new password the next time the user signs in.
5. Choose Next: Permissions.
6. On the Set permissions for user page, choose Add user to group.
7. Choose Create group.
8. In the Create group dialog box, type the name for the new group. The name can consist of letters,
digits, and the following characters: plus (+), equal (=), comma (,), period (.), at (@), underscore (_),
and hyphen (-). The name is not case sensitive and can be a maximum of 128 characters in length.
9. For Filter, choose Job function.
10. In the policy list, select the check box for AdministratorAccess. Then choose Create group.
11. Back in the list of groups, select the check box for your new group. Choose Refresh if necessary to
see the group in the list.
12. Choose Next: Review to see the list of group memberships to be added to the new user. When you
are ready to proceed, choose Create user.
You can use this same process to create more groups and users, and to give your users access to your
AWS account resources. To learn about using policies to restrict users' permissions to specific AWS
resources, go to Access Management and Example Policies for Administering AWS Resources.
To sign in as this new IAM user, sign out of the AWS console, then use the following URL, where
your_aws_account_id is your AWS account number without the hyphens (for example, if your AWS
account number is 1234-5678-9012, your AWS account ID is 123456789012):
https://your_aws_account_id.signin.aws.amazon.com/console/
Enter the IAM user name and password that you just created. When you're signed in, the navigation bar
displays "your_user_name @ your_aws_account_id".
If you don't want the URL for your sign-in page to contain your AWS account ID, you can create an
account alias. From the IAM dashboard, choose Create Account Alias and enter an alias, such as your
company name. To sign in after you create an account alias, use the following URL:
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Container Instances and Services
https://your_account_alias.signin.aws.amazon.com/console/
To verify the sign-in link for IAM users for your account, open the IAM console and check under IAM
users sign-in link on the dashboard.
For more information about IAM, see the AWS Identity and Access Management User Guide.
Create an IAM Role for your Container Instances
and Services
Before the Amazon ECS agent can register container instance into a cluster, the agent must know which
account credentials to use. You can create an IAM role that allows the agent to know which account
it should register the container instance with. When you launch an instance with the Amazon ECS-
optimized AMI provided by Amazon using this role, the agent automatically registers the container
instance into your default cluster.
The Amazon ECS container agent also makes calls to the Amazon EC2 and Elastic Load Balancing APIs on
your behalf, so container instances can be registered and deregistered with load balancers. Before you
can attach a load balancer to an Amazon ECS service, you must create an IAM role for your services to
use before you start them. This requirement applies to any Amazon ECS service that you plan to use with
a load balancer.
Note
The Amazon ECS instance and service roles are automatically created for you in the console first
run experience, so if you intend to use the Amazon ECS console, you can move ahead to Create
a Key Pair (p. 10). If you do not intend to use the Amazon ECS console, and instead plan to
use the AWS CLI, complete the procedures in Amazon ECS Container Instance IAM Role (p. 210)
and Amazon ECS Service Scheduler IAM Role (p. 212) before launching container instances or
using Elastic Load Balancing load balancers with services.
Create a Key Pair
AWS uses public-key cryptography to secure the login information for your instance. A Linux instance,
such as an Amazon ECS container instance, has no password to use for SSH access; you use a key pair to
log in to your instance securely. You specify the name of the key pair when you launch your container
instance, then provide the private key when you log in using SSH.
If you haven't created a key pair already, you can create one using the Amazon EC2 console. Note that if
you plan to launch instances in multiple regions, you'll need to create a key pair in each region. For more
information about regions, see Regions and Availability Zones in the Amazon EC2 User Guide for Linux
Instances.
To create a key pair
1. Open the Amazon EC2 console at https://console.aws.amazon.com/ec2/.
2. From the navigation bar, select a region for the key pair. You can select any region that's available to
you, regardless of your location: however, key pairs are specific to a region. For example, if you plan
to launch an instance in the US East (N. Virginia) region, you must create a key pair for the instance
in the same region.
Note
Amazon ECS is available in the following regions:
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Region Name Region
US East (N. Virginia) us-east-1
US East (Ohio) us-east-2
US West (N.
California)
us-west-1
US West (Oregon) us-west-2
EU (Ireland) eu-west-1
EU (London) eu-west-2
EU (Frankfurt) eu-central-1
Asia Pacific (Tokyo) ap-northeast-1
Asia Pacific
(Singapore)
ap-southeast-1
Asia Pacific (Sydney) ap-southeast-2
Canada (Central) ca-central-1
3. Choose Key Pairs in the navigation pane.
4. Choose Create Key Pair.
5. Enter a name for the new key pair in the Key pair name field of the Create Key Pair dialog box, and
then choose Create. Choose a name that is easy for you to remember, such as your IAM user name,
followed by -key-pair, plus the region name. For example, me-key-pair-useast1.
6. The private key file is automatically downloaded by your browser. The base file name is the name
you specified as the name of your key pair, and the file name extension is .pem. Save the private key
file in a safe place.
Important
This is the only chance for you to save the private key file. You'll need to provide the name
of your key pair when you launch an instance and the corresponding private key each time
you connect to the instance.
7. If you will use an SSH client on a Mac or Linux computer to connect to your Linux instance, use the
following command to set the permissions of your private key file so that only you can read it.
$ chmod 400 your_user_name-key-pair-region_name.pem
For more information, see Amazon EC2 Key Pairs in the Amazon EC2 User Guide for Linux Instances.
To connect to your instance using your key pair
To connect to your Linux instance from a computer running Mac or Linux, specify the .pem file to your
SSH client with the -i option and the path to your private key. To connect to your Linux instance from a
computer running Windows, you can use either MindTerm or PuTTY. If you plan to use PuTTY, you'll need
to install it and use the following procedure to convert the .pem file to a .ppk file.
(Optional) To prepare to connect to a Linux instance from Windows using PuTTY
1. Download and install PuTTY from http://www.chiark.greenend.org.uk/~sgtatham/putty/. Be sure
to install the entire suite.
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(Optional) Install the Amazon ECS
Command Line Interface (CLI)
2. Start PuTTYgen (for example, from the Start menu, choose All Programs, PuTTY, and PuTTYgen).
3. Under Type of key to generate, choose SSH-2 RSA.
4. Choose Load. By default, PuTTYgen displays only files with the extension .ppk. To locate your .pem
file, choose the option to display files of all types.
5. Select the private key file that you created in the previous procedure and choose Open. Choose OK
to dismiss the confirmation dialog box.
6. Choose Save private key. PuTTYgen displays a warning about saving the key without a passphrase.
Choose Yes.
7. Specify the same name for the key that you used for the key pair. PuTTY automatically adds the
.ppk file extension.
(Optional) Install the Amazon ECS Command Line
Interface (CLI)
Note
This step is not required if you use the first-run wizard to create your cluster.
The Amazon EC2 Container Service (Amazon ECS) command line interface (CLI) provides high-level
commands to simplify creating, updating, and monitoring clusters and tasks from a local development
environment. The Amazon ECS CLI supports Docker Compose, a popular open-source tool for defining
and running multi-container applications. For more information about installing and using the Amazon
ECS CLI, see Using the Amazon ECS Command Line Interface (p. 228).
You can also choose to use Amazon ECS through the AWS CLI. However, you will need to create your VPC
and security groups separately, whereas both the Amazon ECS CLI and the first-run wizard will create
this necessary infrastructure for you. For information about installing the AWS CLI or upgrading it to the
latest version, see Installing the AWS Command Line Interface in the AWS Command Line Interface User
Guide.
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Installing Docker
Docker Basics
Docker is a technology that allows you to build, run, test, and deploy distributed applications that are
based on Linux containers. Amazon ECS uses Docker images in task definitions to launch containers on
EC2 instances in your clusters. For Amazon ECS product details, featured customer case studies, and
FAQs, see the Amazon EC2 Container Service product detail pages.
The documentation in this guide assumes that readers possess a basic understanding of what Docker is
and how it works. For more information about Docker, see What is Docker? and the Docker User Guide.
Topics
•Installing Docker (p. 13)
•(Optional) Sign up for a Docker Hub Account (p. 14)
•(Optional) Amazon EC2 Container Registry (p. 14)
•Create a Docker Image and Upload it to Docker Hub (p. 15)
•Next Steps (p. 17)
Installing Docker
Docker is available on many different operating systems, including most modern Linux distributions, like
Ubuntu, and even Mac OSX and Windows. For more information about how to install Docker on your
particular operating system, go to the Docker installation guide.
You don't even need a local development system to use Docker. If you are using Amazon EC2 already, you
can launch an Amazon Linux instance and install Docker to get started.
To install Docker on an Amazon Linux instance
1. Launch an instance with the Amazon Linux AMI. For more information, see Launching an Instance in
the Amazon EC2 User Guide for Linux Instances.
2. Connect to your instance. For more information, see Connect to Your Linux Instance in the Amazon
EC2 User Guide for Linux Instances.
3. Update the installed packages and package cache on your instance.
[ec2-user ~]$ sudo yum update -y
4. Install Docker.
[ec2-user ~]$ sudo yum install -y docker
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(Optional) Sign up for a Docker Hub Account
5. Start the Docker service.
[ec2-user ~]$ sudo service docker start
Starting cgconfig service: [ OK ]
Starting docker: [ OK ]
6. Add the ec2-user to the docker group so you can execute Docker commands without using sudo.
[ec2-user ~]$ sudo usermod -a -G docker ec2-user
7. Log out and log back in again to pick up the new docker group permissions.
8. Verify that the ec2-user can run Docker commands without sudo.
[ec2-user ~]$ docker info
Containers: 2
Images: 24
Storage Driver: devicemapper
Pool Name: docker-202:1-263460-pool
Pool Blocksize: 65.54 kB
Data file: /var/lib/docker/devicemapper/devicemapper/data
Metadata file: /var/lib/docker/devicemapper/devicemapper/metadata
Data Space Used: 702.3 MB
Data Space Total: 107.4 GB
Metadata Space Used: 1.864 MB
Metadata Space Total: 2.147 GB
Library Version: 1.02.89-RHEL6 (2014-09-01)
Execution Driver: native-0.2
Kernel Version: 3.14.27-25.47.amzn1.x86_64
Operating System: Amazon Linux AMI 2014.09
Note
In some cases, you may need to reboot your instance to provide permissions for the ec2-
user to access the Docker daemon. Try rebooting your instance if you see the following
error:
Cannot connect to the Docker daemon. Is the docker daemon running on this host?
(Optional) Sign up for a Docker Hub Account
Docker uses images that are stored in repositories to launch containers with. The most common Docker
image repository (and the default repository for the Docker daemon) is Docker Hub. Although you don't
need a Docker Hub account to use Amazon ECS or Docker, having a Docker Hub account gives you the
freedom to store your modified Docker images so you can use them in your ECS task definitions.
For more information about Docker Hub, and to sign up for an account, go to https://hub.docker.com.
Docker Hub offers public and private registries. You can create a private registry on Docker Hub and
configure Private Registry Authentication (p. 86) on your ECS container instances to use your private
images in task definitions.
(Optional) Amazon EC2 Container Registry
Another registry option is Amazon EC2 Container Registry (Amazon ECR). Amazon ECR is a managed
AWS Docker registry service. Customers can use the familiar Docker CLI to push, pull, and manage
images. For Amazon ECR product details, featured customer case studies, and FAQs, see the Amazon
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Create a Docker Image and Upload it to Docker Hub
EC2 Container Registry product detail pages. To finish this walkthrough using Amazon ECR, see Create a
Docker Image in the Amazon EC2 Container Registry User Guide.
Create a Docker Image and Upload it to Docker
Hub
Amazon ECS task definitions use Docker images to launch containers on the container instances in your
clusters. In this section, you create a Docker image of a simple PHP web application, and test it on your
local system or EC2 instance, and then push the image to your Docker Hub registry so you can use it in an
ECS task definition.
To create a Docker image of a PHP web application
1. Install git and use it to clone the simple PHP application from your GitHub repository onto your
system.
a. Install git.
[ec2-user ~]$ sudo yum install -y git
b. Clone the simple PHP application onto your system.
[ec2-user ~]$ git clone https://github.com/awslabs/ecs-demo-php-simple-app
2. Change directories to the ecs-demo-php-simple-app folder.
[ec2-user ~]$ cd ecs-demo-php-simple-app
3. Examine the Dockerfile in this folder. A Dockerfile is a manifest that describes the base image to use
for your Docker image and what you want installed and running on it. For more information about
Dockerfiles, go to the Dockerfile Reference.
[ec2-user ecs-demo-php-simple-app]$ cat Dockerfile
FROM ubuntu:12.04
# Install dependencies
RUN apt-get update -y
RUN apt-get install -y git curl apache2 php5 libapache2-mod-php5 php5-mcrypt php5-mysql
# Install app
RUN rm -rf /var/www/*
ADD src /var/www
# Configure apache
RUN a2enmod rewrite
RUN chown -R www-data:www-data /var/www
ENV APACHE_RUN_USER www-data
ENV APACHE_RUN_GROUP www-data
ENV APACHE_LOG_DIR /var/log/apache2
EXPOSE 80
CMD ["/usr/sbin/apache2", "-D", "FOREGROUND"]
This Dockerfile uses the Ubuntu 12.04 image. The RUN instructions update the package caches,
install some software packages for the web server and PHP support, and then add your PHP
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Create a Docker Image and Upload it to Docker Hub
application to the web server's document root. The EXPOSE instruction exposes port 80 on the
container, and the CMD instruction starts the web server.
4. Build the Docker image from your Dockerfile. Substitute my-dockerhub-username with your Docker
Hub user name.
Note
Some versions of Docker may require the full path to your Dockerfile in the following
command, instead of the relative path shown below.
[ec2-user ecs-demo-php-simple-app]$ docker build -t my-dockerhub-username/amazon-ecs-
sample .
5. Run docker images to verify that the image was created correctly and that the image name contains
a repository that you can push to (in this example, your Docker Hub user name).
[ec2-user ecs-demo-php-simple-app]$ docker images
REPOSITORY TAG IMAGE ID
CREATED VIRTUAL SIZE
my-dockerhub-username/amazon-ecs-sample latest 43c52559a0a1 12
minutes ago 258.1 MB
ubuntu 12.04 78cef618c77e 3
weeks ago 133.7 MB
6. Run the newly built image. The -p 80:80 option maps the exposed port 80 on the container to port
80 on the host system. For more information about docker run, go to the Docker run reference.
[ec2-user ecs-demo-php-simple-app]$ docker run -p 80:80 my-dockerhub-username/amazon-
ecs-sample
apache2: Could not reliably determine the server's fully qualified domain name, using
172.17.0.2 for ServerName
Note
Output from the Apache web server is displayed in the terminal window. You can ignore the
"Could not reliably determine the server's fully qualified domain name" message.
7. Open a browser and point to the server that is running Docker and hosting your container.
• If you are using an EC2 instance, this is the Public DNS value for the server, which is the same
address you use to connect to the instance with SSH. Make sure that the security group for your
instance allows inbound traffic on port 80.
• If you are running Docker locally, point your browser to http://localhost/.
• If you are using docker-machine on a Windows or Mac computer, find the IP address of the
VirtualBox VM that is hosting Docker with the docker-machine ip command, substituting
machine-name with the name of the docker machine you are using.
$ docker-machine ip machine-name
192.168.59.103
You should see a web page running the simple PHP app.
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Next Steps
8. Stop the Docker container by typing Ctrl+c.
9. Authenticate your Docker client with your Docker Hub credentials.
[ec2-user ecs-demo-php-simple-app]$ docker login
10. Push the image to Docker Hub.
[ec2-user ecs-demo-php-simple-app]$ docker push my-dockerhub-username/amazon-ecs-sample
Next Steps
After the image push is finished, you can use the my-dockerhub-username/amazon-ecs-sample image in
your Amazon ECS task definitions, which you can use to run tasks with.
To register a task definition with the amazon-ecs-sample image
1. Examine the simple-app-task-def.json file in the ecs-demo-php-simple-app folder.
{
"family": "console-sample-app",
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Next Steps
"volumes": [
{
"name": "my-vol",
"host": {}
}
],
"containerDefinitions": [
{
"environment": [],
"name": "simple-app",
"image": "amazon/amazon-ecs-sample",
"cpu": 10,
"memory": 500,
"portMappings": [
{
"containerPort": 80,
"hostPort": 80
}
],
"mountPoints": [
{
"sourceVolume": "my-vol",
"containerPath": "/var/www/my-vol"
}
],
"entryPoint": [
"/usr/sbin/apache2",
"-D",
"FOREGROUND"
],
"essential": true
},
{
"name": "busybox",
"image": "busybox",
"cpu": 10,
"memory": 500,
"volumesFrom": [
{
"sourceContainer": "simple-app"
}
],
"entryPoint": [
"sh",
"-c"
],
"command": [
"/bin/sh -c \"while true; do /bin/date > /var/www/my-vol/date; sleep 1;
done\""
],
"essential": false
}
]
}
This task definition JSON file specifies two containers, one of which uses the amazon-ecs-sample
image. By default, this image is pulled from the Amazon Docker Hub repository, but you can change
the amazon repository defined above to your own repository if you want to use the my-dockerhub-
username/amazon-ecs-sample image you pushed earlier.
2. Register a task definition with the simple-app-task-def.json file.
[ec2-user ecs-demo-php-simple-app]$ aws ecs register-task-definition --cli-input-json
file://simple-app-task-def.json
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Next Steps
The task definition is registered in the console-sample-app family as defined in the JSON file.
To run a task with the console-sample-app task definition
Important
Before you can run tasks in Amazon ECS, you need to launch container instances into your
cluster. For more information about how to set up and launch container instances, see Setting
Up with Amazon ECS (p. 8) and Getting Started with Amazon ECS (p. 20).
• Use the following AWS CLI command to run a task with the console-sample-app task definition.
[ec2-user ecs-demo-php-simple-app]$ aws ecs run-task --task-definition console-sample-
app
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Getting Started with Amazon ECS
Let's get started with Amazon EC2 Container Service (Amazon ECS) by creating a task definition,
scheduling tasks, and configuring a cluster in the Amazon ECS console.
You can optionally create an Amazon EC2 Container Registry (Amazon ECR) image repository and push
an image to it. For more information on Amazon ECR, see the Amazon EC2 Container Registry User Guide.
The Amazon ECS first run wizard will guide you through the process to get started with Amazon ECS.
The wizard gives you the option of creating a cluster and launching our sample web application, or if you
already have a Docker image you would like to launch in Amazon ECS, you can create a task definition
with that image and use that for your cluster instead.
Important
Before you begin, be sure that you've completed the steps in Setting Up with Amazon ECS (p. 8)
and that your AWS user has the required permissions specified in the Amazon ECS First Run
Wizard (p. 220) IAM policy example.
Choose your Amazon ECS first run wizard configuration options
1. Open the Amazon ECS console first run wizard at https://console.aws.amazon.com/ecs/home#/
firstRun.
2. Select your Amazon ECS first run options.
To create an Amazon ECS cluster and deploy a container application to it, check the top option. To
create an Amazon ECR repository and push an image to it, which you can use in your Amazon ECS
task definitions, check the bottom option. Choose Continue to proceed.
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3. If you've chosen to create an Amazon ECR repository, then complete the next two sections of the
first run wizard, Configure repository and Build, tag, and push Docker image . If you are not
creating an Amazon ECR repository, skip ahead to Create a task definition (p. 21).
Configure repository
A repository is where you store Docker images in Amazon ECR. Every time you push or pull an image
from Amazon ECR, you specify the registry and repository location to tell Docker where to push the
image to or where to pull it from.
• For Repository name, enter a unique name for your repository and choose Next step.
Build, tag, and push Docker image
In this section of the wizard, you use the Docker CLI to tag an existing local image (that you have built
from a Dockerfile or pulled from another registry, such as Docker Hub) and then push the tagged image
to your Amazon ECR registry.
1. Retrieve the docker login command that you can use to authenticate your Docker client to your
registry by pasting the aws ecr get-login command from the console into a terminal window.
Note
The get-login command is available in the AWS CLI starting with version 1.9.15. You can
check your AWS CLI version with the aws --version command.
2. Run the docker login command that was returned in the previous step. This command provides an
authorization token that is valid for 12 hours.
Important
When you execute this docker login command, the command string can be visible by other
users on your system in a process list (ps -e) display. Because the docker login command
contains authentication credentials, there is a risk that other users on your system could
view them this way and use them to gain push and pull access to your repositories. If you
are not on a secure system, you should consider this risk and log in interactively by omitting
the -p password option, and then entering the password when prompted.
3. (Optional) If you have a Dockerfile for the image to push, build the image and tag it for your new
repository by pasting the docker build command from the console into a terminal window. Make
sure you are in the same directory as your Dockerfile.
4. Tag the image for your ECR registry and your new repository by pasting the docker tag command
from the console into a terminal window. The console command assumes that your image was built
from a Dockerfile in the previous step; if you did not build your image from a Dockerfile, replace the
first instance of repository:latest with the image ID or image name of your local image to push.
5. Push the newly tagged image to your ECR repository by pasting the docker push command into a
terminal window.
6. Choose Done.
Create a task definition
A task definition is like a blue print for your application. Every time you launch a task in Amazon ECS,
you specify a task definition so the service knows which Docker image to use for containers, how many
containers to use in the task, and the resource allocation for each container.
1. Configure your task definition parameters.
The first run wizard comes preloaded with a task definition, and you can see the simple-app
container defined in the console. You can optionally rename the task definition or review and
edit the resources used by the container (such as CPU units and memory limits) by choosing the
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container name and editing the values shown (CPU units are under the Advanced container
configuration menu). Task definitions created in the first run wizard are limited to a single container
for simplicity's sake. You can create multi-container task definitions later in the Amazon ECS console.
Note
If you are using an Amazon ECR image in your task definition, be sure to use the
full registry/repository:tag naming for your Amazon ECR images. For example,
aws_account_id.dkr.ecr.region.amazonaws.com/my-web-app:latest.
For more information on what each of these task definition parameters does, see Task Definition
Parameters (p. 98).
2. Choose Next step to continue.
Configure service
In this section of the wizard, you select how you would like to configure the Amazon ECS service that
is created from your task definition. A service launches and maintains a specified number of copies of
the task definition in your cluster. The Amazon ECS sample application is a web-based "Hello World"
style application that is meant to run indefinitely, so by running it as a service, it will restart if the task
becomes unhealthy or unexpectedly stops.
1. In the Service Name field, select a name for your service.
2. In the Desired number of tasks field, enter the number of tasks you would like to launch with your
specified task definition.
Note
If your task definition contains static port mappings, the number of container instances you
launch in the next section of the wizard must be greater than or equal to the number of
tasks specified here.
3. (Optional) You can choose to use an Application Load Balancer with your service. When a task
is launched from a service that is configured to use a load balancer, the container instance that
the task is launched on is registered with the load balancer and traffic from the load balancer
is distributed across the instances in the load balancer. For more details, see Introduction to
Application Load Balancers.
Important
Application Load Balancers do incur cost while they exist in your AWS resources. For more
information on Application Load Balancer pricing, see Application Load Balancer Pricing.
Complete the following steps to use a load balancer with your service.
a. In the Application load balancing section, choose the Container name : container port :
protocol menu, and then choose simple-app:80:tcp. The default values here are set up for the
sample application, but you can configure different listener options for the load balancer. For
more information, see Service Load Balancing (p. 141).
b. In the Service IAM Role section, choose the Select IAM role for service menu, and then choose
an existing Amazon ECS service (ecsServiceRole) role that you have already created, or click
Create new role to create the required IAM role for your service.
4. Review your load balancer settings and click Next Step.
Configure cluster
In this section of the wizard, you name your cluster, and then configure the container instances that your
tasks can be placed on, the address range that you can reach your instances and load balancer from, and
the IAM roles to use with your container instances that let Amazon ECS take care of this configuration for
you.
1. In the Cluster name field, choose a name for your cluster.
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2. In the EC2 instance type field, choose the instance type to use for your container instances. Instance
types with more CPU and memory resources can handle more tasks. For more information on the
different instance types, see Amazon EC2 Instances.
3. In the Number of instances field, type the number of Amazon EC2 instances you want to launch into
your cluster for tasks to be placed on. The more instances you have in your cluster, the more tasks
you can place on them. Amazon EC2 instances incur costs while they exist in your AWS resources. For
more information, see Amazon EC2 Pricing.
Note
If you created a service with more than one desired task in it that exposes container ports
on to container instance ports, such as the Amazon ECS sample application, you need to
specify at least that many instances here.
4. Select a key pair name to use with your container instances. This is required for you to log into your
instances with SSH; if you do not specify a key pair here, you cannot connect to your container
instances with SSH. If you do not have a key pair, you can create one in the Amazon EC2 console at
https://console.aws.amazon.com/ec2/.
5. (Optional) In the Security Group section, you can choose a CIDR block that restricts access to your
instances. The default value (Anywhere)allows access from the entire Internet.
6. In the Container instance IAM role section, choose an existing Amazon ECS container instance
(ecsInstanceRole) role that you have already created, or choose Create new role to create the
required IAM role for your container instances.
7. Click Review and Launch to proceed.
Review
1. Review your task definition, task configuration, and cluster configurations and click Launch Instance
& Run Service to finish. You are directed to a Launch Status page that shows the status of your
launch and describes each step of the process (this can take a few minutes to complete while your
Auto Scaling group is created and populated).
2. After the launch is complete, choose View service to view your service in the Amazon ECS console.
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Scale Down Services
Cleaning Up your Amazon ECS
Resources
When you are finished experimenting with or using a particular Amazon ECS cluster, you should clean up
the resources associated with it to avoid incurring charges for resources that you are not using.
Some Amazon ECS resources, such as tasks, services, clusters, and container instances, are cleaned up
using the Amazon ECS console. Other resources, such as Amazon EC2 instances, Elastic Load Balancing
load balancers, and Auto Scaling groups, must be cleaned up manually in the Amazon EC2 console or by
deleting the AWS CloudFormation stack that created them.
Topics
•Scale Down Services (p. 24)
•Delete Services (p. 25)
•Deregister Container Instances (p. 25)
•Delete a Cluster (p. 25)
•Delete the AWS CloudFormation Stack (p. 26)
Scale Down Services
If your cluster contains any services, you should first scale down the desired count of tasks in these
services to 0 so that Amazon ECS does not try to start new tasks on your container instances while you
are cleaning up. Follow the procedure in Updating a Service (p. 165) and enter 0 in the Number of
tasks field.
Alternatively, you can use the following AWS CLI command to scale down your service. Be sure to
substitute the region name, cluster name, and service name for each service that you are scaling down.
aws ecs update-service --cluster default --service service_name --desired-count 0 --
region us-west-2
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Delete Services
Delete Services
Before you can delete a cluster, you must delete the services inside that cluster. After your service has
scaled down to 0 tasks, you can delete it. For each service inside your cluster, follow the procedures in
Deleting a Service (p. 166) to delete it.
Alternatively, you can use the following AWS CLI command to delete your services. Be sure to substitute
the region name, cluster name, and service name for each service that you are deleting.
aws ecs delete-service --cluster default --service service_name --region us-west-2
Deregister Container Instances
Before you can delete a cluster, you must deregister the container instances inside that cluster. For each
container instance inside your cluster, follow the procedures in Deregister a Container Instance (p. 65)
to deregister it.
Alternatively, you can use the following AWS CLI command to deregister your container instances. Be
sure to substitute the region name, cluster name, and container instance ID for each container instance
that you are deregistering.
aws ecs deregister-container-instance --cluster default --container-
instance container_instance_id --region us-west-2 --force
Delete a Cluster
After you have removed the active resources from your Amazon ECS cluster, you can delete it. Use the
following procedure to delete your cluster.
To delete a cluster
1. Open the Amazon ECS console at https://console.aws.amazon.com/ecs/.
2. From the navigation bar, select the region that your cluster is in.
3. In the navigation pane, select Clusters.
4. On the Clusters page, click the x in the upper-right-hand corner of the cluster you want to delete.
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Delete the AWS CloudFormation Stack
5. Choose Yes, Delete to delete the cluster.
Alternatively, you can use the following AWS CLI command to delete your cluster. Be sure to substitute
the region name and cluster name for each cluster that you are deleting.
aws ecs delete-cluster --cluster default --region us-west-2
Delete the AWS CloudFormation Stack
If you created your Amazon ECS resources by following the console first-run wizard, then your resources
are contained in a AWS CloudFormation stack. You can completely clean up all of your remaining AWS
resources that are associated with this stack by deleting it. Deleting the CloudFormation stack terminates
the EC2 instances, removes the Auto Scaling group, deletes any Elastic Load Balancing load balancers,
and removes the Amazon VPC subnets and Internet gateway associated with the cluster.
To delete the AWS CloudFormation stack
1. Open the AWS CloudFormation console at https://console.aws.amazon.com/cloudformation/.
2. From the navigation bar, select the region that your cluster was created in.
3. Select the stack that is associated with your Amazon ECS resources. The Stack Name value starts
with EC2ContainerService-default.
4. Choose Delete Stack and then choose Yes, Delete to delete your stack resources.
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Cluster Concepts
Amazon ECS Clusters
An Amazon EC2 Container Service (Amazon ECS) cluster is a logical grouping of container instances that
you can place tasks on. When you first use the Amazon ECS service, a default cluster is created for you,
but you can create multiple clusters in an account to keep your resources separate.
Topics
•Cluster Concepts (p. 27)
•Creating a Cluster (p. 27)
•Scaling a Cluster (p. 29)
•Deleting a Cluster (p. 30)
Cluster Concepts
• Clusters can contain multiple different container instance types.
• Clusters are region-specific.
• Container instances can only be a part of one cluster at a time.
• You can create custom IAM policies for your clusters to allow or restrict users' access to specific
clusters. For more information, see the Clusters (p. 222) section in Amazon ECS IAM Policy
Examples (p. 220).
Creating a Cluster
You can create a Amazon ECS cluster using the AWS Management Console, as described in this topic.
Before you begin, be sure that you've completed the steps in Setting Up with Amazon ECS (p. 8). After
you've created your cluster, you can register container instances into it and run tasks and services.
Note
This cluster creation wizard provides a simple way to create the resources that are needed by an
ECS cluster, and it lets you customize several common cluster configuration options. However,
this wizard does allow you to customize every resource option (for example, the container
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instance AMI ID). If your requirements extend beyond what is supported in this wizard, consider
using our reference architecture at https://github.com/awslabs/ecs-refarch-cloudformation.
Please do not attempt to modify the underlying resources directly once they are created by the
wizard.
To create a cluster
1. Open the Amazon ECS console at https://console.aws.amazon.com/ecs/.
2. From the navigation bar, select the region to use.
Note
Amazon ECS is available in the following regions:
Region Name Region
US East (N. Virginia) us-east-1
US East (Ohio) us-east-2
US West (N.
California)
us-west-1
US West (Oregon) us-west-2
EU (Ireland) eu-west-1
EU (London) eu-west-2
EU (Frankfurt) eu-central-1
Asia Pacific (Tokyo) ap-northeast-1
Asia Pacific
(Singapore)
ap-southeast-1
Asia Pacific (Sydney) ap-southeast-2
Canada (Central) ca-central-1
3. In the navigation pane, choose Clusters.
4. On the Clusters page, select Create Cluster.
5. For Cluster name, enter a name for your cluster. Up to 255 letters (uppercase and lowercase),
numbers, hyphens, and underscores are allowed.
6. (Optional) To create an empty cluster with no associated container instances, select Create an
empty cluster and choose Create to create your cluster and finish.
Note
If you create an empty cluster, you need to manually launch container instances into it
before you can run tasks in the cluster. For more information, see Launching an Amazon
ECS Container Instance (p. 42).
7. For EC2 instance type, choose the Amazon EC2 instance type for your container instances. The
instance type that you select determines the resources available for your tasks to run on.
8. For Number of instances, choose the number of Amazon EC2 instances to launch into your cluster.
These instances are launched using the latest Amazon ECS-optimized AMI. For more information, see
Amazon ECS-Optimized AMI (p. 34).
9. For EBS storage (GiB), choose the size of the Amazon EBS volume to use for data storage on your
container instances. By default, the Amazon ECS-optimized AMI launches with an 8 GiB root volume
and a 22 GiB data volume. You can increase the size of the data volume to allow for greater image
and container storage.
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10. For Key pair, choose an Amazon EC2 key pair to use with your container instances for SSH access.
If you do not specify a key pair, you cannot connect to your container instances with SSH. For more
information, see Amazon EC2 Key Pairs in the Amazon EC2 User Guide for Linux Instances.
11. In the Networking section, configure the VPC to launch your container instances into. By default,
the cluster creation wizard creates a new VPC with two subnets in different Availability Zones, and
a security group open to the Internet on port 80. This is a basic setup that works well for an HTTP
service. However, you can modify these settings by following the substeps below.
a. For VPC, choose to create a new VPC, or choose an existing VPC.
b. (Optional) If you chose to create a new VPC, for CIDR Block, choose a CIDR block for your VPC.
For more information, see Your VPC and Subnets in the Amazon VPC User Guide.
c. For Subnets, choose the subnets to use for your VPC. If you chose to create a new VPC, you can
keep the default settings or you can modify them to meet your needs. If you chose to use an
existing VPC, select one or more subnets in that VPC to use for your cluster.
d. For Security group, choose the security group to attach to the container instances in your
cluster. If you choose to create a new security group, you can specify a CIDR block to allow
inbound traffic from (the default 0.0.0.0/0 is open to the Internet) and a single port or a range
of contiguous ports to open on the container instance. For more complicated security group
rules, you can choose an existing security group that you have already created.
Note
You can also choose to create a new security group and then modify the rules after the
cluster is created. For more information, see Amazon EC2 Security Groups for Linux
Instances in the Amazon EC2 User Guide for Linux Instances.
12. In the Container instance IAM role section, choose the IAM role to use with your container
instances. If your account has the ecsInstanceRole that is created for you in the console first run
wizard, that is selected by default. If you do not have this role in your account, you can choose to
create the role, or you can choose another IAM role to use with your container instances.
Important
If you do not launch your container instance with the proper IAM permissions, your
Amazon ECS agent will not connect to your cluster. For more information, see Amazon ECS
Container Instance IAM Role (p. 210).
13. Choose Create to create your cluster.
Scaling a Cluster
If your cluster was created with the console first-run experience described in Getting Started with
Amazon ECS (p. 20) after November 24th, 2015, then the Auto Scaling group associated with the AWS
CloudFormation stack created for your cluster can be scaled up or down to add or remove container
instances. You can perform this scaling operation from within the Amazon ECS console.
If your cluster was not created with the console first-run experience described in Getting Started with
Amazon ECS (p. 20) after November 24th, 2015, then you cannot scale your cluster from the Amazon
ECS console. However, you can still modify existing Auto Scaling groups associated with your cluster
in the Auto Scaling console. If you do not have an Auto Scaling group associated with your cluster, you
can create one from an existing container instance. For more information, see Creating an Auto Scaling
Group Using an EC2 Instance in the Auto Scaling User Guide. You can also manually launch or terminate
container instances from the Amazon EC2 console; for more information see Launching an Amazon ECS
Container Instance (p. 42).
To scale a cluster
1. Open the Amazon ECS console at https://console.aws.amazon.com/ecs/.
2. From the navigation bar, choose the region that your cluster exists in.
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3. In the navigation pane, choose Clusters.
4. Choose the cluster that you want to scale.
5. On the Cluster : name page, choose the ECS Instances tab.
If a Scale ECS Instances button appears, then you can scale your cluster in the next step. If not,
you must manually adjust your Auto Scaling group to scale up or down your instances, or you can
manually launch or terminate your container instances in the Amazon EC2 console.
6. Choose Scale ECS Instances.
7. In the Desired number of instances field, enter the number of instances you wish to scale your
cluster to and choose Scale.
Note
If you reduce the number of container instances in your cluster, any tasks that are running
on terminated instances are stopped.
Deleting a Cluster
If you are finished using a cluster, you can delete it. When you delete a cluster in the Amazon ECS
console, the associated resources that are deleted with it vary depending on how the cluster was created.
Step 5 (p. 31) of the following procedure changes based on that condition.
If your cluster was created with the console first-run experience described in Getting Started with
Amazon ECS (p. 20) after November 24th, 2015, or the cluster creation wizard described in Creating a
Cluster (p. 27), then the AWS CloudFormation stack that was created for your cluster is also deleted
when you delete your cluster.
If your cluster was created manually (without the cluster creation wizard) or with the console first
run experience prior to November 24th, 2015, then you must deregister (or terminate) any container
instances associated with the cluster before you can delete it. For more information, see Deregister
a Container Instance (p. 65). In this case, after the cluster is deleted, you should delete any
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remaining AWS CloudFormation stack resources or Auto Scaling groups associated with the cluster
to avoid incurring any future charges for those resources. For more information, see Delete the AWS
CloudFormation Stack (p. 26).
To delete a cluster
1. Open the Amazon ECS console at https://console.aws.amazon.com/ecs/.
2. From the navigation bar, select the region to use.
Note
Amazon ECS is available in the following regions:
Region Name Region
US East (N. Virginia) us-east-1
US East (Ohio) us-east-2
US West (N.
California)
us-west-1
US West (Oregon) us-west-2
EU (Ireland) eu-west-1
EU (London) eu-west-2
EU (Frankfurt) eu-central-1
Asia Pacific (Tokyo) ap-northeast-1
Asia Pacific
(Singapore)
ap-southeast-1
Asia Pacific (Sydney) ap-southeast-2
Canada (Central) ca-central-1
3. In the navigation pane, choose Clusters.
4. On the Clusters page, choose the cluster you want to delete.
Note
If your cluster has registered container instances, you must deregister or terminate them.
For more information, see Deregister a Container Instance (p. 65).
5. Choose Delete Cluster to delete the cluster. You will see one of two confirmation prompts:
•Deleting the cluster also deletes the CloudFormation stack EC2ContainerService-cluster_name:
Deleting this cluster cleans up the associated resources that were created with the cluster,
including Auto Scaling groups, VPCs or load balancers.
•Deleting the cluster does not affect CloudFormation resources...: Deleting this cluster does
not clean up any resources that are associated with the cluster, including Auto Scaling groups,
VPCs or load balancers. Also, any container instances that are registered with this cluster must
be deregistered or terminated before you can delete the cluster; for more information, see
Deregister a Container Instance (p. 65). You can visit the AWS CloudFormation console at
https://console.aws.amazon.com/cloudformation/ to update or delete any of these resources; for
more information, see Delete the AWS CloudFormation Stack (p. 26).
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Container Instance Concepts
Amazon ECS Container Instances
An Amazon ECS container instance is an Amazon EC2 instance that is running the Amazon ECS container
agent and has been registered into a cluster. When you run tasks with Amazon ECS, your tasks are placed
on your active container instances.
Topics
•Container Instance Concepts (p. 32)
•Container Instance Lifecycle (p. 33)
•Check the Instance Role for Your Account (p. 34)
•Container Instance AMIs (p. 34)
•Launching an Amazon ECS Container Instance (p. 42)
•Bootstrapping Container Instances with Amazon EC2 User Data (p. 45)
•Connect to Your Container Instance (p. 51)
•Using CloudWatch Logs with Container Instances (p. 52)
•Container Instance Draining (p. 59)
•Managing Container Instances Remotely (p. 60)
•Starting a Task at Container Instance Launch Time (p. 63)
•Deregister a Container Instance (p. 65)
Container Instance Concepts
• Your container instance must be running the Amazon ECS container agent to register into one of
your clusters. If you are using the Amazon ECS-optimized AMI, the agent is already installed. To use
a different operating system, install the agent. For more information, see Amazon ECS Container
Agent (p. 68).
• Because the Amazon ECS container agent makes calls to Amazon ECS on your behalf, you must launch
container instances with an IAM role that authenticates to your account and provides the required
resource permissions. For more information, see Amazon ECS Container Instance IAM Role (p. 210).
• If any of the containers associated with your tasks require external connectivity, you can map their
network ports to ports on the host Amazon ECS container instance so they are reachable from the
Internet. Your container instance security group must allow inbound access to the ports you want to
expose. For more information, see Create a Security Group in the Amazon VPC Getting Started Guide.
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Container Instance Lifecycle
• We strongly recommend launching your container instances inside a VPC, because Amazon VPC
delivers more control over your network and offers more extensive configuration capabilities. For more
information, see Amazon EC2 and Amazon Virtual Private Cloud in the Amazon EC2 User Guide for
Linux Instances.
• Container instances need external network access to communicate with the Amazon ECS service
endpoint. If your container instances do not have public IP addresses, then they must use network
address translation (NAT) or an HTTP proxy to provide this access. For more information, see NAT
Instances in the Amazon VPC User Guide and HTTP Proxy Configuration (p. 91) in this guide.
• The type of EC2 instance that you choose for your container instances determines the resources
available in your cluster. Amazon EC2 provides different instance types, each with different CPU,
memory, storage, and networking capacity that you can use to run your tasks. For more information,
see Amazon EC2 Instances.
• Because each container instance has unique state information that is stored locally on the container
instance and within Amazon ECS, they should not be deregistered from one cluster and re-registered
into another. To relocate container instance resources, we recommend that you terminate container
instances from one cluster and launch new container instances with the latest Amazon ECS-optimized
AMI in the new cluster. For more information, see Terminate Your Instance in the Amazon EC2 User
Guide for Linux Instances and Launching an Amazon ECS Container Instance (p. 42).
• Because each container instance has unique state information that is stored locally on the container
instance and within Amazon ECS, you cannot stop a container instance and change its instance type.
Instead, we recommend that you terminate the container instance and launch a new container instance
with the desired instance size and the latest Amazon ECS-optimized AMI in your desired cluster. For
more information, see Terminate Your Instance in the Amazon EC2 User Guide for Linux Instances and
Launching an Amazon ECS Container Instance (p. 42) in this guide.
Container Instance Lifecycle
When the Amazon ECS container agent registers an instance into your cluster, the container instance
reports its status as ACTIVE and its agent connection status as TRUE. This container instance can accept
run task requests.
If you stop (not terminate) an Amazon ECS container instance, the status remains ACTIVE, but the
agent connection status transitions to FALSE within a few minutes. Any tasks that were running on the
container instance stop. If you start the container instance again, the container agent reconnects with
the Amazon ECS service, and you are able to run tasks on the instance again.
Important
If you stop and start a container instance, or reboot that instance, some older versions of the
Amazon ECS container agent register the instance again without deregistering the original
container instance ID. In this case, Amazon ECS lists more container instances in your cluster
than you actually have. (If you have duplicate container instance IDs for the same Amazon
EC2 instance ID, you can safely deregister the duplicates that are listed as ACTIVE with an
agent connection status of FALSE.) This issue is fixed in the current version of the Amazon ECS
container agent. To update to the current version, see Updating the Amazon ECS Container
Agent (p. 73).
If you change the status of a container instance to DRAINING, new tasks are not placed on the container
instance. Any service tasks running on the container instance are removed, if possible, so that you can
perform system updates. For more information, see Container Instance Draining (p. 59).
If you deregister or terminate a container instance, the container instance status changes to INACTIVE
immediately, and the container instance is no longer reported when you list your container instances.
However, you can still describe the container instance for one hour following termination. After one hour,
the instance description is no longer available.
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Check the Instance Role for Your Account
Check the Instance Role for Your Account
The Amazon ECS container agent makes calls to the Amazon ECS APIs on your behalf. Container
instances that run the agent require an IAM policy and role for the service to know that the agent
belongs to you.
In most cases, the Amazon ECS instance role is automatically created for you in the console first-run
experience. You can use the following procedure to check and see if your account already has an Amazon
ECS service role.
To check for the ecsInstanceRole in the IAM console
1. Sign in to the IAM console at https://console.aws.amazon.com/iam/.
2. In the navigation pane, choose Roles.
3. Search the list of roles for ecsInstanceRole. If the role exists, you do not need to create it. If the role
does not exist, follow the procedures in Amazon ECS Container Instance IAM Role (p. 210) to create
the role.
Container Instance AMIs
The basic Amazon EC2 Container Service (Amazon ECS) container instance specification consists of the
following:
Required
• A modern Linux distribution running at least version 3.10 of the Linux kernel.
• The Amazon ECS container agent (preferably the latest version). For more information, see Amazon
ECS Container Agent (p. 68).
• A Docker daemon running at least version 1.5.0, and any Docker runtime dependencies. For more
information, see Check runtime dependencies in the Docker documentation.
Note
For the best experience, we recommend the Docker version that ships with and is tested with
the corresponding Amazon ECS agent version that you are using. For more information, see
Amazon ECS-Optimized AMI Container Agent Versions (p. 72).
Recommended
• An initialization and nanny process to run and monitor the Amazon ECS agent. The Amazon ECS-
optimized AMI uses the ecs-init upstart process. For more information, see the ecs-init project on
GitHub.
The Amazon ECS-optimized AMI is preconfigured with these requirements and recommendations. We
recommend that you use the Amazon ECS-optimized AMI for your container instances unless your
application requires a specific operating system or a Docker version that is not yet available in that AMI.
For more information, see Amazon ECS-Optimized AMI (p. 34).
Amazon ECS-Optimized AMI
The Amazon ECS-optimized AMI is the recommended AMI for you to use to launch your Amazon
ECS container instances. Although you can create your own container instance AMI that meets the
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basic specifications outlined in Container Instance AMIs (p. 34), the Amazon ECS-optimized AMI is
preconfigured and tested on Amazon ECS by AWS engineers. It is the simplest AMI for you to get started
and to get your containers running on AWS quickly.
The current Amazon ECS-optimized AMI (amzn-ami-2016.09.g-amazon-ecs-optimized) consists of:
• The latest minimal version of the Amazon Linux AMI
• The latest version of the Amazon ECS container agent (1.14.1)
• The recommended version of Docker for the latest Amazon ECS container agent (1.12.6)
• The latest version of the ecs-init package to run and monitor the Amazon ECS agent (1.14.1-1)
Topics
•How to Launch the Latest Amazon ECS-Optimized AMI (p. 35)
•Storage Configuration (p. 36)
•Subscribing to Amazon ECS–Optimized AMI Update Notifications (p. 40)
How to Launch the Latest Amazon ECS-Optimized AMI
The following are several ways that you can launch the latest Amazon ECS-optimized AMI into your
cluster:
• The Amazon ECS console first-run wizard launches your container instances with the latest Amazon
ECS-optimized AMI. For more information, see Getting Started with Amazon ECS (p. 20).
• You can launch your container instances manually in the Amazon EC2 console by following the
procedures in Launching an Amazon ECS Container Instance (p. 42). You could also choose the EC2
console link in the table below that corresponds to your cluster's region.
• Use an AMI ID from the table below that corresponds to your cluster's region with the AWS CLI, the
AWS SDKs, or an AWS CloudFormation template to launch your instances.
The current Amazon ECS–optimized AMI IDs by region are listed below for reference.
Region AMI Name AMI ID EC2 console link
us-east-1 amzn-ami-2016.09.g-
amazon-ecs-optimized
ami-275ffe31 Launch instance
us-east-2 amzn-ami-2016.09.g-
amazon-ecs-optimized
ami-62745007 Launch instance
us-west-1 amzn-ami-2016.09.g-
amazon-ecs-optimized
ami-689bc208 Launch instance
us-west-2 amzn-ami-2016.09.g-
amazon-ecs-optimized
ami-62d35c02 Launch instance
eu-west-1 amzn-ami-2016.09.g-
amazon-ecs-optimized
ami-95f8d2f3 Launch instance
eu-west-2 amzn-ami-2016.09.g-
amazon-ecs-optimized
ami-bf9481db Launch instance
eu-central-1 amzn-ami-2016.09.g-
amazon-ecs-optimized
ami-085e8a67 Launch instance
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Region AMI Name AMI ID EC2 console link
ap-northeast-1 amzn-ami-2016.09.g-
amazon-ecs-optimized
ami-f63f6f91 Launch instance
ap-southeast-1 amzn-ami-2016.09.g-
amazon-ecs-optimized
ami-b4ae1dd7 Launch instance
ap-southeast-2 amzn-ami-2016.09.g-
amazon-ecs-optimized
ami-fbe9eb98 Launch instance
ca-central-1 amzn-ami-2016.09.g-
amazon-ecs-optimized
ami-ee58e58a Launch instance
For previous versions of the Amazon ECS-optimized AMI and its corresponding Docker and Amazon ECS
container agent versions, see Amazon ECS-Optimized AMI Container Agent Versions (p. 72).
Storage Configuration
By default, the Amazon ECS-optimized AMI ships with 30 GiB of total storage. You can modify this value
at launch time to increase or decrease the available storage on your container instance. This storage is
used for the operating system and for Docker images and metadata. The sections below describe the
storage configuration of the Amazon ECS-optimized AMI, based on the AMI version.
Version 2015.09.d and Later
Amazon ECS-optimized AMIs from version 2015.09.d and later launch with an 8-GiB volume for the
operating system that is attached at /dev/xvda and mounted as the root of the file system. There is
an additional 22-GiB volume that is attached at /dev/xvdcz that Docker uses for image and metadata
storage. The volume is configured as a Logical Volume Management (LVM) device and it is accessed
directly by Docker via the devicemapper backend. Because the volume is not mounted, you cannot use
standard storage information commands (such as df -h) to determine the available storage. However,
you can use LVM commands and docker info to find the available storage by following the procedure
below. For more information about LVM, see the LVM HOWTO in The Linux Documentation Project.
The docker-storage-setup utility configures the LVM volume group and logical volume for Docker when
the instance launches. By default, docker-storage-setup creates a volume group called docker, adds /
dev/xvdcz as a physical volume to that group. It then creates a logical volume called docker-pool that
uses 99% of the available storage in the volume group. The remaining 1% of the available storage is
reserved for metadata.
Note
Earlier Amazon ECS-optimized AMI versions (2015.09.d to 2016.03.a) create a logical volume
that uses 40% of the available storage in the volume group. When the logical volume becomes
60% full, the logical volume is increased in size by 20%.
To determine the available storage for Docker
• You can use the LVM commands, vgs and lvs, or the docker info command to view available storage
for Docker.
Note
The LVM command output displays storage values in GiB (2^30 bytes), and docker info
displays storage values in GB (10^9 bytes).
a. You can view the available storage in the volume group with the vgs command. This command
shows the total size of the volume group and the available space in the volume group that can
be used to grow the logical volume. The example below shows a 22-GiB volume with 204 MiB of
free space.
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[ec2-user ~]$ sudo vgs
Output:
VG #PV #LV #SN Attr VSize VFree
docker 1 1 0 wz--n- 22.00g 204.00m
b. You can view the available space in the logical volume with the lvs command. The example
below shows a logical volume that is 21.75 GiB in size, and it is 7.63% full. This logical volume
can grow until there is no more free space in the volume group.
[ec2-user@ ~]$ sudo lvs
Output:
LV VG Attr LSize Pool Origin Data% Meta% Move Log Cpy%Sync
Convert
docker-pool docker twi-aot--- 21.75g 7.63 4.96
c. The docker info command also provides information about how much data space it is using,
and how much data space is available. However, its available space value is based on the logical
volume size that it is using.
Note
Because docker info displays storage values as GB (10^9 bytes), instead of GiB (2^30
bytes), the values displayed here look larger for the same amount of storage displayed
with lvs. However, the values are equal (23.35 GB = 21.75 GiB).
[ec2-user ~]$ docker info | grep "Data Space"
Output:
Data Space Used: 1.782 GB
Data Space Total: 23.35 GB
Data Space Available: 21.57 GB
To extend the Docker logical volume
The easiest way to add storage to your container instances is to terminate the existing instances and
launch new ones with larger data storage volumes. However, if you are unable to do this, you can add
storage to the volume group that Docker uses and extend its logical volume by following these steps.
Note
If your container instance storage is filling up too quickly, there are a few actions that you can
take to reduce this effect:
• (Amazon ECS container agent 1.8.0 and later) Reduce the amount of time
that stopped or exited containers remain on your container instances. The
ECS_ENGINE_TASK_CLEANUP_WAIT_DURATION agent configuration variable sets the time duration
to wait from when a task is stopped until the Docker container is removed (by default, this
value is 3 hours). This removes the Docker container data. If this value is set too low, you may
not be able to inspect your stopped containers or view the logs before they are removed. For
more information, see Amazon ECS Container Agent Configuration (p. 79).
• Remove non-running containers and unused images from your container instances. You can
use the following example commands to manually remove stopped containers and unused
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images. Deleted containers cannot be inspected later, and deleted images must be pulled
again before starting new containers from them.
To remove non-running containers, execute the following command on your container
instance:
$ docker rm $(docker ps -aq)
To remove unused images, execute the following command on your container instance:
$ docker rmi $(docker images -q)
• Remove unused data blocks within containers. You can use the following command to run
fstrim on any running container and discard any data blocks that are unused by the container
file system.
$ sudo sh -c "docker ps -q | xargs docker inspect --format='{{ .State.Pid }}' |
xargs -IZ fstrim /proc/Z/root/"
1. Create a new Amazon EBS volume in the same Availability Zone as your container instance. For more
information, see Creating an Amazon EBS Volume in the Amazon EC2 User Guide for Linux Instances.
2. Attach the volume to your container instance. The default location for the Docker data volume is /
dev/xvdcz. For consistency, attach additional volumes in reverse alphabetical order from that device
name (for example, /dev/xvdcy). For more information, see Attaching an Amazon EBS Volume to an
Instance in the Amazon EC2 User Guide for Linux Instances.
3. Connect to your container instance using SSH. For more information, see Connect to Your Container
Instance (p. 51).
4. Check the size of your docker-pool logical volume. The example below shows a logical volume of
409.19 GiB.
[ec2-user ~]$ sudo lvs
Output:
LV VG Attr LSize Pool Origin Data% Meta% Move Log Cpy%Sync
Convert
docker-pool docker twi-aot--- 409.19g 0.16 0.08
5. Check the current available space in your volume group. The example below shows 612.75 GiB in the
VFree column.
[ec2-user ~]$ sudo vgs
Output:
VG #PV #LV #SN Attr VSize VFree
docker 1 1 0 wz--n- 1024.00g 612.75g
6. Add the new volume to the docker volume group, substituting the device name to which you
attached the new volume. In this example, a 1-TiB volume was previously added and attached to /
dev/xvdcy.
[ec2-user ~]$ sudo vgextend docker /dev/xvdcy
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Physical volume "/dev/sdcy" successfully created
Volume group "docker" successfully extended
7. Verify that your volume group size has increased with the vgs command. The VFree column should
show the increased storage size. The example below now has 1.6 TiB in the VFree column, which is
1 TiB larger than it was previously. Your VFree column should be the sum of the original VFree value
and the size of the volume you attached.
[ec2-user ~]$ sudo vgs
Output:
VG #PV #LV #SN Attr VSize VFree
docker 2 1 0 wz--n- 2.00t 1.60t
8. Extend the docker-pool logical volume with the size of the volume you added earlier. The command
below adds 1024 GiB to the logical volume, which is entered as 1024G.
[ec2-user ~]$ sudo lvextend -L+1024G /dev/docker/docker-pool
Output:
Size of logical volume docker/docker-pool_tdata changed from 409.19 GiB (104752
extents) to 1.40 TiB (366896 extents).
Logical volume docker-pool successfully resized
9. Verify that your logical volume has increased in size.
[ec2-user ~]$ sudo lvs
Output:
LV VG Attr LSize Pool Origin Data% Meta% Move Log Cpy%Sync
Convert
docker-pool docker twi-aot--- 1.40t 0.04 0.12
10. (Optional) Verify that docker info also recognizes the added storage space.
Note
Because docker info displays storage values as GB (10^9 bytes), instead of GiB (2^30 bytes),
the values displayed here look larger for the same amount of storage displayed with lvs.
However, the values are equal (1.539 TB =1.40 TiB).
[ec2-user ~]$ docker info | grep "Data Space"
Output:
Data Space Used: 109.6 MB
Data Space Total: 1.539 TB
Data Space Available: 1.539 TB
Version 2015.09.c and Earlier
Amazon ECS-optimized AMIs from version 2015.09.c and earlier launch with a single 30-GiB volume that
is attached at /dev/xvda and mounted as the root of the file system. This volume shares the operating
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system and all Docker images and metadata. You can determine the available storage on your container
instance with standard storage information commands (such as df -h).
There is no practical way to add storage (that Docker can use) to instances launched from these AMIs
without stopping them. If you find that your container instances need more storage than the default 30
GiB, you should terminate each instance. Then, launch another in its place with the latest Amazon ECS-
optimized AMI and a large enough data storage volume.
Subscribing to Amazon ECS–Optimized AMI Update
Notifications
The Amazon ECS-optimized AMI receives regular updates for agent changes, Docker version updates,
and Linux kernel security updates. You can subscribe to the AMI update Amazon SNS topic to receive
notifications when a new Amazon ECS–optimized AMI is available. Notifications are available in all
formats that Amazon SNS supports.
Note
Your user account must have sns::subscribe IAM permissions to subscribe to an SNS topic.
You can subscribe an Amazon SQS queue to this notification topic, but you must use a topic ARN that is
in the same region. For more information, see Tutorial: Subscribing an Amazon SQS Queue to an Amazon
SNS Topic in the Amazon Simple Queue Service Developer Guide.
You can also use an AWS Lambda function to trigger events when notifications are received. For more
information, see Invoking Lambda functions using Amazon SNS notifications in the Amazon Simple
Notification Service Developer Guide.
The Amazon SNS topic ARNs for each region are shown below.
AWS Region Amazon SNS Topic ARN
us-east-1 arn:aws:sns:us-east-1:177427601217:ecs-
optimized-amazon-ami-update
us-east-2 arn:aws:sns:us-east-2:177427601217:ecs-
optimized-amazon-ami-update
us-west-1 arn:aws:sns:us-west-1:177427601217:ecs-
optimized-amazon-ami-update
us-west-2 arn:aws:sns:us-west-2:177427601217:ecs-
optimized-amazon-ami-update
eu-west-1 arn:aws:sns:eu-west-1:177427601217:ecs-
optimized-amazon-ami-update
eu-west-2 arn:aws:sns:eu-west-2:177427601217:ecs-
optimized-amazon-ami-update
eu-central-1 arn:aws:sns:eu-central-1:177427601217:ecs-
optimized-amazon-ami-update
ap-northeast-1 arn:aws:sns:ap-
northeast-1:177427601217:ecs-optimized-
amazon-ami-update
ap-southeast-1 arn:aws:sns:ap-
southeast-1:177427601217:ecs-optimized-
amazon-ami-update
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AWS Region Amazon SNS Topic ARN
ap-southeast-2 arn:aws:sns:ap-
southeast-2:177427601217:ecs-optimized-
amazon-ami-update
ca-central-1 arn:aws:sns:ca-central-1:177427601217:ecs-
optimized-amazon-ami-update
To subscribe to AMI update notification emails in the AWS Management Console
1. Open the Amazon SNS console at https://console.aws.amazon.com/sns/v2/home.
2. In the region list, choose the same region as the topic ARN to which to subscribe. This example uses
the us-west-2 region.
3. Choose Create subscription.
4. In the Create Subscription dialog box, for Topic ARN, paste the Amazon ECS-optimized AMI update
topic ARN: arn:aws:sns:us-west-2:177427601217:ecs-optimized-amazon-ami-update.
5. For Protocol, choose Email. For Endpoint, type an email address you can use to receive the
notification.
6. Choose Create subscription.
7. In your email application, open the message from AWS Notifications and open the link to confirm
your subscription.
Your web browser displays a confirmation response from Amazon SNS.
To subscribe to AMI update notification emails with the AWS CLI
1. Run the following command with the AWS CLI:
aws sns --region us-west-2 subscribe --topic-arn arn:aws:sns:us-
west-2:177427601217:ecs-optimized-amazon-ami-update --protocol email --notification-
endpoint your_email@your_domain.com
2. In your email application, open the message from AWS Notifications and open the link to confirm
your subscription.
Your web browser displays a confirmation response from Amazon SNS.
Amazon SNS Message Format
An example AMI update notification message is shown below:
{
"ECSAgent": {
"ReleaseVersion": "1.14.1"
},
"ECSAmis": [
{
"ReleaseVersion": "2016.09.g",
"AgentVersion": "1.14.1",
"ReleaseNotes": "This AMI includes the latest ECS agent 2016.09.g",
"OsType": "linux",
"OperatingSystemName": "Amazon Linux",
"Regions": {
"ap-northeast-1": {
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"Name": "amzn-ami-2016.09.g-amazon-ecs-optimized",
"ImageId": "ami-f63f6f91"
},
"ap-southeast-1": {
"Name": "amzn-ami-2016.09.g-amazon-ecs-optimized",
"ImageId": "ami-b4ae1dd7"
},
"ap-southeast-2": {
"Name": "amzn-ami-2016.09.g-amazon-ecs-optimized",
"ImageId": "ami-fbe9eb98"
},
"ca-central-1": {
"Name": "amzn-ami-2016.09.g-amazon-ecs-optimized",
"ImageId": "ami-ee58e58a"
},
"eu-central-1": {
"Name": "amzn-ami-2016.09.g-amazon-ecs-optimized",
"ImageId": "ami-085e8a67"
},
"eu-west-1": {
"Name": "amzn-ami-2016.09.g-amazon-ecs-optimized",
"ImageId": "ami-95f8d2f3"
},
"eu-west-2": {
"Name": "amzn-ami-2016.09.g-amazon-ecs-optimized",
"ImageId": "ami-bf9481db"
},
"us-east-1": {
"Name": "amzn-ami-2016.09.g-amazon-ecs-optimized",
"ImageId": "ami-275ffe31"
},
"us-east-2": {
"Name": "amzn-ami-2016.09.g-amazon-ecs-optimized",
"ImageId": "ami-62745007"
},
"us-west-1": {
"Name": "amzn-ami-2016.09.g-amazon-ecs-optimized",
"ImageId": "ami-689bc208"
},
"us-west-2": {
"Name": "amzn-ami-2016.09.g-amazon-ecs-optimized",
"ImageId": "ami-62d35c02"
}
}
}
]
}
Launching an Amazon ECS Container Instance
You can launch an Amazon ECS container instance using the AWS Management Console, as described
in this topic. Before you begin, be sure that you've completed the steps in Setting Up with Amazon
ECS (p. 8). After you've launched your instance, you can use it to run tasks.
To launch a container instance
1. Open the Amazon EC2 console at https://console.aws.amazon.com/ec2/.
2. From the navigation bar, select the region to use.
Note
Amazon ECS is available in the following regions:
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Region Name Region
US East (N. Virginia) us-east-1
US East (Ohio) us-east-2
US West (N.
California)
us-west-1
US West (Oregon) us-west-2
EU (Ireland) eu-west-1
EU (London) eu-west-2
EU (Frankfurt) eu-central-1
Asia Pacific (Tokyo) ap-northeast-1
Asia Pacific
(Singapore)
ap-southeast-1
Asia Pacific (Sydney) ap-southeast-2
Canada (Central) ca-central-1
3. From the console dashboard, choose Launch Instance.
4. On the Choose an Amazon Machine Image (AMI) page, choose Community AMIs.
5. Choose an AMI for your container instance. You can choose the Amazon ECS-optimized AMI,
or another operating system, such as CoreOS or Ubuntu. If you do not choose the Amazon
ECS-optimized AMI, you must follow the procedures in Installing the Amazon ECS Container
Agent (p. 68).
Note
For Amazon ECS-specific CoreOS installation instructions, see https://coreos.com/docs/
running-coreos/cloud-providers/ecs/.
To use the Amazon ECS-optimized AMI, type amazon-ecs-optimized in the Search community
AMIs field and press the Enter key. Choose Select next to the amzn-ami-2016.09.g-amazon-ecs-
optimized AMI. The current Amazon ECS–optimized AMI IDs by region are listed below for reference.
Region AMI ID
us-east-1 ami-275ffe31
us-east-2 ami-62745007
us-west-1 ami-689bc208
us-west-2 ami-62d35c02
eu-west-1 ami-95f8d2f3
eu-west-2 ami-bf9481db
eu-central-1 ami-085e8a67
ap-northeast-1 ami-f63f6f91
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Region AMI ID
ap-southeast-1 ami-b4ae1dd7
ap-southeast-2 ami-fbe9eb98
ca-central-1 ami-ee58e58a
6. On the Choose an Instance Type page, you can select the hardware configuration of your instance.
The t2.micro instance type is selected by default. The instance type that you select determines the
resources available for your tasks to run on.
7. Choose Next: Configure Instance Details.
8. On the Configure Instance Details page, set the Auto-assign Public IP field depending on whether
you want your instance to be accessible from the public Internet. If your instance should be
accessible from the Internet, verify that the Auto-assign Public IP field is set to Enable. If your
instance should not be accessible from the Internet, set this field to Disable.
Note
Container instances need external network access to communicate with the Amazon ECS
service endpoint. If your container instances do not have public IP addresses, then they
must use network address translation (NAT) or an HTTP proxy to provide this access.
For more information, see NAT Instances in the Amazon VPC User Guide and HTTP Proxy
Configuration (p. 91) in this guide.
9. On the Configure Instance Details page, select the ecsInstanceRole IAM role value that you
created for your container instances in Setting Up with Amazon ECS (p. 8).
Important
If you do not launch your container instance with the proper IAM permissions, your Amazon
ECS agent cannot connect to your cluster. For more information, see Amazon ECS Container
Instance IAM Role (p. 210).
10. (Optional) Configure your Amazon ECS container instance with user data, such as the agent
environment variables from Amazon ECS Container Agent Configuration (p. 79). Amazon EC2 user
data scripts are executed only one time, when the instance is first launched.
By default, your container instance launches into your default cluster. To launch into a non-default
cluster, choose the Advanced Details list. Then, paste the following script into the User data field,
replacing your_cluster_name with the name of your cluster.
#!/bin/bash
echo ECS_CLUSTER=your_cluster_name >> /etc/ecs/ecs.config
Or, if you have an ecs.config file in Amazon S3 and have enabled Amazon S3 read-only access to
your container instance role, choose the Advanced Details list. Then, paste the following script into
the User data field, replacing your_bucket_name with the name of your bucket to install the AWS CLI
and write your configuration file at launch time.
Note
For more information about this configuration, see Storing Container Instance
Configuration in Amazon S3 (p. 84).
#!/bin/bash
yum install -y aws-cli
aws s3 cp s3://your_bucket_name/ecs.config /etc/ecs/ecs.config
For more information, see Bootstrapping Container Instances with Amazon EC2 User Data (p. 45).
11. Choose Next: Add Storage.
12. On the Add Storage page, configure the storage for your container instance.
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Bootstrap Container Instances
If you are using an Amazon ECS-optimized AMI before the 2015.09.d version, your instance has a
single volume that is shared by the operating system and Docker.
If you are using the 2015.09.d or later Amazon ECS-optimized AMI, your instance has two volumes
configured. The Root volume is for the operating system's use, and the second Amazon EBS volume
(attached to /dev/xvdcz) is for Docker's use.
You can optionally increase or decrease the volume sizes for your instance to meet your application
needs.
13. Choose Review and Launch.
14. On the Review Instance Launch page, under Security Groups, you see that the wizard created and
selected a security group for you. Instead, select the security group that you created in Setting Up
with Amazon ECS (p. 8) using the following steps:
a. Choose Edit security groups.
b. On the Configure Security Group page, select the Select an existing security group option.
c. Select the security group you created for your container instance from the list of existing
security groups, and choose Review and Launch.
15. On the Review Instance Launch page, choose Launch.
16. In the Select an existing key pair or create a new key pair dialog box, choose Choose an existing
key pair, then select the key pair that you created when getting set up.
When you are ready, select the acknowledgment field, and then choose Launch Instances.
17. A confirmation page lets you know that your instance is launching. Choose View Instances to close
the confirmation page and return to the console.
18. On the Instances screen, you can view the status of your instance. It takes a short time for an
instance to launch. When you launch an instance, its initial state is pending. After the instance starts,
its state changes to running, and it receives a public DNS name. If the Public DNS column is hidden,
choose Show/Hide, Public DNS.
Bootstrapping Container Instances with Amazon
EC2 User Data
When you launch an Amazon ECS container instance, you have the option of passing user data to
the instance. The data can be used to perform common automated configuration tasks and even run
scripts when the instance boots. For Amazon ECS, the most common use cases for user data are to pass
configuration information to the Docker daemon and the Amazon ECS container agent.
You can pass multiple types of user data to Amazon EC2, including cloud boothooks, shell scripts, and
cloud-init directives. For more information about these and other format types, see the Cloud-Init
documentation.
You can pass this user data into the Amazon EC2 launch wizard in Step 10 (p. 44) of Launching an
Amazon ECS Container Instance (p. 42).
Topics
•Amazon ECS Container Agent (p. 46)
•Docker Daemon (p. 46)
•cloud-init-per Utility (p. 46)
•MIME Multi Part Archive (p. 47)
•Example Container Instance User Data Configuration Scripts (p. 48)
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Amazon ECS Container Agent
The Amazon ECS-optimized AMI looks for agent configuration data in the /etc/ecs/ecs.config file
when the container agent starts. You can specify this configuration data at launch with Amazon EC2 user
data. For a complete list of available Amazon ECS container agent configuration variables, see Amazon
ECS Container Agent Configuration (p. 79).
To set only a single agent configuration variable, such as the cluster name, use echo to copy the variable
to the configuration file:
#!/bin/bash
echo "ECS_CLUSTER=MyCluster" >> /etc/ecs/ecs.config
If you have multiple variables to write to /etc/ecs/ecs.config, use the following heredoc format. This
format writes everything between the lines beginning with cat and EOF to the configuration file.
#!/bin/bash
cat <<'EOF' >> /etc/ecs/ecs.config
ECS_CLUSTER=MyCluster
ECS_ENGINE_AUTH_TYPE=docker
ECS_ENGINE_AUTH_DATA={"https://index.docker.io/v1/":
{"username":"my_name","password":"my_password","email":"email@example.com"}}
ECS_LOGLEVEL=debug
EOF
Docker Daemon
You can specify Docker daemon configuration information with Amazon EC2 user data, but this
configuration data must be written before the Docker daemon starts. The cloud-boothook user data
format executes earlier in the boot process than a user data shell script. For a complete list of Docker
daemon configuration options, see the Docker daemon documentation.
By default, cloud-boothook user data is run at every instance boot, so you must create a mechanism
to prevent the boothook from running multiple times. The cloud-init-per utility is provided to control
boothook frequency in this manner. For more information, see cloud-init-per Utility (p. 46).
In the example below, the --storage-opt dm.basesize=20G option is appended to any existing options
in the Docker daemon configuration file, /etc/sysconfig/docker.
#cloud-boothook
cloud-init-per once docker_options echo 'OPTIONS="${OPTIONS} --storage-opt
dm.basesize=20G"' >> /etc/sysconfig/docker
To write multiple lines to a file, use the following heredoc format to accomplish the same goal:
#cloud-boothook
cloud-init-per instance docker_options cat <<'EOF' >> /etc/sysconfig/docker
OPTIONS="${OPTIONS} --storage-opt dm.basesize=20G"
HTTP_PROXY=http://proxy.example.com:80/
EOF
cloud-init-per Utility
The cloud-init-per utility is provided by the cloud-init package to help you create boothook commands
for instances that run at a specified frequency.
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The cloud-init-per utility syntax is as follows:
cloud-init-per frequency name cmd [ arg1 [ arg2 [ ... ] ]
frequency
How often the boothook should run.
• Specify once to never run again, even with a new instance ID.
• Specify instance to run on the first boot for each new instance launch. For example, if you create
an AMI from the instance after the boothook has run, it still runs again on subsequent instances
launched from that AMI.
• Specify always to run at every boot.
name
The name to include in the semaphore file path that is written when the boothook runs. The
semaphore file is written to /var/lib/cloud/instances/instance_id/sem/bootper.name.instance.
cmd
The command and arguments that the boothook should execute.
In the example below, the command echo 'OPTIONS="${OPTIONS} --storage-opt dm.basesize=20G"'
>> /etc/sysconfig/docker is executed only once. A semaphore file is written that contains its name.
#cloud-boothook
cloud-init-per once docker_options echo 'OPTIONS="${OPTIONS} --storage-opt
dm.basesize=20G"' >> /etc/sysconfig/docker
The semaphore file records the exit code of the command and a UNIX timestamp for when it was
executed.
[ec2-user ~]$ cat /var/lib/cloud/instances/i-0c7f87d7611b2165e/sem/
bootper.docker_options.instance
Output:
0 1488410363
MIME Multi Part Archive
You can combine multiple user data blocks together into a single user data block called a MIME multi-
part file. For example, you might want to combine a cloud boothook that configures the Docker daemon
with a user data shell script that writes configuration information for the Amazon ECS container agent.
A MIME multi-part file consists of the following components:
• The content type and part boundary declaration: Content-Type: multipart/mixed;
boundary="==BOUNDARY=="
• The MIME version declaration: MIME-Version: 1.0
• One or more user data blocks, which contain the following components:
• The opening boundary, which signals the beginning of a user data block: --==BOUNDARY==
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• The content type declaration for the block (for the list of content types, see the Cloud-Init
documentation): Content-Type: text/cloud-boothook; charset="us-ascii"
• The content of the user data, for example, a list of shell commands or cloud-init directives
• The closing boundary, which signals the end of the MIME multi-part file: --==BOUNDARY==--
Example MIME multi-part file
This example MIME multi-part file configures the Docker base device size to 20 GiB and configures the
Amazon ECS container agent to register the instance into the cluster named my-ecs-cluster.
Content-Type: multipart/mixed; boundary="==BOUNDARY=="
MIME-Version: 1.0
--==BOUNDARY==
Content-Type: text/cloud-boothook; charset="us-ascii"
# Set Docker daemon options
cloud-init-per once docker_options echo 'OPTIONS="${OPTIONS} --storage-opt
dm.basesize=20G"' >> /etc/sysconfig/docker
--==BOUNDARY==
Content-Type: text/x-shellscript; charset="us-ascii"
#!/bin/bash
# Set any ECS agent configuration options
echo "ECS_CLUSTER=my-ecs-cluster" >> /etc/ecs/ecs.config
--==BOUNDARY==--
Example Container Instance User Data Configuration
Scripts
The following example user data scripts configure an Amazon ECS container instance at launch.
Ubuntu Container Instance with systemd
This example user data script configures an Ubuntu 16.04 instance to:
• Install Docker
• Create the required iptables rules for IAM roles for tasks
• Create the required directories for the Amazon ECS container agent
• Write the Amazon ECS container agent configuration file
• Write the systemd unit file to monitor the agent
• Enable and start the systemd unit
You can use this script for your own container instances, provided that they are launched from an Ubuntu
16.04 AMI. Be sure to replace the ECS_CLUSTER=default line in the configuration file to specify your own
cluster name, if you are not using the default cluster. For more information about launching container
instances, see Launching an Amazon ECS Container Instance (p. 42).
#!/bin/bash
# Install Docker
apt-get update -y && apt-get install -y docker.io
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# Set iptables rules
echo 'net.ipv4.conf.all.route_localnet = 1' >> /etc/sysctl.conf
sysctl -p /etc/sysctl.conf
iptables -t nat -A PREROUTING -p tcp -d 169.254.170.2 --dport 80 -j DNAT --to-destination
127.0.0.1:51679
iptables -t nat -A OUTPUT -d 169.254.170.2 -p tcp -m tcp --dport 80 -j REDIRECT --to-ports
51679
# Write iptables rules to persist after reboot
iptables-save > /etc/iptables/rules.v4
# Create directories for ECS agent
mkdir -p /var/log/ecs /var/lib/ecs/data /etc/ecs
# Write ECS config file
cat << EOF > /etc/ecs/ecs.config
ECS_DATADIR=/data
ECS_ENABLE_TASK_IAM_ROLE=true
ECS_ENABLE_TASK_IAM_ROLE_NETWORK_HOST=true
ECS_LOGFILE=/log/ecs-agent.log
ECS_AVAILABLE_LOGGING_DRIVERS=["json-file","awslogs"]
ECS_LOGLEVEL=info
ECS_CLUSTER=default
EOF
# Write systemd unit file
cat << EOF > /etc/systemd/system/docker-container@ecs-agent.service
[Unit]
Description=Docker Container %I
Requires=docker.service
After=docker.service
[Service]
Restart=always
ExecStart=/usr/bin/docker run --name %i \
--restart=on-failure:10 \
--volume=/var/run:/var/run \
--volume=/var/log/ecs/:/log \
--volume=/var/lib/ecs/data:/data \
--volume=/etc/ecs:/etc/ecs \
--net=host \
--env-file=/etc/ecs/ecs.config \
amazon/amazon-ecs-agent:latest
ExecStop=/usr/bin/docker rm -f %i
[Install]
WantedBy=default.target
EOF
systemctl enable docker-container@ecs-agent.service
systemctl start docker-container@ecs-agent.service
CentOS Container Instance with systemd and SELinux
This example user data script configures a CentOS 7 instance with SELinux enabled to:
• Install Docker
• Create the required iptables rules for IAM roles for tasks
• Create the required directories for the Amazon ECS container agent
• Write the Amazon ECS container agent configuration file
• Write the systemd unit file to monitor the agent
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• Enable and start the systemd unit
Note
The docker run command in the systemd unit file below contains the required modifications for
SELinux, including the --privileged flag, and the :Z suffixes to the volume mounts.
You can use this script for your own container instances (provided that they are launched from an
CentOS 7 AMI), but be sure to replace the ECS_CLUSTER=default line in the configuration file to specify
your own cluster name (if you are not using the default cluster). For more information about launching
container instances, see Launching an Amazon ECS Container Instance (p. 42).
#!/bin/bash
# Install Docker
yum install -y docker
# Set iptables rules
echo 'net.ipv4.conf.all.route_localnet = 1' >> /etc/sysctl.conf
sysctl -p /etc/sysctl.conf
iptables -t nat -A PREROUTING -p tcp -d 169.254.170.2 --dport 80 -j DNAT --to-destination
127.0.0.1:51679
iptables -t nat -A OUTPUT -d 169.254.170.2 -p tcp -m tcp --dport 80 -j REDIRECT --to-ports
51679
# Write iptables rules to persist after reboot
iptables-save > /etc/sysconfig/iptables
# Create directories for ECS agent
mkdir -p /var/log/ecs /var/lib/ecs/data /etc/ecs
# Write ECS config file
cat << EOF > /etc/ecs/ecs.config
ECS_DATADIR=/data
ECS_ENABLE_TASK_IAM_ROLE=true
ECS_ENABLE_TASK_IAM_ROLE_NETWORK_HOST=true
ECS_LOGFILE=/log/ecs-agent.log
ECS_AVAILABLE_LOGGING_DRIVERS=["json-file","awslogs"]
ECS_LOGLEVEL=info
ECS_CLUSTER=default
EOF
# Write systemd unit file
cat << EOF > /etc/systemd/system/docker-container@ecs-agent.service
[Unit]
Description=Docker Container %I
Requires=docker.service
After=docker.service
[Service]
Restart=always
ExecStart=/usr/bin/docker run --name %i \
--privileged \
--restart=on-failure:10 \
--volume=/var/run:/var/run \
--volume=/var/log/ecs/:/log:Z \
--volume=/var/lib/ecs/data:/data:Z \
--volume=/etc/ecs:/etc/ecs \
--net=host \
--env-file=/etc/ecs/ecs.config \
amazon/amazon-ecs-agent:latest
ExecStop=/usr/bin/docker rm -f %i
[Install]
WantedBy=default.target
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EOF
systemctl enable docker-container@ecs-agent.service
systemctl start docker-container@ecs-agent.service
Connect to Your Container Instance
To perform basic administrative tasks on your instance, such as updating or installing software or
accessing diagnostic logs, connect to the instance using SSH. To connect to your instance using SSH, your
container instances must meet the following prerequisites:
• Your container instances need external network access to connect using SSH. If your container
instances are running in a private VPC, they need an SSH bastion instance to provide this access. For
more information, see the Securely connect to Linux instances running in a private Amazon VPC blog
post.
• Your container instances must have been launched with a valid Amazon EC2 key pair. Amazon ECS
container instances have no password, and you use a key pair to log in using SSH. If you did not specify
a key pair when you launched your instance, there is no way to connect to the instance.
• SSH uses port 22 for communication. Port 22 must be open in your container instance security group
for you to connect to your instance using SSH.
Note
The Amazon ECS console first-run experience creates a security group for your container
instances without inbound access on port 22. If your container instances were launched from
the console first-run experience, add inbound access to port 22 on the security group used for
those instances. For more information, see Authorizing Network Access to Your Instances in
the Amazon EC2 User Guide for Linux Instances.
To connect to your container instance
1. Find the public IP or DNS address for your container instance.
a. Open the Amazon ECS console at https://console.aws.amazon.com/ecs/.
b. Select the cluster that hosts your container instance.
c. On the Cluster page, choose ECS Instances.
d. On the Container Instance column, select the container instance to connect to.
e. On the Container Instance page, record the Public IP or Public DNS for your instance.
2. Find the default username for your container instance AMI. The user name for instances launched
with the Amazon ECS-optimized AMI is ec2-user. For Ubuntu AMIs, the default user name is ubuntu.
For CoreOS, the default user name is core.
3. If you are using a macOS or Linux computer, connect to your instance with the following command,
substituting the path to your private key and the public address for your instance:
$ ssh -i /path/to/my-key-pair.pem ec2-user@ec2-198-51-100-1.compute-1.amazonaws.com
If you are using a Windows computer, see Connecting to Your Linux Instance from Windows Using
PuTTY in the Amazon EC2 User Guide for Linux Instances.
Important
If you experience any issues connecting to your instance, see Troubleshooting Connecting to
Your Instance in the Amazon EC2 User Guide for Linux Instances.
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CloudWatch Logs
Using CloudWatch Logs with Container Instances
You can configure your container instances to send log information to CloudWatch Logs. This enables
you to view different logs from your container instances in one convenient location. This topic helps you
get started using CloudWatch Logs on your container instances that were launched with the Amazon
ECS-optimized AMI.
To send container logs from your tasks to CloudWatch Logs, see Using the awslogs Log Driver (p. 117).
For more information on CloudWatch Logs, see Monitoring Log Files in the Amazon CloudWatch User
Guide.
Topics
•CloudWatch Logs IAM Policy (p. 52)
•Installing the CloudWatch Logs Agent (p. 53)
•Configuring and Starting the CloudWatch Logs Agent (p. 53)
•Viewing CloudWatch Logs (p. 56)
•Configuring CloudWatch Logs at Launch with User Data (p. 57)
CloudWatch Logs IAM Policy
Before your container instances can send log data to CloudWatch Logs, you must create an IAM policy to
allow your container instances to use the CloudWatch Logs APIs, and then you must attach that policy to
the ecsInstanceRole.
To create the ECS-CloudWatchLogs IAM policy
1. Open the IAM console at https://console.aws.amazon.com/iam/.
2. In the navigation pane, choose Policies.
3. Choose Create Policy.
4. On the Create Policy page, choose Create Your Own Policy.
5. On the Review Policy page, enter the following information and choose Create Policy.
a. In the Policy Name field, enter ECS-CloudWatchLogs.
b. In the Policy Document field, paste the following policy.
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Action": [
"logs:CreateLogGroup",
"logs:CreateLogStream",
"logs:PutLogEvents",
"logs:DescribeLogStreams"
],
"Resource": [
"arn:aws:logs:*:*:*"
]
}
]
}
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To attach the ECS-CloudWatchLogs policy to your ecsInstanceRole
1. Open the IAM console at https://console.aws.amazon.com/iam/.
2. In the navigation pane, choose Roles.
3. Choose ecsInstanceRole. If the role does not exist, follow the procedures in Amazon ECS Container
Instance IAM Role (p. 210) to create the role.
4. Choose the Permissions tab.
5. In the Managed Policies section, choose Attach Policy.
6. In the Filter box, type ECS-CloudWatchLogs to narrow the available policies to attach.
7. Check the box to the left of the ECS-CloudWatchLogs policy and choose Attach Policy.
Installing the CloudWatch Logs Agent
After you have added the ECS-CloudWatchLogs policy to your ecsInstanceRole, you can install the
CloudWatch Logs agent on your container instances.
Note
This procedure was written for the Amazon ECS-optimized AMI, and may not work on other
operating systems. For information on installing the agent on other operating systems, see
Getting Started with CloudWatch Logs in the Amazon CloudWatch User Guide.
To install the CloudWatch Logs agent
• Run the following command to install the CloudWatch Logs agent.
[ec2-user ~]$ sudo yum install -y awslogs
After you have installed the agent, proceed to the next section to configure the agent.
Configuring and Starting the CloudWatch Logs Agent
The CloudWatch Logs agent configuration file (/etc/awslogs/awslogs.conf) describes the log files
to send to CloudWatch Logs. The agent configuration file's [general] section defines common
configurations that apply to all log streams, and you can add individual log stream sections for each file
on your container instances that you want to monitor. For more information, see CloudWatch Logs Agent
Reference in the Amazon CloudWatch User Guide.
The example configuration file below is configured for the Amazon ECS-optimized AMI, and it provides
log streams for several common log files:
/var/log/dmesg
The message buffer of the Linux kernel.
/var/log/messages
Global system messages.
/var/log/docker
Docker daemon log messages.
/var/log/ecs/ecs-init.log
Log messages from the ecs-init upstart job.
/var/log/ecs/ecs-agent.log
Log messages from the Amazon ECS container agent.
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/var/log/ecs/audit.log
Log messages from the IAM roles for tasks credential provider.
You can use the example file below for your Amazon ECS container instances, but you must substitute
the {cluster} and {container_instance_id} entries with the cluster name and container instance ID
for each container instance so that the log streams are grouped by cluster name and separate for each
individual container instance. The procedure that follows the example configuration file has steps to
replace the cluster name and container instance ID placeholders.
[general]
state_file = /var/lib/awslogs/agent-state
[/var/log/dmesg]
file = /var/log/dmesg
log_group_name = /var/log/dmesg
log_stream_name = {cluster}/{container_instance_id}
[/var/log/messages]
file = /var/log/messages
log_group_name = /var/log/messages
log_stream_name = {cluster}/{container_instance_id}
datetime_format = %b %d %H:%M:%S
[/var/log/docker]
file = /var/log/docker
log_group_name = /var/log/docker
log_stream_name = {cluster}/{container_instance_id}
datetime_format = %Y-%m-%dT%H:%M:%S.%f
[/var/log/ecs/ecs-init.log]
file = /var/log/ecs/ecs-init.log.*
log_group_name = /var/log/ecs/ecs-init.log
log_stream_name = {cluster}/{container_instance_id}
datetime_format = %Y-%m-%dT%H:%M:%SZ
[/var/log/ecs/ecs-agent.log]
file = /var/log/ecs/ecs-agent.log.*
log_group_name = /var/log/ecs/ecs-agent.log
log_stream_name = {cluster}/{container_instance_id}
datetime_format = %Y-%m-%dT%H:%M:%SZ
[/var/log/ecs/audit.log]
file = /var/log/ecs/audit.log.*
log_group_name = /var/log/ecs/audit.log
log_stream_name = {cluster}/{container_instance_id}
datetime_format = %Y-%m-%dT%H:%M:%SZ
To configure the CloudWatch Logs agent
1. Back up the existing CloudWatch Logs agent configuration file.
[ec2-user ~]$ sudo mv /etc/awslogs/awslogs.conf /etc/awslogs/awslogs.conf.bak
2. Create a blank configuration file.
[ec2-user ~]$ sudo touch /etc/awslogs/awslogs.conf
3. Open the /etc/awslogs/awslogs.conf file with a text editor, and copy the example file above into it.
4. Install the jq JSON query utility.
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[ec2-user ~]$ sudo yum install -y jq
5. Query the Amazon ECS introspection API to find the cluster name and set it to an environment
variable.
[ec2-user ~]$ cluster=$(curl -s http://localhost:51678/v1/metadata | jq -r '.
| .Cluster')
6. Replace the {cluster} placeholders in the file with the value of the environment variable you set in
the previous step.
[ec2-user ~]$ sudo sed -i -e "s/{cluster}/$cluster/g" /etc/awslogs/awslogs.conf
7. Query the Amazon ECS introspection API to find the container instance ID and set it to an
environment variable.
[ec2-user ~]$ container_instance_id=$(curl -s http://localhost:51678/v1/metadata | jq -
r '. | .ContainerInstanceArn' | awk -F/ '{print $2}' )
8. Replace the {container_instance_id} placeholders in the file with the value of the environment
variable you set in the previous step.
[ec2-user ~]$ sudo sed -i -e "s/{container_instance_id}/$container_instance_id/g" /etc/
awslogs/awslogs.conf
To configure the CloudWatch Logs agent region
By default, the CloudWatch Logs agent sends data to the us-east-1 region. If you would like to send
your data to a different region, such as the region that your cluster is located in, you can set the region in
the /etc/awslogs/awscli.conf file.
1. Open the /etc/awslogs/awscli.conf file with a text editor.
2. In the [default] section, replace us-east-1 with the region where you want to view log data.
3. Save the file and exit your text editor.
To start the CloudWatch Logs agent
1. Start the CloudWatch Logs agent with the following command.
[ec2-user ~]$ sudo service awslogs start
Output:
Starting awslogs: [ OK ]
2. Use the chkconfig command to ensure that the CloudWatch Logs agent starts at every system boot.
[ec2-user ~]$ sudo chkconfig awslogs on
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Viewing CloudWatch Logs
Viewing CloudWatch Logs
After you have given your container instance role the proper permissions to send logs to CloudWatch
Logs, and you have configured and started the agent, your container instance should be sending its log
data to CloudWatch Logs. You can view and search these logs in the AWS Management Console.
Note
New instance launches may take a few minutes to send data to CloudWatch Logs.
To view your CloudWatch Logs data
1. Open the CloudWatch console at https://console.aws.amazon.com/cloudwatch/.
2. Choose Logs in the left navigation.
3. You should see the log groups you configured in Configuring and Starting the CloudWatch Logs
Agent (p. 53).
4. Choose a log group that you would like to view.
5. Choose a log stream to view. The streams are identified by the cluster name and container instance
ID that sent the logs.
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Configuring CloudWatch Logs at Launch with User Data
Configuring CloudWatch Logs at Launch with User
Data
When you launch an Amazon ECS container instance in Amazon EC2, you have the option of passing
user data to the instance that can be used to perform common automated configuration tasks and even
run scripts after the instance starts. You can pass several types of user data to instances, including shell
scripts, cloud-init directives, and Upstart jobs. You can also pass this data into the launch wizard as
plain text, as a file (this is useful for launching instances via the command line tools), or as base64-
encoded text (for API calls).
The example user data block below performs the following tasks:
• Installs the awslogs package, which contains the CloudWatch Logs agent
• Installs the jq JSON query utility
• Writes the configuration file for the CloudWatch Logs agent and configures the region to send data to
(the region that the container instance is located)
• Gets the cluster name and container instance ID after the Amazon ECS container agent starts and then
writes those values to the CloudWatch Logs agent configuration file log streams
• Starts the CloudWatch Logs agent
• Configures the CloudWatch Logs agent to start at every system boot
Content-Type: multipart/mixed; boundary="==BOUNDARY=="
MIME-Version: 1.0
--==BOUNDARY==
Content-Type: text/x-shellscript; charset="us-ascii"
#!/bin/bash
# Install awslogs and the jq JSON parser
yum install -y awslogs jq
# Inject the CloudWatch Logs configuration file contents
cat > /etc/awslogs/awslogs.conf <<- EOF
[general]
state_file = /var/lib/awslogs/agent-state
[/var/log/dmesg]
file = /var/log/dmesg
log_group_name = /var/log/dmesg
log_stream_name = {cluster}/{container_instance_id}
[/var/log/messages]
file = /var/log/messages
log_group_name = /var/log/messages
log_stream_name = {cluster}/{container_instance_id}
datetime_format = %b %d %H:%M:%S
[/var/log/docker]
file = /var/log/docker
log_group_name = /var/log/docker
log_stream_name = {cluster}/{container_instance_id}
datetime_format = %Y-%m-%dT%H:%M:%S.%f
[/var/log/ecs/ecs-init.log]
file = /var/log/ecs/ecs-init.log.*
log_group_name = /var/log/ecs/ecs-init.log
log_stream_name = {cluster}/{container_instance_id}
datetime_format = %Y-%m-%dT%H:%M:%SZ
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[/var/log/ecs/ecs-agent.log]
file = /var/log/ecs/ecs-agent.log.*
log_group_name = /var/log/ecs/ecs-agent.log
log_stream_name = {cluster}/{container_instance_id}
datetime_format = %Y-%m-%dT%H:%M:%SZ
[/var/log/ecs/audit.log]
file = /var/log/ecs/audit.log.*
log_group_name = /var/log/ecs/audit.log
log_stream_name = {cluster}/{container_instance_id}
datetime_format = %Y-%m-%dT%H:%M:%SZ
EOF
--==BOUNDARY==
Content-Type: text/x-shellscript; charset="us-ascii"
#!/bin/bash
# Set the region to send CloudWatch Logs data to (the region where the container instance
is located)
region=$(curl 169.254.169.254/latest/meta-data/placement/availability-zone | sed s'/.$//')
sed -i -e "s/region = us-east-1/region = $region/g" /etc/awslogs/awscli.conf
--==BOUNDARY==
Content-Type: text/upstart-job; charset="us-ascii"
#upstart-job
description "Configure and start CloudWatch Logs agent on Amazon ECS container instance"
author "Amazon Web Services"
start on started ecs
script
exec 2>>/var/log/ecs/cloudwatch-logs-start.log
set -x
until curl -s http://localhost:51678/v1/metadata
do
sleep 1
done
# Grab the cluster and container instance ARN from instance metadata
cluster=$(curl -s http://localhost:51678/v1/metadata | jq -r '. | .Cluster')
container_instance_id=$(curl -s http://localhost:51678/v1/metadata | jq -r '.
| .ContainerInstanceArn' | awk -F/ '{print $2}' )
# Replace the cluster name and container instance ID placeholders with the actual values
sed -i -e "s/{cluster}/$cluster/g" /etc/awslogs/awslogs.conf
sed -i -e "s/{container_instance_id}/$container_instance_id/g" /etc/awslogs/awslogs.conf
service awslogs start
chkconfig awslogs on
end script
--==BOUNDARY==--
If you have created the ECS-CloudWatchLogs policy and attached it to your ecsInstanceRole as described
in CloudWatch Logs IAM Policy (p. 52), then you can add the above user data block to any container
instances that you launch manually, or you can add it to an Auto Scaling launch configuration, and
your container instances that are launched with this user data will begin sending their log data to
CloudWatch Logs as soon as they launch. For more information, see Launching an Amazon ECS Container
Instance (p. 42).
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Container Instance Draining
Container Instance Draining
There are times when you might need to remove an instance from a cluster; for example, to perform
system updates, update the Docker daemon, or scale down the cluster size. Container instance draining
enables you to remove a container instance from a cluster without impacting tasks in your cluster.
When you set a container instance to DRAINING, Amazon ECS prevents new tasks from being scheduled
for placement on the container instance. If the resources are available, replacement service tasks are
started on other container instances in the cluster. Service tasks on the container instance that are in the
PENDING state are stopped immediately.
Service tasks on the container instance that are in the RUNNING state are stopped and replaced according
to the service's deployment configuration parameters, minimumHealthyPercent and maximumPercent.
• If minimumHealthyPercent is below 100%, the scheduler can ignore desiredCount temporarily during
task replacement. For example, desiredCount is four tasks, a minimum of 50% allows the scheduler to
stop two existing tasks before starting two new tasks. If the minimum is 100%, the service scheduler
can't remove existing tasks until the replacement tasks are considered healthy. If tasks for services that
do not use a load balancer are in the RUNNING state, they are considered healthy. Tasks for services that
use a load balancer are considered healthy if they are in the RUNNING state and the container instance
they are hosted on is reported as healthy by the load balancer.
• The maximumPercent parameter represents an upper limit on the number of running tasks during task
replacement, which enables you to define the replacement batch size. For example, if desiredCount
of four tasks, a maximum of 200% starts four new tasks before stopping the four tasks to be drained
(provided that the cluster resources required to do this are available). If the maximum is 100%, then
replacement tasks can't start until the draining tasks have stopped.
For more information, see Service Definition Parameters (p. 139).
Any PENDING or RUNNING tasks that do not belong to a service are unaffected; you must wait for them to
finish or stop them manually.
A container instance has completed draining when there are no more RUNNING tasks (although the state
remains as DRAINING). You can verify this using the ListTasks operation with the containerInstance
parameter.
When you change the status of a container instance from DRAINING to ACTIVE, the Amazon ECS scheduler
can schedule tasks on the instance again.
Draining Instances
You can use the UpdateContainerInstancesState API action or the update-container-instances-state
command to change the status of a container instance to DRAINING.
The following procedure demonstrates how to set your instance to DRAINING using the AWS Management
Console.
To set your instance to DRAINING using the console
1. Open the Amazon ECS console at https://console.aws.amazon.com/ecs/.
2. In the navigation pane, choose Clusters and select the cluster.
3. Choose ECS Instances and select the check box for the container instances.
4. Choose Actions, Drain instances.
5. After the instances are processed, choose Done.
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Managing Container Instances Remotely
Managing Container Instances Remotely
You can use the Amazon EC2 Run Command feature to securely and remotely manage the configuration
of your Amazon ECS container instances. Run Command provides a simple way of performing common
administrative tasks without having to log on locally to the instance. You can manage configuration
changes across your clusters by simultaneously executing commands on multiple container instances.
Run Command reports the status and results of each command.
Here are some examples of the types of tasks you can perform with Run Command:
• Install or uninstall packages
• Perform security updates
• Clean up Docker images
• Stop or start services
• View system resources
• View log files
• Perform file operations
This topic covers basic installation of Run Command on the Amazon ECS-optimized AMI and a few simple
use cases, but it is by no means exhaustive. For more information about Run Command, see Manage
Amazon EC2 Instances Remotely in the Amazon EC2 User Guide for Linux Instances.
Topics
•Run Command IAM Policy (p. 60)
•Installing the SSM Agent on the Amazon ECS-optimized AMI (p. 61)
•Using Run Command (p. 61)
Run Command IAM Policy
Before you can send commands to your container instances with Run Command, you must attach an IAM
policy that allows access to the Amazon EC2 Systems Manager (SSM) APIs to the ecsInstanceRole. The
procedure below describes how to attach the AmazonEC2RoleforSSM managed policy to your container
instance role so that instances launched with this role can use Run Command.
To attach the AmazonEC2RoleforSSM policy to your ecsInstanceRole
1. Open the IAM console at https://console.aws.amazon.com/iam/.
2. In the navigation pane, choose Roles.
3. Choose ecsInstanceRole. If the role does not exist, follow the procedures in Amazon ECS Container
Instance IAM Role (p. 210) to create the role.
4. Choose the Permissions tab.
5. In the Managed Policies section, choose Attach Policy.
6. For Filter, type AmazonEC2RoleforSSM to narrow the available policies to attach.
7. Select the check box for AmazonEC2RoleforSSM policy and choose Attach Policy.
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Amazon ECS-optimized AMI
Installing the SSM Agent on the Amazon ECS-
optimized AMI
After you have attached the AmazonEC2RoleforSSM policy to your ecsInstanceRole, you can install the
SSM agent on your container instances. The SSM agent processes Run Command requests and configures
the instances that are specified in the request. Use the following procedures to install the SSM agent on
your Amazon ECS-optimized AMI container instances.
To manually install the SSM agent on existing Amazon ECS-optimized AMI container
instances
1. Connect to your container instance. (p. 51)
2. Install the SSM agent RPM. The SSM agent is available in all regions that Amazon ECS is available
in, and each region has its own region-specific download URL; the example command below works
for all regions that Amazon ECS supports, but you can avoid cross-region data transfer costs for the
RPM download by substituting the region of your container instance.
[ec2-user ~]$ sudo yum install -y https://amazon-ssm-us-east-1.s3.amazonaws.com/latest/
linux_amd64/amazon-ssm-agent.rpm
To install the SSM agent on new instance launches with Amazon EC2 user data
• Launch one or more container instances by following the procedure in Launching an Amazon ECS
Container Instance (p. 42), but in Step 10 (p. 44), copy and paste the user data script below
into the User data field. You can also add the commands from this user data script to another
existing script that you may have to perform other tasks, such as setting the cluster name for the
instance to register into.
Note
The user data script below installs the jq JSON parser and uses that to determine the region
of the container instance. Then it downloads and installs the SSM agent.
#!/bin/bash
# Install JQ JSON parser
yum install -y jq
# Get the current region from the instance metadata
region=$(curl -s http://169.254.169.254/latest/dynamic/instance-identity/document | jq
-r .region)
# Install the SSM agent RPM
yum install -y https://amazon-ssm-$region.s3.amazonaws.com/latest/linux_amd64/amazon-
ssm-agent.rpm
Using Run Command
After you have attached the AmazonEC2RoleforSSM policy to your ecsInstanceRole, and installed the
SSM agent on your container instances, you can start using Run Command to send commands to your
container instances. The following topic in the Amazon EC2 User Guide for Linux Instances explains how
to run commands and shell scripts on your instances and view the resulting output:
•Running Shell Scripts with Run Command
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Using Run Command
For more information about Run Command, see Manage Amazon EC2 Instances Remotely in the Amazon
EC2 User Guide for Linux Instances.
Example: To update container instance software with Run Command
One of the most common use cases for Run Command on Amazon ECS container instances is to update
the instance software on your entire fleet of container instances at once, simultaneously.
1. Attach the AmazonEC2RoleforSSM policy to your ecsInstanceRole. (p. 60)
2. Install the SSM agent on your container instances. For more information, see Installing the SSM
Agent on the Amazon ECS-optimized AMI (p. 61).
3. Open the Amazon EC2 console at https://console.aws.amazon.com/ec2/.
4. In the left navigation, choose Commands.
5. Choose Run a command.
6. For Command document, choose AWS-RunShellScript.
7. In the Target instances section, choose Select instances and check the container instances to send
the update command to.
8. In the Commands section, enter the command or commands to send to your container instances. In
this example, the command below updates the instance software, but you can send any command
that you want.
$ yum update -y
9. Choose Run to send the command to the specified instances.
10. (Optional) Choose View result to see the results of your command.
11. (Optional) Choose a command from the list of recent commands to view the command output.
12. (Optional) Choose the Output tab, and then choose View Output. The image below shows a snippet
of the container instance output for the yum update command.
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Note
Unless you configure a command to save the output to an Amazon S3 bucket, then the
command output is truncated at 2500 characters.
Starting a Task at Container Instance Launch Time
Depending on your application architecture design, you may need to run a specific container on every
container instance to deal with operations or security concerns such as monitoring, security, metrics,
service discovery, or logging.
To do this, you can configure your container instances to call the docker run command with the user
data script at launch, or in some init system such as Upstart or systemd. While this method works, it has
some disadvantages because Amazon ECS has no knowledge of the container and cannot monitor the
CPU, memory, ports, or any other resources used. To ensure that Amazon ECS can properly account for
all task resources, create a task definition for the container to run on your container instances. Then, use
Amazon ECS to place the task at launch time with Amazon EC2 user data.
The Amazon EC2 user data script in the following procedure uses the Amazon ECS introspection API to
identify the container instance. Then, it uses the AWS CLI and the start-task command to run a specified
task on itself during startup.
To start a task at container instance launch time
1. If you have not done so already, create a task definition with the container you want to run on your
container instance at launch by following the procedures in Creating a Task Definition (p. 95).
2. Modify your ecsInstanceRole IAM role to add permissions for the StartTask API operation. For
more information, see Amazon ECS Container Instance IAM Role (p. 210).
a. Open the IAM console at https://console.aws.amazon.com/iam/.
b. In the navigation pane, choose Roles.
c. Choose the ecsInstanceRole. If the role does not exist, use the procedure in Amazon ECS
Container Instance IAM Role (p. 210) to create the role and return to this procedure. If the role
does exist, select the role to view the attached policies.
d. In the Inline Policies section, choose Create Role Policy.
e. On the Set Permissions page, choose Custom Policy, Select.
f. For Policy Name, enter StartTask.
g. For Policy Document, copy and paste the following policy and choose Apply Policy.
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
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"Action": [
"ecs:StartTask"
],
"Resource": "*"
}
]
}
3. Launch one or more container instances by following the procedure in Launching an Amazon ECS
Container Instance (p. 42), but in Step 10 (p. 44). Then, copy and paste the MIME multi-part
user data script below into the User data field. Substitute your_cluster_name with the cluster
for the container instance to register into and my_task_def with the task definition to run on the
instance at launch.
Note
The MIME mult-ipart content below uses a shell script to set configuration values and install
packages. It also uses an Upstart job to start the task after the ecs service is running and
the introspection API is available.
Content-Type: multipart/mixed; boundary="==BOUNDARY=="
MIME-Version: 1.0
--==BOUNDARY==
Content-Type: text/text/x-shellscript; charset="us-ascii"
#!/bin/bash
# Specify the cluster that the container instance should register into
cluster=your_cluster_name
# Write the cluster configuration variable to the ecs.config file
# (add any other configuration variables here also)
echo ECS_CLUSTER=$cluster >> /etc/ecs/ecs.config
# Install the AWS CLI and the jq JSON parser
yum install -y aws-cli jq
--==BOUNDARY==
Content-Type: text/text/upstart-job; charset="us-ascii"
#upstart-job
description "Amazon EC2 Container Service (start task on instance boot)"
author "Amazon Web Services"
start on started ecs
script
exec 2>>/var/log/ecs/ecs-start-task.log
set -x
until curl -s http://localhost:51678/v1/metadata
do
sleep 1
done
# Grab the container instance ARN and AWS region from instance metadata
instance_arn=$(curl -s http://localhost:51678/v1/metadata | jq -r '.
| .ContainerInstanceArn' | awk -F/ '{print $NF}' )
cluster=$(curl -s http://localhost:51678/v1/metadata | jq -r '. | .Cluster' | awk -F/
'{print $NF}' )
region=$(curl -s http://localhost:51678/v1/metadata | jq -r '.
| .ContainerInstanceArn' | awk -F: '{print $4}')
# Specify the task definition to run at launch
task_definition=my_task_def
# Run the AWS CLI start-task command to start your task on this container instance
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aws ecs start-task --cluster $cluster --task-definition $task_definition --container-
instances $instance_arn --started-by $instance_arn --region $region
end script
--==BOUNDARY==--
4. Verify that your container instances launch into the correct cluster and that your tasks have started.
a. Open the Amazon ECS console at https://console.aws.amazon.com/ecs/.
b. From the navigation bar, choose the region that your cluster is in.
c. In the navigation pane, choose Clusters and select the cluster that hosts your container
instances.
d. On the Cluster page, choose Tasks.
Each container instance you launched should have your task running on it, and the container
instance ARN should be in the Started By column.
If you do not see your tasks, you can log in to your container instances with SSH and check the /
var/log/ecs/ecs-start-task.log file for debugging information.
Deregister a Container Instance
When you are finished with a container instance, you can deregister it from your cluster.
Following deregistration, the container instance is no longer able to accept new tasks. If you have tasks
running on the container instance when you deregister it, these tasks remain running until you terminate
the instance or the tasks stop through some other means. However, these tasks are orphaned (no longer
monitored or accounted for by Amazon ECS). If an orphaned task on your container instance is part of an
Amazon ECS service, then the service scheduler starts another copy of that task, on a different container
instance, if possible. Any containers in orphaned service tasks that are registered with a Classic Load
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Balancer or an Application Load Balancer target group are deregistered. They begin connection draining
according to the settings on the load balancer or target group.
If you intend to use the container instance for some other purpose after deregistration, you should stop
all of the tasks running on the container instance before deregistration. This stops any orphaned tasks
from consuming resources.
Important
Because each container instance has unique state information, they should not be deregistered
from one cluster and re-registered into another. To relocate container instance resources, we
recommend that you terminate container instances from one cluster and launch new container
instances with the latest Amazon ECS-optimized AMI in the new cluster. For more information,
see Terminate Your Instance in the Amazon EC2 User Guide for Linux Instances and Launching an
Amazon ECS Container Instance (p. 42).
Deregistering a container instance removes the instance from a cluster, but it does not terminate the
EC2 instance. If you are finished using the instance, be sure to terminate it in the Amazon EC2 console to
stop billing. For more information, see Terminate Your Instance in the Amazon EC2 User Guide for Linux
Instances.
Note
If you terminate a running container instance with a connected Amazon ECS container agent,
the agent automatically deregisters the instance from your cluster. Stopped container instances
or instances with disconnected agents are not automatically deregistered when terminated.
To deregister a container instance
1. Open the Amazon ECS console at https://console.aws.amazon.com/ecs/.
2. From the navigation bar, choose the region that your container instance is registered in.
3. In the navigation pane, choose Clusters and select the cluster that hosts your container instance.
4. On the Cluster : name page, choose ECS Instances.
5. Choose the container instance ID that to deregister.
6. On the Container Instance : id page, choose Deregister.
7. Review the deregistration message, and choose Yes, Deregister.
8. If you are finished with the container instance, terminate the underlying Amazon EC2 instance. For
more information, see Terminate Your Instance in the Amazon EC2 User Guide for Linux Instances.
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Note
If your instance is maintained by an Auto Scaling group or AWS CloudFormation stack,
terminate the instance by updating the Auto Scaling group or AWS CloudFormation stack.
Otherwise, the Auto Scaling group re-creates the instance after you terminate it.
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Amazon ECS Container Agent
The Amazon ECS container agent allows container instances to connect to your cluster. The Amazon
ECS container agent is included in the Amazon ECS-optimized AMI, but you can also install it on any EC2
instance that supports the Amazon ECS specification. The Amazon ECS container agent is only supported
on EC2 instances.
Note
The source code for the Amazon ECS container agent is available on GitHub. We encourage you
to submit pull requests for changes that you would like to have included. However, Amazon Web
Services does not currently provide support for running modified copies of this software.
Topics
•Installing the Amazon ECS Container Agent (p. 68)
•Amazon ECS Container Agent Versions (p. 71)
•Updating the Amazon ECS Container Agent (p. 73)
•Amazon ECS Container Agent Configuration (p. 79)
•Automated Task and Image Cleanup (p. 85)
•Private Registry Authentication (p. 86)
•Amazon ECS Container Agent Introspection (p. 90)
•HTTP Proxy Configuration (p. 91)
Installing the Amazon ECS Container Agent
If your container instance was not launched from an AMI that includes the Amazon ECS container agent,
you can install it using the following procedure.
Note
The Amazon ECS container agent is included in the Amazon ECS-optimized AMI and does not
require installation.
To install the Amazon ECS container agent on an Amazon Linux EC2 instance
1. Launch an Amazon Linux instance with an IAM role that allows access to Amazon ECS. For more
information, see Amazon ECS Container Instance IAM Role (p. 210).
2. Connect to your instance.
3. Install the ecs-init package. For more information about ecs-init, see the source code on GitHub.
[ec2-user ~]$ sudo yum install -y ecs-init
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4. Start the Docker daemon.
[ec2-user ~]$ sudo service docker start
Output:
Starting cgconfig service: [ OK ]
Starting docker: [ OK ]
5. Start the ecs-init upstart job.
[ec2-user ~]$ sudo start ecs
Output:
ecs start/running, process 2804
6. (Optional) You can verify that the agent is running and see some information about your new
container instance with the agent introspection API. For more information, see the section called
“Amazon ECS Container Agent Introspection” (p. 90).
[ec2-user ~]$ curl http://localhost:51678/v1/metadata
Output:
{
"Cluster": "default",
"ContainerInstanceArn": "<container_instance_ARN>",
"Version": "Amazon ECS Agent - v1.14.1 (467c3d7)"
}
To install the Amazon ECS container agent on a non-Amazon Linux EC2 instance
1. Launch an EC2 instance with an IAM role that allows access to Amazon ECS. For more information,
see Amazon ECS Container Instance IAM Role (p. 210).
2. Connect to your instance.
3. Install Docker on your instance. Amazon ECS requires a minimum Docker version of 1.5.0 (version
1.12.6 is recommended), and the default Docker versions in many system package managers, such
as yum or apt-get do not meet this minimum requirement. For information about installing the
latest Docker version on your particular Linux distribution, see https://docs.docker.com/engine/
installation/.
Note
The Amazon Linux AMI always includes the recommended version of Docker for use with
Amazon ECS. You can install Docker on Amazon Linux with the sudo yum install docker -y
command.
4. Check your Docker version to verify that your system meets the minimum version requirement.
ubuntu:~$ sudo docker version
Output:
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Client API version: 1.16
Go version (client): go1.3.3
Git commit (client): 5bc2ff8
OS/Arch (client): linux/amd64
Server version: 1.4.1
Server API version: 1.16
Go version (server): go1.3.3
Git commit (server): 5bc2ff8
In this example, the Docker version is 1.4.1, which is below the minimum version of 1.5.0. This
instance needs to upgrade its Docker version before proceeding. For information about installing the
latest Docker version on your particular Linux distribution, go to https://docs.docker.com/engine/
installation/.
5. Run the following commands on your container instance to allow the port proxy to route traffic
using loopback addresses.
ubuntu:~$ sudo sh -c "echo 'net.ipv4.conf.all.route_localnet = 1' >> /etc/sysctl.conf"
ubuntu:~$ sudo sysctl -p /etc/sysctl.conf
6. Run the following commands on your container instance to enable IAM roles for tasks. For more
information, see IAM Roles for Tasks (p. 216).
ubuntu:~$ iptables -t nat -A PREROUTING -p tcp -d 169.254.170.2 --dport 80 -j DNAT --
to-destination 127.0.0.1:51679
ubuntu:~$ iptables -t nat -A OUTPUT -d 169.254.170.2 -p tcp -m tcp --dport 80 -j
REDIRECT --to-ports 51679
7. Write the new iptables configuration to your operating system-specific location.
• For Debian/Ubuntu:
sudo sh -c 'iptables-save > /etc/iptables/rules.v4'
• For CentOS/RHEL:
sudo sh -c 'iptables-save > /etc/sysconfig/iptables'
8. Create the /etc/ecs directory and create the Amazon ECS container agent configuration file.
ubuntu:~$ sudo mkdir -p /etc/ecs && sudo touch /etc/ecs/ecs.config
9. Edit the /etc/ecs/ecs.config file and add the following contents. If you do not want your container
instance to register with the default cluster, specify your cluster name as the value for ECS_CLUSTER.
ECS_DATADIR=/data
ECS_ENABLE_TASK_IAM_ROLE=true
ECS_ENABLE_TASK_IAM_ROLE_NETWORK_HOST=true
ECS_LOGFILE=/log/ecs-agent.log
ECS_AVAILABLE_LOGGING_DRIVERS=["json-file","awslogs"]
ECS_LOGLEVEL=info
ECS_CLUSTER=default
For more information about these and other agent runtime options, see Amazon ECS Container
Agent Configuration (p. 79).
Note
You can optionally store your agent environment variables in Amazon S3 (which can be
downloaded to your container instances at launch time using Amazon EC2 user data). This
is recommended for sensitive information such as authentication credentials for private
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repositories. For more information, see Storing Container Instance Configuration in Amazon
S3 (p. 84) and Private Registry Authentication (p. 86).
10. Pull and run the latest Amazon ECS container agent on your container instance.
Note
You should use Docker restart policies or a process manager (such as upstart or systemd) to
treat the container agent as a service or a daemon and ensure that it is restarted if it exits.
For more information, see Automatically start containers and Restart policies in the Docker
documentation. The Amazon ECS-optimized AMI uses the ecs-init RPM for this purpose,
and you can view the source code for this RPM on GitHub. For example systemd unit files
for Ubuntu 16.04 and CentOS 7, see Example Container Instance User Data Configuration
Scripts (p. 48).
The following example agent run command is broken into separate lines to show each option. For
more information about these and other agent runtime options, see Amazon ECS Container Agent
Configuration (p. 79).
Important
Operating systems with SELinux enabled require the --privileged option in your docker
run command. In addition, for SELinux-enabled container instances, we recommend that
you add the :Z option to the /log and /data volume mounts. However, the host mounts
for these volumes must exist before you run the command or you will receive a no such
file or directory error. Take the following action if you experience difficulty running the
Amazon ECS agent on an SELinux-enabled container instance:
• Create the host volume mount points on your container instance.
ubuntu:~$ sudo mkdir -p /var/log/ecs /var/lib/ecs/data
• Add the --privileged option to the docker run command below.
• Append the :Z option to the /log and /data container volume mounts (for example, --
volume=/var/log/ecs/:/log:Z) to the docker run command below.
ubuntu:~$ sudo docker run --name ecs-agent \
--detach=true \
--restart=on-failure:10 \
--volume=/var/run:/var/run \
--volume=/var/log/ecs/:/log \
--volume=/var/lib/ecs/data:/data \
--volume=/etc/ecs:/etc/ecs \
--net=host \
--env-file=/etc/ecs/ecs.config \
amazon/amazon-ecs-agent:latest
Note
If you receive an Error response from daemon: Cannot start container message, you
can delete the failed container with the sudo docker rm ecs-agent command and try
running the agent again.
Amazon ECS Container Agent Versions
Each Amazon ECS container agent version supports a different feature set and provides bug fixes from
previous versions. When possible, we always recommend using the latest version of the Amazon ECS
container agent. To update your container agent to the latest version, see Updating the Amazon ECS
Container Agent (p. 73).
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Launching your container instances from the most recent Amazon ECS-optimized AMI ensures that you
receive the current container agent version. To launch a container instance with the latest Amazon ECS-
optimized AMI, see Launching an Amazon ECS Container Instance (p. 42).
To install the latest version of the Amazon ECS container agent on another operating system, see
Installing the Amazon ECS Container Agent (p. 68). The table in Amazon ECS-Optimized AMI
Container Agent Versions (p. 72) shows the Docker version that is tested on Amazon Linux for each
agent version.
To see which features and enhancements are included with each agent release, see https://github.com/
aws/amazon-ecs-agent/releases.
Amazon ECS-Optimized AMI Container Agent
Versions
The Amazon ECS-optimized AMI comes prepackaged with the Amazon ECS container agent, Docker, and
the ecs-init service that controls the starting and stopping of the agent at boot and shutdown. The
following table lists the container agent version, the ecs-init version, and the Docker version that is
tested and packaged with each Amazon ECS-optimized AMI.
Note
As new Amazon ECS-optimized AMIs and Amazon ECS agent versions are released, older
versions are still available for launch in Amazon EC2. However, we encourage you to update
to the latest version (p. 73) of the Amazon ECS agent and to keep your container instance
software up to date. If you request support for an older version of the Amazon ECS agent
through AWS Support, you may be asked to move to the latest version as a part of the support
process.
Amazon ECS-
optimized AMI
Amazon ECS container
agent version
Docker version ecs-init version
2016.09.g 1.14.1 1.12.6 1.14.1-1
2016.09.f 1.14.0 1.12.6 1.14.0-2
2016.09.e 1.14.0 1.12.6 1.14.0-1
2016.09.d 1.13.1 1.12.6 1.13.1-2
2016.09.c 1.13.1 1.11.2 1.13.1-1
2016.09.b 1.13.1 1.11.2 1.13.1-1
2016.09.a 1.13.0 1.11.2 1.13.0-1
2016.03.j 1.13.0 1.11.2 1.13.0-1
2016.03.i 1.12.2 1.11.2 1.12.2-1
2016.03.h 1.12.1 1.11.2 1.12.1-1
2016.03.g 1.12.0 1.11.2 1.12.0-1
2016.03.f 1.11.1 1.11.2 1.11.1-1
2016.03.e 1.11.0 1.11.2 1.11.0-1
2016.03.d 1.10.0 1.11.1 1.10.0-1
2016.03.c 1.10.0 1.11.1 1.10.0-1
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Amazon ECS-
optimized AMI
Amazon ECS container
agent version
Docker version ecs-init version
2016.03.b 1.9.0 1.9.1 1.9.0-1
2016.03.a 1.8.2 1.9.1 1.8.2-1
2015.09.g 1.8.1 1.9.1 1.8.1-1
2015.09.f 1.8.0 1.9.1 1.8.0-1
2015.09.e 1.7.1 1.9.1 1.7.1-1
2015.09.d 1.7.1 1.9.1 1.7.1-1
2015.09.c 1.7.0 1.7.1 1.7.0-1
2015.09.b 1.6.0 1.7.1 1.6.0-1
2015.09.a 1.5.0 1.7.1 1.5.0-1
2015.03.g 1.4.0 1.7.1 1.4.0-2
2015.03.f 1.4.0 1.6.2 1.4.0-1
2015.03.e 1.3.1 1.6.2 1.3.1-1
2015.03.d 1.2.1 1.6.2 1.2.0-2
2015.03.c 1.2.0 1.6.2 1.2.0-1
2015.03.b 1.1.0 1.6.0 1.0-3
2015.03.a 1.0.0 1.5.0 1.0-1
For more information about the Amazon ECS-optimized AMI, including AMI IDs for the latest version in
each region, see Amazon ECS-Optimized AMI (p. 34).
Updating the Amazon ECS Container Agent
Occasionally, you may need to update the Amazon ECS container agent to pick up bug fixes and new
features. Updating the Amazon ECS container agent does not interrupt running tasks or services on the
container instance. The process for updating the agent differs depending on whether your container
instance was launched with the Amazon ECS-optimized AMI or another operating system.
Topics
•Checking Your Amazon ECS Container Agent Version (p. 73)
•Updating the Amazon ECS Container Agent on the Amazon ECS-Optimized AMI (p. 75)
•Manually Updating the Amazon ECS Container Agent (for Non-Amazon ECS-optimized
AMIs) (p. 77)
Checking Your Amazon ECS Container Agent Version
You can check the version of the container agent that is running on your container instances to see if you
need to update it. The container instance view in the Amazon ECS console provides the agent version.
Use the following procedure to check your agent version.
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To check if your Amazon ECS container agent is running the latest version in the console
1. Open the Amazon ECS console at https://console.aws.amazon.com/ecs/.
2. On the Clusters page, select the cluster that hosts the container instance or instances to check.
3. On the Cluster : cluster_name page, choose ECS Instances.
4. Note the Agent version column for your container instances. If you are using an outdated agent
version on any of your container instances, the console alerts you with a message and flags the
outdated agent version.
If your agent version is 1.14.1, you are running the latest container agent. If your agent version is
below 1.14.1, you can update your container agent with the following procedures:
• If your container instance is running the Amazon ECS-optimized AMI, see Updating the Amazon
ECS Container Agent on the Amazon ECS-Optimized AMI (p. 75).
• If your container instance is not running the Amazon ECS-optimized AMI, see Manually Updating
the Amazon ECS Container Agent (for Non-Amazon ECS-optimized AMIs) (p. 77).
Important
To update the Amazon ECS agent version from versions prior to v1.0.0 on your Amazon
ECS-optimized AMI, we recommend that you terminate your current container instance
and launch a new instance with the most recent AMI version. Any container instances that
use a preview version should be retired and replaced with the most recent AMI. For more
information, see Launching an Amazon ECS Container Instance (p. 42).
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Agent on the Amazon ECS-Optimized AMI
You can also use the Amazon ECS container agent introspection API to check the agent version
from the container instance itself. For more information, see Amazon ECS Container Agent
Introspection (p. 90).
To check if your Amazon ECS container agent is running the latest version with the
introspection API
1. Log in to your container instance via SSH.
2. Query the introspection API.
[ec2-user ~]$ curl -s 127.0.0.1:51678/v1/metadata | python -mjson.tool
Output:
{
"Cluster": "default",
"ContainerInstanceArn": "arn:aws:ecs:us-west-2:<aws_account_id>:container-
instance/4d3910c1-27c8-410c-b1df-f5d06fab4305",
"Version": "Amazon ECS Agent - v1.14.1 (467c3d7)"
}
Note
The introspection API added Version information in the version v1.0.0 of the Amazon
ECS container agent. If Version is not present when querying the introspection API, or the
introspection API is not present in your agent at all, then the version you are running is
v0.0.3 or earlier. You should update your version.
Updating the Amazon ECS Container Agent on the
Amazon ECS-Optimized AMI
If you are using the Amazon ECS-optimized AMI, you have several options to get the latest version of the
Amazon ECS container agent (shown in order of recommendation):
• Terminate your current container instances and launch the latest version of the Amazon ECS-optimized
AMI (either manually or by updating your Auto Scaling launch configuration with the latest AMI). This
provides a fresh container instance with the most current tested and validated versions of Amazon
Linux, Docker, ecs-init, and the Amazon ECS container agent. For more information, see Amazon ECS-
Optimized AMI (p. 34).
• Connect to the instance with SSH and update the ecs-init package (and its dependencies) to the
latest version. This operation provides the most current tested and validated versions of Docker and
ecs-init that are available in the Amazon Linux repositories and the latest version of the Amazon
ECS container agent. For more information, see To update the ecs-init package on the Amazon ECS-
optimized AMI (p. 75).
• Update the container agent with the UpdateContainerAgent API operation, either through the console
or with the AWS CLI or AWS SDKs. For more information, see Updating the Amazon ECS Container
Agent with the UpdateContainerAgent API Operation (p. 76).
To update the ecs-init package on the Amazon ECS-optimized AMI
1. Log in to your container instance via SSH. For more information, see Connect to Your Container
Instance (p. 51).
2. Update the ecs-init package with the following command.
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[ec2-user ~]$ sudo yum update -y ecs-init
Note
The ecs-init package and the Amazon ECS container agent are updated immediately.
However, newer versions of Docker are not loaded until the Docker daemon is restarted,
either by rebooting the instance, or by running sudo service docker restart to restart
Docker and then sudo start ecs to restart the container agent.
Updating the Amazon ECS Container Agent with the
UpdateContainerAgent API Operation
Important
This update process is only supported on the Amazon ECS-optimized AMI. For container
instances that are running other operating systems, see Manually Updating the Amazon ECS
Container Agent (for Non-Amazon ECS-optimized AMIs) (p. 77).
To update the Amazon ECS agent version from versions prior to v1.0.0 on your Amazon ECS-
optimized AMI, we recommend that you terminate your current container instance and launch
a new instance with the most recent AMI version. Any container instances that use a preview
version should be retired and replaced with the most recent AMI. For more information, see
Launching an Amazon ECS Container Instance (p. 42).
The update process begins when you request an agent update, either through the console or with the
AWS CLI or AWS SDKs. Amazon ECS checks your current agent version against the latest available agent
version, and if an update is possible, the update process progresses as shown in the flow chart below. If
an update is not available, for example, if the agent is already running the most recent version, then a
NoUpdateAvailableException is returned.
The stages in the update process shown above are as follows:
PENDING
An agent update is available, and the update process has started.
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Manually Updating the Amazon ECS Container
Agent (for Non-Amazon ECS-optimized AMIs)
STAGING
The agent has begun downloading the agent update. If the agent cannot download the update, or
if the contents of the update are incorrect or corrupted, then the agent sends a notification of the
failure and the update transitions to the FAILED state.
STAGED
The agent download has completed and the agent contents have been verified.
UPDATING
The ecs-init service is restarted and it picks up the new agent version. If the agent is for some
reason unable to restart, the update transitions to the FAILED state; otherwise, the agent signals
Amazon ECS that the update is complete.
To update the Amazon ECS container agent on the Amazon ECS-optimized AMI in the console
1. Open the Amazon ECS console at https://console.aws.amazon.com/ecs/.
2. On the Clusters page, select the cluster that hosts the container instance or instances to check.
3. On the Cluster : cluster_name page, choose ECS Instances.
4. Select the container instance to update.
5. On the Container Instance page, choose Update agent.
To update the Amazon ECS container agent on the Amazon ECS-optimized AMI with the AWS
CLI
• Use the following command to update the Amazon ECS container agent on your container instance:
aws ecs update-container-agent --cluster cluster_name --container-
instance container_instance_id
Manually Updating the Amazon ECS Container Agent
(for Non-Amazon ECS-optimized AMIs)
To manually update the Amazon ECS container agent (for non-Amazon ECS-optimized AMIs)
1. Log in to your container instance via SSH.
2. Check to see if your agent uses the ECS_DATADIR environment variable to save its state.
ubuntu:~$ docker inspect ecs-agent | grep ECS_DATADIR
Output:
"ECS_DATADIR=/data",
Important
If the previous command does not return the ECS_DATADIR environment variable, you must
stop any tasks running on this container instance before updating your agent. Newer agents
with the ECS_DATADIR environment variable save their state and you can update them while
tasks are running without issues.
3. Stop the Amazon ECS container agent.
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ubuntu:~$ docker stop ecs-agent
4. Delete the agent container.
ubuntu:~$ docker rm ecs-agent
5. Ensure that the /etc/ecs directory and Amazon ECS container agent configuration file exist at /etc/
ecs/ecs.config.
ubuntu:~$ sudo mkdir -p /etc/ecs && sudo touch /etc/ecs/ecs.config
6. Edit the /etc/ecs/ecs.config file and ensure that it contains at least the following variable
declarations. If you do not want your container instance to register with the default cluster, specify
your cluster name as the value for ECS_CLUSTER.
ECS_DATADIR=/data
ECS_ENABLE_TASK_IAM_ROLE=true
ECS_ENABLE_TASK_IAM_ROLE_NETWORK_HOST=true
ECS_LOGFILE=/log/ecs-agent.log
ECS_AVAILABLE_LOGGING_DRIVERS=["json-file","awslogs"]
ECS_LOGLEVEL=info
ECS_CLUSTER=default
For more information about these and other agent runtime options, see Amazon ECS Container
Agent Configuration (p. 79).
Note
You can optionally store your agent environment variables in Amazon S3 (which can be
downloaded to your container instances at launch time using Amazon EC2 user data). This
is recommended for sensitive information such as authentication credentials for private
repositories. For more information, see Storing Container Instance Configuration in Amazon
S3 (p. 84) and Private Registry Authentication (p. 86).
7. Pull the latest Amazon ECS container agent image from Docker Hub.
ubuntu:~$ docker pull amazon/amazon-ecs-agent:latest
Output:
Pulling repository amazon/amazon-ecs-agent
a5a56a5e13dc: Download complete
511136ea3c5a: Download complete
9950b5d678a1: Download complete
c48ddcf21b63: Download complete
Status: Image is up to date for amazon/amazon-ecs-agent:latest
8. Run the latest Amazon ECS container agent on your container instance.
Note
You should use Docker restart policies or a process manager (such as upstart or systemd) to
treat the container agent as a service or a daemon and ensure that it is restarted if it exits.
For more information, see Automatically start containers and Restart policies in the Docker
documentation. The Amazon ECS-optimized AMI uses the ecs-init RPM for this purpose,
and you can view the source code for this RPM on GitHub. For example systemd unit files
for Ubuntu 16.04 and CentOS 7, see Example Container Instance User Data Configuration
Scripts (p. 48).
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Amazon ECS Container Agent Configuration
The following example agent run command is broken into separate lines to show each option. For
more information about these and other agent runtime options, see Amazon ECS Container Agent
Configuration (p. 79).
Important
Operating systems with SELinux enabled require the --privileged option in your docker
run command. In addition, for SELinux-enabled container instances, we recommend that
you add the :Z option to the /log and /data volume mounts. However, the host mounts
for these volumes must exist before you run the command or you will receive a no such
file or directory error. Take the following action if you experience difficulty running the
Amazon ECS agent on an SELinux-enabled container instance:
• Create the host volume mount points on your container instance.
ubuntu:~$ sudo mkdir -p /var/log/ecs /var/lib/ecs/data
• Add the --privileged option to the docker run command below.
• Append the :Z option to the /log and /data container volume mounts (for example, --
volume=/var/log/ecs/:/log:Z) to the docker run command below.
ubuntu:~$ sudo docker run --name ecs-agent \
--detach=true \
--restart=on-failure:10 \
--volume=/var/run:/var/run \
--volume=/var/log/ecs/:/log \
--volume=/var/lib/ecs/data:/data \
--volume=/etc/ecs:/etc/ecs \
--net=host \
--env-file=/etc/ecs/ecs.config \
amazon/amazon-ecs-agent:latest
Note
If you receive an Error response from daemon: Cannot start container message, you
can delete the failed container with the sudo docker rm ecs-agent command and try
running the agent again.
Amazon ECS Container Agent Configuration
The Amazon ECS container agent supports a number of configuration options, most of which should be
set through environment variables. The following environment variables are available, and all of them
are optional.
If your container instance was launched with the Amazon ECS-optimized AMI, you can set these
environment variables in the /etc/ecs/ecs.config file and then restart the agent. You can also write
these configuration variables to your container instances with Amazon EC2 user data at launch time. For
more information, see Bootstrapping Container Instances with Amazon EC2 User Data (p. 45).
If you are manually starting the Amazon ECS container agent (for non-Amazon ECS-optimized AMIs),
you can use these environment variables in the docker run command that you use to start the agent
with the syntax --env=VARIABLE_NAME=VARIABLE_VALUE. For sensitive information, such as authentication
credentials for private repositories, you should store your agent environment variables in a file and pass
them all at one time with the --env-file path_to_env_file option.
Topics
•Available Parameters (p. 80)
•Storing Container Instance Configuration in Amazon S3 (p. 84)
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Available Parameters
Available Parameters
Environment
Key
Example Values Description Default
Value
ECS_CLUSTER MyCluster The cluster that this agent should
check into.
default
ECS_RESERVED_PORTS[22, 80, 5000, 8080] An array of ports that should
be marked as unavailable for
scheduling on this container
instance.
[22, 2375,
2376,
51678]
ECS_RESERVED_PORTS_UDP[53, 123] An array of UDP ports that should
be marked as unavailable for
scheduling on this container
instance.
[]
ECS_ENGINE_AUTH_TYPEdockercfg | docker Required for private registry
authentication. This is the
type of authentication data in
ECS_ENGINE_AUTH_DATA. For more
information, see Authentication
Formats (p. 87).
Null
ECS_ENGINE_AUTH_DATAExample
(ECS_ENGINE_AUTH_TYPE=dockercfg):
{"https://index.docker.io/v1/":
{"auth":"zq212MzEXAMPLE7o6T25Dk0i","email":"email@example.com"}}
Example
(ECS_ENGINE_AUTH_TYPE=docker):
{"https://index.docker.io/v1/":
{"username":"my_name","password":"my_password","email":"email@example.com"}}
Required for private
registry authentication. If
ECS_ENGINE_AUTH_TYPE=dockercfg,
then the ECS_ENGINE_AUTH_DATA
value should be the contents
of a Docker configuration file
(~/.dockercfg or ~/.docker/
config.json) created by
running docker login. If
ECS_ENGINE_AUTH_TYPE=docker,
then the ECS_ENGINE_AUTH_DATA
value should be a JSON
representation of the registry
server to authenticate against,
as well as the authentication
parameters required by that
registry (such as user name,
password, and email address
for that account). For more
information, see Authentication
Formats (p. 87).
Null
AWS_DEFAULT_REGIONus-east-1 The region to be used in API
requests as well as to infer the
correct back-end host.
Taken
from EC2
instance
metadata.
AWS_ACCESS_KEY_IDAKIAIOSFODNN7EXAMPLE The access key used by the agent
for all calls.
Taken
from EC2
instance
metadata.
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Available Parameters
Environment
Key
Example Values Description Default
Value
AWS_SECRET_ACCESS_KEYwJalrXUtnFEMI/K7MDENG/
bPxRfiCYEXAMPLEKEY
The secret key used by the agent
for all calls.
Taken
from EC2
instance
metadata.
DOCKER_HOST unix:///var/run/docker.sock Used to create a connection to the
Docker daemon; behaves similarly
to the environment variable as used
by the Docker client.
unix:///
var/run/
docker.sock
ECS_LOGLEVEL crit | error | warn | info |
debug
The level to log at on stdout.info
ECS_LOGFILE /ecs-agent.log The path to output full debugging
information to. If blank, no logs are
recorded. If this value is set, logs
at the debug level (regardless of
ECS_LOGLEVEL) are written to that
file.
Null
ECS_CHECKPOINTtrue | false Whether or not to save the
checkpoint state to the location
specified with ECS_DATADIR.
If
ECS_DATADIR
is explicitly
set to a
non-empty
value, then
ECS_CHECKPOINT
is set to
true;
otherwise,
it is set to
false.
ECS_DATADIR /data The name of the persistent data
directory on the container that is
running the Amazon ECS container
agent. The directory is used to save
information about the cluster and
the agent state.
Null
ECS_UPDATES_ENABLEDtrue | false Whether to exit for ECS agent
updates when they are requested.
false
ECS_UPDATE_DOWNLOAD_DIR/cache The filesystem location to place
update tarballs within the container
when they are downloaded.
ECS_DISABLE_METRICStrue | false Whether to disable CloudWatch
metrics for Amazon ECS. If this
value is set to true, CloudWatch
metrics are not collected.
false
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Available Parameters
Environment
Key
Example Values Description Default
Value
ECS_DOCKER_GRAPHPATH/var/lib/docker Used to create the path to the state
file of launched containers. The
state file is used to read utilization
metrics of containers.
/var/lib/
docker
AWS_SESSION_TOKEN The session token used for
temporary credentials.
Taken
from EC2
instance
metadata.
ECS_RESERVED_MEMORY32 The amount of memory, in MiB, to
reserve for processes that are not
managed by ECS.
0
ECS_AVAILABLE_LOGGING_DRIVERS["json-file","awslogs"]
For information about how to use
the awslogs log driver, see Using
the awslogs Log Driver (p. 117).
For more information about the
different log drivers available for
your Docker version and how to
configure them, see Configure
logging drivers in the Docker
documentation.
The logging drivers available
on the container instance. The
Amazon ECS container agent
running on a container instance
must register the logging drivers
available on that instance with the
ECS_AVAILABLE_LOGGING_DRIVERS
environment variable before
containers placed on that instance
can use log configuration options
for those drivers in tasks.
["json-
file","awslogs"]
ECS_DISABLE_PRIVILEGEDtrue | false Whether launching privileged
containers is disabled on the
container instance. If this value is
set to true, privileged containers
are not permitted.
false
ECS_SELINUX_CAPABLEtrue | false Whether SELinux is available on the
container instance.
false
ECS_APPARMOR_CAPABLEtrue | false Whether AppArmor is available on
the container instance.
false
ECS_ENGINE_TASK_CLEANUP_WAIT_DURATION1h (Valid time units are "ns", "us" (or
"µs"), "ms", "s", "m", and "h".)
Time duration to wait from when
a task is stopped until the docker
container is removed. As this
removes the docker container data,
be aware that if this value is set too
low, you may not be able to inspect
your stopped containers or view the
logs before they are removed. The
minimum duration is 1m; any value
shorter than 1 minute is ignored.
3h
ECS_CONTAINER_STOP_TIMEOUT10m (Valid time units are "ns",
"us" (or "µs"), "ms", "s", "m", and "h".)
Time duration to wait from when a
task is stopped before its containers
are forcefully killed if they do not
exit normally on their own.
30s
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Available Parameters
Environment
Key
Example Values Description Default
Value
HTTP_PROXY 10.0.0.131:3128 The hostname (or IP address) and
port number of an HTTP proxy to
use for the ECS agent to connect to
the Internet (for example, if your
container instances do not have
external network access through
an Amazon VPC Internet gateway
or NAT gateway or instance). If
this variable is set, you must also
set the NO_PROXY variable to filter
EC2 instance metadata and Docker
daemon traffic from the proxy. For
more information, see HTTP Proxy
Configuration (p. 91).
Null
NO_PROXY 169.254.169.254,/var/run/
docker.sock
The HTTP traffic that should not
be forwarded to the specified
HTTP_PROXY. You must specify
169.254.169.254,/var/run/
docker.sock to filter EC2 instance
metadata and Docker daemon
traffic from the proxy. For more
information, see HTTP Proxy
Configuration (p. 91).
Null
ECS_ENABLE_TASK_IAM_ROLEtrue | false Whether IAM roles for tasks should
be enabled on the container
instance for task containers with
the bridge or default network
modes. For more information, see
IAM Roles for Tasks (p. 216).
false
ECS_ENABLE_TASK_IAM_ROLE_NETWORK_HOSTtrue | false Whether IAM roles for tasks should
be enabled on the container
instance for task containers with
the host network mode. This
variable is only supported on agent
versions 1.12.0 and later. For more
information, see IAM Roles for
Tasks (p. 216).
false
ECS_DISABLE_IMAGE_CLEANUPtrue Whether to disable automated
image cleanup for the Amazon
ECS agent. For more information,
see Automated Task and Image
Cleanup (p. 85).
false
ECS_IMAGE_CLEANUP_INTERVAL30m The time interval between
automated image cleanup cycles.
If set to less than 10 minutes, the
value is ignored.
30m
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Storing Container Instance Configuration in Amazon S3
Environment
Key
Example Values Description Default
Value
ECS_IMAGE_MINIMUM_CLEANUP_AGE30m The minimum time interval
between when an image is pulled
and when it can be considered for
automated image cleanup.
1h
ECS_NUM_IMAGES_DELETE_PER_CYCLE5 The maximum number of images to
delete in a single automated image
cleanup cycle. If set to less than 1,
the value is ignored.
5
ECS_INSTANCE_ATTRIBUTES{"custom attribute":
"custom_attribute_value"}
For information about
custom attributes to use, see
Attributes (p. 131).
A list of custom attributes, in JSON
form, to apply to your container
instances. Using this attribute at
instance registration will add the
custom attributes allowing you to
skip the manual method of adding
custom attributes via the AWS
Management Console.
An invalid JSON value for this
variable will cause the agent to exit
with a code of 5 and a message
will appear in the agent logs. If
the JSON value is valid but there is
an issue detected when validating
the attribute (for example if the
value is too long or contains invalid
characters) then the container
instance registration will happen
but the agent will exit with a code
5 and a message will be written
to the agent logs. For information
on how to locate the agent logs,
see Amazon ECS Container Agent
Log (p. 281).
Null
Storing Container Instance Configuration in Amazon
S3
Amazon ECS container agent configuration is controlled with the environment variables described above.
The Amazon ECS-optimized AMI checks for these variables in /etc/ecs/ecs.config when the container
agent starts and configures the agent accordingly. Certain innocuous environment variables, such as
ECS_CLUSTER, can be passed to the container instance at launch time through Amazon EC2 user data
and written to this file without consequence. However, other sensitive information, such as your AWS
credentials or the ECS_ENGINE_AUTH_DATA variable, should never be passed to an instance in user data or
written to /etc/ecs/ecs.config in a way that they would show up in a .bash_history file.
Storing configuration information in a private bucket in Amazon S3 and granting read-only access to
your container instance IAM role is a secure and convenient way to allow container instance configuration
at launch time. You can store a copy of your ecs.config file in a private bucket, and then use Amazon
EC2 user data to install the AWS CLI and copy your configuration information to /etc/ecs/ecs.config
when the instance launches.
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Automated Task and Image Cleanup
To allow Amazon S3 read-only access for your container instance role
1. Open the IAM console at https://console.aws.amazon.com/iam/.
2. In the navigation pane, choose Roles.
3. Choose the IAM role you use for your container instances (this role is likely titled ecsInstanceRole).
For more information, see Amazon ECS Container Instance IAM Role (p. 210).
4. Under Managed Policies, choose Attach Policy.
5. On the Attach Policy page, type S3 into the Filter field to narrow the policy results.
6. Check the box to the left of the AmazonS3ReadOnlyAccess policy and click Attach Policy.
To store an ecs.config file in Amazon S3
1. Create an ecs.config file with valid environment variables and values from Amazon ECS Container
Agent Configuration (p. 79) using the following format. This example configures private registry
authentication. For more information, see Private Registry Authentication (p. 86).
ECS_ENGINE_AUTH_TYPE=dockercfg
ECS_ENGINE_AUTH_DATA={"https://index.docker.io/v1/":
{"auth":"zq212MzEXAMPLE7o6T25Dk0i","email":"email@example.com"}}
2. Create a private bucket in Amazon S3 to store your configuration file. For more information, see
Create a Bucket in the Amazon Simple Storage Service Getting Started Guide.
3. Upload the ecs.config file to your Amazon S3 bucket. For more information, see Add an Object to a
Bucket in the Amazon Simple Storage Service Getting Started Guide.
To load an ecs.config file from Amazon S3 at launch
1. Complete the above procedures in this section to allow read-only Amazon S3 access to your
container instances and store an ecs.config file in a private Amazon S3 bucket.
2. Launch new container instances by following the steps in Launching an Amazon ECS Container
Instance (p. 42). In Step 10 (p. 44), use the following example script that installs the AWS CLI and
copies your configuration file to /etc/ecs/ecs.config.
#!/bin/bash
yum install -y aws-cli
aws s3 cp s3://your_bucket_name/ecs.config /etc/ecs/ecs.config
Automated Task and Image Cleanup
Each time a task is placed on a container instance, the Amazon ECS container agent checks to see if the
images referenced in the task are the most recent of the specified tag in the repository. If not, it pulls
the images from their respective repositories. If you frequently update the images in your tasks and
services, your container instance storage can quickly fill up with Docker images that you are no longer
using and will likely never use again. For example, you may use a continuous integration and continuous
deployment (CI/CD) pipeline.
Likewise, containers that belong to stopped tasks can also consume container instance storage with log
information, data volumes, and other artifacts. These artifacts are useful for debugging containers that
have stopped unexpectedly, but most of this storage can be safely freed up after a period of time.
By default, the Amazon ECS container agent automatically cleans up stopped tasks and Docker images
that are not being used by any tasks on your container instances.
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Tunable Parameters
Note
The automated image cleanup feature requires at least version 1.13.0 of the Amazon ECS
container agent. To update your agent to the latest version, see Updating the Amazon ECS
Container Agent (p. 73).
Tunable Parameters
The following agent configuration variables are available to tune your automated task and image
cleanup experience. For more information about how to set these variables on your container instances,
see Amazon ECS Container Agent Configuration (p. 79).
ECS_ENGINE_TASK_CLEANUP_WAIT_DURATION
This variable specifies the time to wait before removing any containers that belong to stopped tasks.
The image cleanup process cannot delete an image as long as there is a container that references
it. After images are not referenced by any containers (either stopped or running), then the image
becomes a candidate for cleanup. By default, this parameter is set to 3 hours but you can reduce this
period to as low as 1 minute, if you need to for your application.
ECS_DISABLE_IMAGE_CLEANUP
If you set this variable to true, then automated image cleanup is disabled on your container instance
and no images are automatically removed.
ECS_IMAGE_CLEANUP_INTERVAL
This variable specifies how frequently the automated image cleanup process should check for
images to delete. The default is every 30 minutes but you can reduce this period to as low as 10
minutes to remove images more frequently.
ECS_IMAGE_MINIMUM_CLEANUP_AGE
This variable specifies the minimum amount of time between when an image was pulled and when it
may become a candidate for removal; this is used to prevent cleaning up images that have just been
pulled. The default is 1 hour.
ECS_NUM_IMAGES_DELETE_PER_CYCLE
This variable specifies how many images may be removed during a single cleanup cycle. The default
is 5 and the minimum is 1.
Cleanup Workflow
When the Amazon ECS container agent is running and automated image cleanup is not disabled,
the agent checks for Docker images that are not referenced by running or stopped containers at a
frequency determined by the ECS_IMAGE_CLEANUP_INTERVAL variable. If unused images are found and
they are older than the minimum cleanup time specified by the ECS_IMAGE_MINIMUM_CLEANUP_AGE
variable, the agent removes up to the maximum number of images that are specified with the
ECS_NUM_IMAGES_DELETE_PER_CYCLE variable. The least-recently referenced images are deleted first. After
the images are removed, the agent waits until the next interval and repeats the process again.
Private Registry Authentication
The Amazon ECS container agent can authenticate with private registries, including Docker Hub, using
basic authentication. When you enable private registry authentication, you can use private Docker
images in your task definitions.
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Authentication Formats
The agent looks for two environment variables when it launches: ECS_ENGINE_AUTH_TYPE, which specifies
the type of authentication data that is being sent, and ECS_ENGINE_AUTH_DATA, which contains the actual
authentication credentials.
The Amazon ECS-optimized AMI scans the /etc/ecs/ecs.config file for these variables when the
container instance launches, and each time the service is started (with the sudo start ecs command).
AMIs that are not Amazon ECS-optimized should store these environment variables in a file and pass
them with the --env-file path_to_env_file option to the docker run command that starts the
container agent.
Important
We do not recommend that you inject these authentication environment variables at instance
launch time with Amazon EC2 user data or pass them with the --env option to the docker run
command. These methods are not appropriate for sensitive data like authentication credentials.
To safely add authentication credentials to your container instances, see Storing Container
Instance Configuration in Amazon S3 (p. 84).
Authentication Formats
There are two available formats for private registry authentication, dockercfg and docker.
dockercfg Authentication Format
The dockercfg format uses the authentication information stored in the configuration file that is created
when you run the docker login command. You can create this file by running docker login on your local
system (or by logging in to a container instance and running the command there) and entering your
registry user name, password, and email address. Depending on your Docker version, this file is saved as
either ~/.dockercfg or ~/.docker/config.json.
$ cat ~/.docker/config.json
Output:
{
"auths": {
"https://index.docker.io/v1/": {
"auth": "zq212MzEXAMPLE7o6T25Dk0i"
}
}
}
Important
Newer versions of Docker create a configuration file as shown above with an outer auths object.
The Amazon ECS agent only supports dockercfg authentication data that is in the below
format, without the auths object. If you have the jq utility installed, you can extract this data
with the following command: cat ~/.docker/config.json | jq .auths
$ cat ~/.docker/config.json
Output:
{
"https://index.docker.io/v1/": {
"auth": "zq212MzEXAMPLE7o6T25Dk0i",
"email": "email@example.com"
}
}
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Enabling Private Registries
In the above example, the following environment variables should be added to the environment variable
file (/etc/ecs/ecs.config for the Amazon ECS-optimized AMI) that the Amazon ECS container agent
loads at run time. If you are not using the Amazon ECS-optimized AMI and you are starting the agent
manually with docker run, specify the environment variable file with the --env-file path_to_env_file
option when you start the agent.
ECS_ENGINE_AUTH_TYPE=dockercfg
ECS_ENGINE_AUTH_DATA={"https://index.docker.io/v1/":
{"auth":"zq212MzEXAMPLE7o6T25Dk0i","email":"email@example.com"}}
You can configure multiple private registries with the following syntax.
ECS_ENGINE_AUTH_TYPE=dockercfg
ECS_ENGINE_AUTH_DATA={"repo.example-01.com":
{"auth":"zq212MzEXAMPLE7o6T25Dk0i","email":"email@example-01.com"},"repo.example-02.com":
{"auth":"fQ172MzEXAMPLEoF7225DU0j","email":"email@example-02.com"}}
docker Authentication Format
The docker format uses a JSON representation of the registry server that the agent should authenticate
with, as well as the authentication parameters required by that registry (such as user name, password,
and the email address for that account). For a Docker Hub account, the JSON representation looks like
this:
{
"https://index.docker.io/v1/": {
"username": "my_name",
"password": "my_password",
"email": "email@example.com"
}
}
In this example, the following environment variables should be added to the environment variable file (/
etc/ecs/ecs.config for the Amazon ECS-optimized AMI) that the Amazon ECS container agent loads at
run time. If you are not using the Amazon ECS-optimized AMI and you are starting the agent manually
with docker run, specify the environment variable file with the --env-file path_to_env_file option
when you start the agent.
ECS_ENGINE_AUTH_TYPE=docker
ECS_ENGINE_AUTH_DATA={"https://index.docker.io/v1/":
{"username":"my_name","password":"my_password","email":"email@example.com"}}
You can configure multiple private registries with the following syntax.
ECS_ENGINE_AUTH_TYPE=docker
ECS_ENGINE_AUTH_DATA={"repo.example-01.com":
{"username":"my_name","password":"my_password","email":"email@example-01.com"},"repo.example-02.com":
{"username":"another_name","password":"another_password","email":"email@example-02.com"}}
Enabling Private Registries
Use the following procedure to enable private registries for your container instances.
To enable private registries in the Amazon ECS-optimized AMI
1. Log in to your container instance via SSH.
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2. Open the /etc/ecs/ecs.config file and add the ECS_ENGINE_AUTH_TYPE and ECS_ENGINE_AUTH_DATA
values for your registry and account.
[ec2-user ~]$ sudo vi /etc/ecs/ecs.config
This example authenticates a Docker Hub user account.
ECS_ENGINE_AUTH_TYPE=docker
ECS_ENGINE_AUTH_DATA={"https://index.docker.io/v1/":
{"username":"my_name","password":"my_password","email":"email@example.com"}}
3. Check to see if your agent uses the ECS_DATADIR environment variable to save its state.
[ec2-user ~]$ docker inspect ecs-agent | grep ECS_DATADIR
Output:
"ECS_DATADIR=/data",
Important
If the previous command does not return the ECS_DATADIR environment variable, you
must stop any tasks running on this container instance before stopping the agent. Newer
agents with the ECS_DATADIR environment variable save their state and you can stop and
start them while tasks are running without issues. For more information, see Updating the
Amazon ECS Container Agent (p. 73).
4. Stop the ecs service.
[ec2-user ~]$ sudo stop ecs
Output:
ecs stop/waiting
5. Restart the ecs service.
[ec2-user ~]$ sudo start ecs
Output:
ecs start/running, process 2959
6. (Optional) You can verify that the agent is running and see some information about your new
container instance by querying the agent introspection API. For more information, see the section
called “Amazon ECS Container Agent Introspection” (p. 90).
[ec2-user ~]$ curl http://localhost:51678/v1/metadata
Output:
{
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"ContainerInstanceArn": "<container_instance_ARN>",
"Version": "Amazon ECS Agent - v1.14.1 (467c3d7)"
}
Amazon ECS Container Agent Introspection
The Amazon ECS container agent provides an API for gathering details about the container instance that
the agent is running on and the associated tasks that are running on that instance. You can use the curl
command from within the container instance to query the Amazon ECS container agent (port 51678) and
return container instance metadata or task information.
To view container instance metadata log in to your container instance via SSH and run the following
command. Metadata includes the container instance ID, the Amazon ECS cluster in which the container
instance is registered, and the Amazon ECS container agent version information,
[ec2-user ~]$ curl http://localhost:51678/v1/metadata
Output:
{
"Cluster": "default",
"ContainerInstanceArn": "<container_instance_ARN>",
"Version": "Amazon ECS Agent - v1.14.1 (467c3d7)"
}
To view information about all of the tasks that are running on a container instance, log in to your
container instance via SSH and run the following command:
[ec2-user ~]$ curl http://localhost:51678/v1/tasks
Output:
{
"Tasks": [
{
"Arn": "arn:aws:ecs:us-east-1:<aws_account_id>:task/example5-58ff-46c9-
ae05-543f8example",
"DesiredStatus": "RUNNING",
"KnownStatus": "RUNNING",
"Family": "hello_world",
"Version": "8",
"Containers": [
{
"DockerId": "9581a69a761a557fbfce1d0f6745e4af5b9dbfb86b6b2c5c4df156f1a5932ff1",
"DockerName": "ecs-hello_world-8-mysql-fcae8ac8f9f1d89d8301",
"Name": "mysql"
},
{
"DockerId": "bf25c5c5b2d4dba68846c7236e75b6915e1e778d31611e3c6a06831e39814a15",
"DockerName": "ecs-hello_world-8-wordpress-e8bfddf9b488dff36c00",
"Name": "wordpress"
}
]
}
]
}
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HTTP Proxy Configuration
You can view information for a particular task that is running on a container instance. To specify a
specific task or container, append one of the following to the request:
• The task ARN (?taskarn=task_arn)
• The container Docker ID (?dockerid=docker_id)
To get task information with a Docker ID, log in to your container instance via SSH and run the following
command.
Note
The Amazon ECS container agent introspection API requires full Docker IDs, not the short
version that is shown with docker ps. You can get the full Docker ID for a container by running
the docker ps --no-trunc command on the container instance.
[ec2-user ~]$ curl http://localhost:51678/v1/tasks?
dockerid=9581a69a761a557fbfce1d0f6745e4af5b9dbfb86b6b2c5c4df156f1a5932ff1
Output:
{
"Arn": "arn:aws:ecs:us-east-1:<aws_account_id>:task/example5-58ff-46c9-
ae05-543f8example",
"DesiredStatus": "RUNNING",
"KnownStatus": "RUNNING",
"Family": "hello_world",
"Version": "8",
"Containers": [
{
"DockerId": "9581a69a761a557fbfce1d0f6745e4af5b9dbfb86b6b2c5c4df156f1a5932ff1",
"DockerName": "ecs-hello_world-8-mysql-fcae8ac8f9f1d89d8301",
"Name": "mysql"
},
{
"DockerId": "bf25c5c5b2d4dba68846c7236e75b6915e1e778d31611e3c6a06831e39814a15",
"DockerName": "ecs-hello_world-8-wordpress-e8bfddf9b488dff36c00",
"Name": "wordpress"
}
]
}
HTTP Proxy Configuration
To configure your Amazon ECS container agent to use an HTTP proxy, set the following variables in the
/etc/ecs/ecs.config, /etc/init/ecs.override, and /etc/sysconfig/docker files at launch time (with
Amazon EC2 user data), or manually edit the configuration file and restart the agent afterwards:
/etc/ecs/ecs.config and /etc/init/ecs.override
HTTP_PROXY=10.0.0.131:3128
Set this value to the hostname (or IP address) and port number of an HTTP proxy to use for
the ECS agent to connect to the Internet. For example, your container instances may not have
external network access through an Amazon VPC Internet gateway, NAT gateway, or instance.
NO_PROXY=169.254.169.254,169.254.170.2,/var/run/docker.sock
Set this value to 169.254.169.254,169.254.170.2,/var/run/docker.sock to filter EC2 instance
metadata, IAM roles for tasks, and Docker daemon traffic from the proxy.
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/etc/sysconfig/docker
HTTP_PROXY=10.0.0.131:3128
Set this value to the hostname (or IP address) and port number of an HTTP proxy to use for the
Docker daemon to connect to the Internet. For example, your container instances may not have
external network access through an Amazon VPC Internet gateway, NAT gateway, or instance.
NO_PROXY=169.254.169.254
Set this value to 169.254.169.254 to filter EC2 instance metadata from the proxy.
The above variables only affect the Amazon ECS container agent, ecs-init, and the Docker daemon;
they do not configure Docker or any other services (such as yum) to use the proxy.
Example HTTP proxy user data script
The example user data cloud-boothook script below configures the Amazon ECS container agent, the
Docker daemon, and yum to use an HTTP proxy that you specify. You can also specify a cluster into
which the container instance will register itself.
To use this script when you launch a container instance, follow the steps in Launching an Amazon ECS
Container Instance (p. 42), and in Step 10 (p. 44). Then, copy and paste the cloud-boothook script below
into the User data field (be sure to substitute the red example values with your own proxy and cluster
information).
#cloud-boothook
# Configure Yum, the Docker daemon, and the ECS agent to use an HTTP proxy
# Specify proxy host, port number, and ECS cluster name to use
PROXY_HOST=10.0.0.131
PROXY_PORT=3128
CLUSTER_NAME=proxy-test
# Set Yum HTTP proxy
if [ ! -f /var/lib/cloud/instance/sem/config_yum_http_proxy ]; then
echo "proxy=http://$PROXY_HOST:$PROXY_PORT" >> /etc/yum.conf
echo "$$: $(date +%s.%N | cut -b1-13)" > /var/lib/cloud/instance/sem/config_yum_http_proxy
fi
# Set Docker HTTP proxy
if [ ! -f /var/lib/cloud/instance/sem/config_docker_http_proxy ]; then
echo "export HTTP_PROXY=http://$PROXY_HOST:$PROXY_PORT/" >> /etc/sysconfig/docker
echo "NO_PROXY=169.254.169.254" >> /etc/sysconfig/docker
echo "$$: $(date +%s.%N | cut -b1-13)" > /var/lib/cloud/instance/sem/
config_docker_http_proxy
fi
# Set ECS agent HTTP proxy
if [ ! -f /var/lib/cloud/instance/sem/config_ecs-agent_http_proxy ]; then
echo "ECS_CLUSTER=$CLUSTER_NAME" >> /etc/ecs/ecs.config
echo "HTTP_PROXY=$PROXY_HOST:$PROXY_PORT" >> /etc/ecs/ecs.config
echo "NO_PROXY=169.254.169.254,169.254.170.2,/var/run/docker.sock" >> /etc/ecs/ecs.config
echo "$$: $(date +%s.%N | cut -b1-13)" > /var/lib/cloud/instance/sem/config_ecs-
agent_http_proxy
fi
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Amazon ECS Task Definitions
A task definition is required to run Docker containers in Amazon ECS. Some of the parameters you can
specify in a task definition include:
• Which Docker images to use with the containers in your task
• How much CPU and memory to use with each container
• Whether containers are linked together in a task
• The Docker networking mode to use for the containers in your task
• What (if any) ports from the container are mapped to the host container instance
• Whether the task should continue to run if the container finishes or fails
• The command the container should run when it is started
• What (if any) environment variables should be passed to the container when it starts
• Any data volumes that should be used with the containers in the task
• What (if any) IAM role your tasks should use for permissions
You can define multiple containers and data volumes in a task definition. For a complete description of
the parameters available in a task definition, see Task Definition Parameters (p. 98).
Your entire application stack does not need to exist on a single task definition, and in most cases it
should not. Your application can span multiple task definitions by combining related containers into
their own task definitions, each representing a single component. For more information, see Application
Architecture (p. 94).
Topics
•Application Architecture (p. 94)
•Creating a Task Definition (p. 95)
•Task Definition Parameters (p. 98)
•Using Data Volumes in Tasks (p. 112)
•Using the awslogs Log Driver (p. 117)
•Example Task Definitions (p. 122)
•Updating a Task Definition (p. 125)
•Deregistering Task Definitions (p. 125)
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Application Architecture
When you’re considering how to model task definitions and services, it helps to think about what
processes need to run together on the same instance and how you will scale each component. As an
example, imagine an application that consists of the following components:
• A front-end service that displays information on a web page
• A back-end service that provides APIs for the front-end service
• A data store
In your development environment, you probably run all three containers together on your Docker host.
You might be tempted to use the same approach for your production environment, but this approach has
several drawbacks:
• Changes to one component can impact all three components, which may be a larger scope for the
change than you want
• Each component is more difficult to scale because you have to scale every container proportionally
• Task definitions can only have 10 container definitions and your application stack might require more,
either now or in the future
• Every container in a task definition must land on the same container instance, which may limit your
instance choices to the largest sizes
Instead, you should create task definitions that group the containers that are used for a common
purpose, and separate the different components into multiple task definitions. In this example, three
task definitions each specify one container. The example cluster below has three container instances
registered with three front-end service containers, two back-end service containers, and one data store
service container.
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You can group related containers in a task definition, such as linked containers that must be run
together. For example, you could add a log streaming container to your front-end service and include
that in the same task definition.
After you have your task definitions, you can create services from them to maintain the availability of
your desired tasks. For more information, see Creating a Service (p. 160). In your services, you can
associate containers with Elastic Load Balancing load balancers. For more information, see Service Load
Balancing (p. 141). When your application requirements change, you can update your services to scale
the number of desired tasks up or down, or to deploy newer versions of the containers in your tasks. For
more information, see Updating a Service (p. 165).
Creating a Task Definition
Before you can run Docker containers on Amazon ECS, you must create a task definition.
You can define multiple containers and data volumes in a task definition. For a complete description of
the parameters available in a task definition, see Task Definition Parameters (p. 98).
To create a new task definition
1. Open the Amazon ECS console at https://console.aws.amazon.com/ecs/.
2. From the navigation bar, select the region in which to register your task definition.
3. In the navigation pane, choose Task Definitions.
4. On the Task Definitions page, choose Create new Task Definition.
5. (Optional) If you have a JSON representation of your task definition, complete the following steps:
a. On the Create a Task Definition page, scroll to the bottom of the page and choose Configure
via JSON.
b. Paste your task definition JSON into the text area and choose Save.
c. Verify your information and choose Create.
6. For Task Definition Name, type a name for your task definition. Up to 255 letters (uppercase and
lowercase), numbers, hyphens, and underscores are allowed.
7. (Optional) For Task Role, choose an IAM role that provides permissions for containers in your task to
make calls to AWS APIs on your behalf. For more information, see IAM Roles for Tasks (p. 216).
Note
Only roles that have the Amazon EC2 Container Service Task Role trust relationship are
shown here. For help creating an IAM role for your tasks, see Creating an IAM Role and
Policy for your Tasks (p. 218).
8. (Optional) For Network Mode, choose the Docker network mode to use for the containers in your
task. The available network modes correspond to those described in Network settings in the Docker
run reference.
The default Docker network mode is bridge. If the network mode is set to none, you cannot
specify port mappings in your container definitions, and the task's containers do not have external
connectivity. The host network mode offers the highest networking performance for containers
because they use the host network stack instead of the virtualized network stack provided by the
bridge mode; however, exposed container ports are mapped directly to the corresponding host port,
so you cannot take advantage of dynamic host port mappings or run multiple instantiations of the
same task on a single container instance if port mappings are used.
9. (Optional) For Constraint, define how tasks that are created from this task definition are placed in
your cluster (for example, on container instances with a specific instance type or specific custom
attributes). For more information, see Amazon ECS Task Placement Constraints (p. 130).
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Task Definition Template
10. For each container in your task definition, complete the following steps.
a. Choose Add container.
b. Fill out each required field and any optional fields to use in your container definitions (more
container definition parameters are available in the Advanced container configuration menu).
For more information, see Task Definition Parameters (p. 98).
c. Choose Add to add your container to the task definition.
11. (Optional) To define data volumes for your task, choose Add volume. For more information, see
Using Data Volumes in Tasks (p. 112).
a. For Name, type a name for your volume. Up to 255 letters (uppercase and lowercase), numbers,
hyphens, and underscores are allowed.
b. (Optional) For Source Path, type the path on the host container instance to present to the
container. If you leave this field empty, the Docker daemon assigns a host path for you. If you
specify a source path, the data volume persists at the specified location on the host container
instance until you delete it manually. If the source path does not exist on the host container
instance, the Docker daemon creates it. If the location does exist, the contents of the source
path folder are exported to the container.
12. Choose Create.
Task Definition Template
An empty task definition template is shown below. You can use this template to create your task
definition which can then be pasted into the console JSON input area or saved to a file and used with the
AWS CLI --cli-input-json option. For more information about these parameters, see Task Definition
Parameters (p. 98).
{
"family": "",
"taskRoleArn": "",
"networkMode": "",
"containerDefinitions": [
{
"name": "",
"image": "",
"cpu": 0,
"memory": 0,
"memoryReservation": 0,
"links": [
""
],
"portMappings": [
{
"containerPort": 0,
"hostPort": 0,
"protocol": ""
}
],
"essential": true,
"entryPoint": [
""
],
"command": [
""
],
"environment": [
{
"name": "",
"value": ""
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}
],
"mountPoints": [
{
"sourceVolume": "",
"containerPath": "",
"readOnly": true
}
],
"volumesFrom": [
{
"sourceContainer": "",
"readOnly": true
}
],
"hostname": "",
"user": "",
"workingDirectory": "",
"disableNetworking": true,
"privileged": true,
"readonlyRootFilesystem": true,
"dnsServers": [
""
],
"dnsSearchDomains": [
""
],
"extraHosts": [
{
"hostname": "",
"ipAddress": ""
}
],
"dockerSecurityOptions": [
""
],
"dockerLabels": {
"KeyName": ""
},
"ulimits": [
{
"name": "",
"softLimit": 0,
"hardLimit": 0
}
],
"logConfiguration": {
"logDriver": "",
"options": {
"KeyName": ""
}
}
}
],
"placementConstraints": [
{
"expression": "",
"type": "memberOf"
}
],
"volumes": [
{
"name": "",
"host": {
"sourcePath": ""
}
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}
]
}
Note that you can generate this task definition template using the following AWS CLI command.
aws ecs register-task-definition --generate-cli-skeleton
Task Definition Parameters
Task definitions are split into four basic parts: the task family, the IAM task role, container definitions,
and volumes. The family is the name of the task, and each family can have multiple revisions. The IAM
task role specifies the permissions that containers in the task should have. Container definitions specify
which image to use, how much CPU and memory the container are allocated, and many more options.
Volumes allow you to share data between containers and even persist the data on the container instance
when the containers are no longer running. The family and container definitions are required in a task
definition, while task role, network mode, and volumes are optional.
Parts
•Family (p. 98)
•Task Role (p. 98)
•Network Mode (p. 99)
•Container Definitions (p. 99)
•Task Placement Constraints (p. 111)
•Volumes (p. 111)
Family
family
Type: string
Required: yes
When you register a task definition, you give it a family, which is similar to a name for multiple
versions of the task definition, specified with a revision number. The first task definition that is
registered into a particular family is given a revision of 1, and any task definitions registered after
that are given a later sequential revision number.
Task Role
taskRoleArn
Type: string
Required: no
When you register a task definition, you can provide a task role for an IAM role that allows the
containers in the task permission to call the AWS APIs that are specified in its associated policies on
your behalf. For more information, see IAM Roles for Tasks (p. 216).
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Network Mode
Network Mode
networkMode
Type: string
Required: no
When you register a task definition, you can specify the Docker networking mode to use with
its containers. The default Docker network mode is bridge. If the network mode is set to none,
you cannot specify port mappings in your container definitions, and the task's containers do not
have external connectivity. The host network mode offers the highest networking performance
for containers because they use the host network stack instead of the virtualized network stack
provided by the bridge mode; however, exposed container ports are mapped directly to the
corresponding host port, so you cannot take advantage of dynamic host port mappings or run
multiple instantiations of the same task on a single container instance if port mappings are used.
Container Definitions
When you register a task definition, you must specify a list of container definitions that are passed to the
Docker daemon on a container instance. The following parameters are allowed in a container definition.
Topics
•Standard Container Definition Parameters (p. 99)
•Advanced Container Definition Parameters (p. 102)
Standard Container Definition Parameters
The following task definition parameters are either required or used in most container definitions.
name
Type: string
Required: yes
The name of a container. If you are linking multiple containers together in a task definition, the
name of one container can be entered in the links of another container to connect the containers.
Up to 255 letters (uppercase and lowercase), numbers, hyphens, and underscores are allowed. This
parameter maps to name in the Create a container section of the Docker Remote API and the --name
option to docker run.
image
Type: string
Required: yes
The image used to start a container. This string is passed directly to the Docker daemon. Images
in the Docker Hub registry are available by default. You can also specify other repositories with
repository-url/image:tag. Up to 255 letters (uppercase and lowercase), numbers, hyphens,
underscores, colons, periods, forward slashes, and number signs are allowed. This parameter maps
to Image in the Create a container section of the Docker Remote API and the IMAGE parameter of
docker run.
Note
Amazon ECS task definitions currently only support tags as image identifiers within a
specified repository (and not sha256 digests).
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• Images in Amazon ECR repositories use the full registry/repository:tag naming convention. For
example, aws_account_id.dkr.ecr.region.amazonaws.com/my-web-app:latest
• Images in official repositories on Docker Hub use a single name (for example, ubuntu or mongo).
• Images in other repositories on Docker Hub are qualified with an organization name (for example,
amazon/amazon-ecs-agent).
• Images in other online repositories are qualified further by a domain name (for example, quay.io/
assemblyline/ubuntu).
memory
Type: integer
Required: no
The hard limit (in MiB) of memory to present to the container. If your container attempts to exceed
the memory specified here, the container is killed. This parameter maps to Memory in the Create a
container section of the Docker Remote API and the --memory option to docker run.
You must specify a non-zero integer for one or both of memory or memoryReservation in container
definitions. If you specify both, memory must be greater than memoryReservation. If you specify
memoryReservation, then that value is subtracted from the available memory resources for the
container instance on which the container is placed; otherwise, the value of memory is used.
The Docker daemon reserves a minimum of 4 MiB of memory for a container, so you should not
specify fewer than 4 MiB of memory for your containers.
memoryReservation
Type: integer
Required: no
The soft limit (in MiB) of memory to reserve for the container. When system memory is under
contention, Docker attempts to keep the container memory to this soft limit; however, your
container can consume more memory when it needs to, up to either the hard limit specified with the
memory parameter (if applicable), or all of the available memory on the container instance, whichever
comes first. This parameter maps to MemoryReservation in the Create a container section of the
Docker Remote API and the --memory-reservation option to docker run.
You must specify a non-zero integer for one or both of memory or memoryReservation in container
definitions. If you specify both, memory must be greater than memoryReservation. If you specify
memoryReservation, then that value is subtracted from the available memory resources for the
container instance on which the container is placed; otherwise, the value of memory is used.
For example, if your container normally uses 128 MiB of memory, but occasionally bursts to 256 MiB
of memory for short periods of time, you can set a memoryReservation of 128 MiB, and a memory
hard limit of 300 MiB. This configuration would allow the container to only reserve 128 MiB of
memory from the remaining resources on the container instance, but also allow the container to
consume more memory resources when needed.
portMappings
Type: object array
Required: no
Port mappings allow containers to access ports on the host container instance to send or receive
traffic. This parameter maps to PortBindings in the Create a container section of the Docker Remote
API and the --publish option to docker run. If the network mode of a task definition is set to none,
then you cannot specify port mappings. If the network mode of a task definition is set to host, then
host ports must either be undefined or they must match the container port in the port mapping.
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Note
After a task reaches the RUNNING status, manual and automatic host and container port
assignments are visible in the Network Bindings section of a container description of a
selected task in the Amazon ECS console, or the networkBindings section of describe-tasks
AWS CLI command output or DescribeTasks API responses.
hostPort
Type: integer
Required: no
The port number on the container instance to reserve for your container. You can specify
a non-reserved host port for your container port mapping (this is referred to as static host
port mapping), or you can omit the hostPort (or set it to 0) while specifying a containerPort
and your container will automatically receive a port (this is referred to as dynamic host port
mapping) in the ephemeral port range for your container instance operating system and Docker
version.
The default ephemeral port range is 49153 to 65535, and this range is used for Docker versions
prior to 1.6.0. For Docker version 1.6.0 and later, the Docker daemon tries to read the ephemeral
port range from /proc/sys/net/ipv4/ip_local_port_range (which is 32768 to 61000 on
the latest Amazon ECS-optimized AMI); if this kernel parameter is unavailable, the default
ephemeral port range is used. You should not attempt to specify a host port in the ephemeral
port range, since these are reserved for automatic assignment. In general, ports below 32768
are outside of the ephemeral port range.
The default reserved ports are 22 for SSH, the Docker ports 2375 and 2376, and the Amazon
ECS container agent port 51678. Any host port that was previously user-specified for a running
task is also reserved while the task is running (after a task stops, the host port is released).
The current reserved ports are displayed in the remainingResources of describe-container-
instances output, and a container instance may have up to 100 reserved ports at a time,
including the default reserved ports (automatically assigned ports do not count toward the 100
reserved ports limit).
containerPort
Type: integer
Required: yes, when portMappings are used
The port number on the container that is bound to the user-specified or automatically assigned
host port. If you specify a container port and not a host port, your container automatically
receives a host port in the ephemeral port range (for more information, see hostPort). Port
mappings that are automatically assigned in this way do not count toward the 100 reserved
ports limit of a container instance.
protocol
Type: string
Required: no
The protocol used for the port mapping. Valid values are tcp and udp. The default is tcp.
Important
UDP support is only available on container instances that were launched with version
1.2.0 of the Amazon ECS container agent (such as the amzn-ami-2015.03.c-amazon-
ecs-optimized AMI) or later, or with container agents that have been updated to
version 1.3.0 or later. To update your container agent to the latest version, see
Updating the Amazon ECS Container Agent (p. 73).
If you are specifying a host port, use the following syntax:
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"portMappings": [
{
"containerPort": integer,
"hostPort": integer
}
...
]
If you want an automatically assigned host port, use the following syntax:
"portMappings": [
{
"containerPort": integer
}
...
]
Advanced Container Definition Parameters
The following advanced container definition parameters provide extended capabilities to the docker run
command that is used to launch containers on your Amazon ECS container instances.
Topics
•Environment (p. 102)
•Network Settings (p. 104)
•Storage and Logging (p. 106)
•Security (p. 109)
•Resource Limits (p. 109)
•Docker Labels (p. 110)
Environment
cpu
Type: integer
Required: no
The number of cpu units to reserve for the container. A container instance has 1,024 cpu units for
every CPU core. This parameter specifies the minimum amount of CPU to reserve for a container,
and containers share unallocated CPU units with other containers on the instance with the same
ratio as their allocated amount. This parameter maps to CpuShares in the Create a container section
of the Docker Remote API and the --cpu-shares option to docker run.
Note
You can determine the number of CPU units that are available per Amazon EC2 instance
type by multiplying the vCPUs listed for that instance type on the Amazon EC2 Instances
detail page by 1,024.
For example, if you run a single-container task on a single-core instance type with 512 CPU units
specified for that container, and that is the only task running on the container instance, that
container could use the full 1,024 CPU unit share at any given time. However, if you launched
another copy of the same task on that container instance, each task would be guaranteed a
minimum of 512 CPU units when needed, and each container could float to higher CPU usage if the
other container was not using it, but if both tasks were 100% active all of the time, they would be
limited to 512 CPU units.
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The Docker daemon on the container instance uses the CPU value to calculate the relative CPU
share ratios for running containers. For more information, see CPU share constraint in the Docker
documentation. The minimum valid CPU share value that the Linux kernel will allow is 2; however,
the CPU parameter is not required, and you can use CPU values below 2 in your container definitions.
For CPU values below 2 (including null), the behavior varies based on your Amazon ECS container
agent version:
•Agent versions <= 1.1.0: Null and zero CPU values are passed to Docker as 0, which Docker then
converts to 1,024 CPU shares. CPU values of 1 are passed to Docker as 1, which the Linux kernel
converts to 2 CPU shares.
•Agent versions >= 1.2.0: Null, zero, and CPU values of 1 are passed to Docker as 2.
essential
Type: Boolean
Required: no
If the essential parameter of a container is marked as true, and that container fails or stops for any
reason, all other containers that are part of the task are stopped. If the essential parameter of a
container is marked as false, then its failure does not affect the rest of the containers in a task. If
this parameter is omitted, a container is assumed to be essential.
All tasks must have at least one essential container. If you have an application that is composed
of multiple containers, you should group containers that are used for a common purpose into
components, and separate the different components into multiple task definitions. For more
information, see Application Architecture (p. 94).
"essential": true|false
entryPoint
Important
Early versions of the Amazon ECS container agent do not properly handle entryPoint
parameters. If you have problems using entryPoint , update your container agent or enter
your commands and arguments as command array items instead.
Type: string array
Required: no
The entry point that is passed to the container. This parameter maps to Entrypoint in the Create
a container section of the Docker Remote API and the --entrypoint option to docker run. For
more information about the Docker ENTRYPOINT parameter, go to https://docs.docker.com/engine/
reference/builder/#entrypoint.
"entryPoint": ["string", ...]
command
Type: string array
Required: no
The command that is passed to the container. This parameter maps to Cmd in the Create a container
section of the Docker Remote API and the COMMAND parameter to docker run. For more information
about the Docker CMD parameter, go to https://docs.docker.com/engine/reference/builder/#cmd.
"command": ["string", ...]
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workingDirectory
Type: string
Required: no
The working directory in which to run commands inside the container. This parameter maps to
WorkingDir in the Create a container section of the Docker Remote API and the --workdir option to
docker run.
"workingDirectory": "string"
environment
Type: object array
Required: no
The environment variables to pass to a container. This parameter maps to Env in the Create a
container section of the Docker Remote API and the --env option to docker run.
Important
We do not recommend using plain text environment variables for sensitive information,
such as credential data.
name
Type: string
Required: yes, when environment is used
The name of the environment variable.
value
Type: string
Required: yes, when environment is used
The value of the environment variable.
"environment" : [
{ "name" : "string", "value" : "string" },
{ "name" : "string", "value" : "string" }
]
Network Settings
disableNetworking
Type: Boolean
Required: no
When this parameter is true, networking is disabled within the container. This parameter maps to
NetworkDisabled in the Create a container section of the Docker Remote API.
"disableNetworking": true|false
links
Type: string array
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Required: no
The link parameter allows containers to communicate with each other without the need for port
mappings. The name:internalName construct is analogous to name:alias in Docker links. Up to
255 letters (uppercase and lowercase), numbers, hyphens, and underscores are allowed. For more
information about linking Docker containers, go to https://docs.docker.com/engine/userguide/
networking/default_network/dockerlinks/. This parameter maps to Links in the Create a container
section of the Docker Remote API and the --link option to docker run.
Important
Containers that are collocated on a single container instance may be able to communicate
with each other without requiring links or host port mappings. Network isolation is achieved
on the container instance using security groups and VPC settings.
"links": ["name:internalName", ...]
hostname
Type: string
Required: no
The hostname to use for your container. This parameter maps to Hostname in the Create a container
section of the Docker Remote API and the --hostname option to docker run.
"hostname": "string"
dnsServers
Type: string array
Required: no
A list of DNS servers that are presented to the container. This parameter maps to Dns in the Create a
container section of the Docker Remote API and the --dns option to docker run.
"dnsServers": ["string", ...]
dnsSearchDomains
Type: string array
Required: no
A list of DNS search domains that are presented to the container. This parameter maps to DnsSearch
in the Create a container section of the Docker Remote API and the --dns-search option to docker
run.
"dnsSearchDomains": ["string", ...]
extraHosts
Type: object array
Required: no
A list of hostnames and IP address mappings to append to the /etc/hosts file on the container. This
parameter maps to ExtraHosts in the Create a container section of the Docker Remote API and the
--add-host option to docker run.
"extraHosts": [
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{
"hostname": "string",
"ipAddress": "string"
}
...
]
hostname
Type: string
Required: yes, when extraHosts are used
The hostname to use in the /etc/hosts entry.
ipAddress
Type: string
Required: yes, when extraHosts are used
The IP address to use in the /etc/hosts entry.
Storage and Logging
readonlyRootFilesystem
Type: Boolean
Required: no
When this parameter is true, the container is given read-only access to its root file system. This
parameter maps to ReadonlyRootfs in the Create a container section of the Docker Remote API and
the --read-only option to docker run.
"readonlyRootFilesystem": true|false
mountPoints
Type: object array
Required: no
The mount points for data volumes in your container. This parameter maps to Volumes in the Create
a container section of the Docker Remote API and the --volume option to docker run.
sourceVolume
Type: string
Required: yes, when mountPoints are used
The name of the volume to mount.
containerPath
Type: string
Required: yes, when mountPoints are used
The path on the container to mount the host volume at.
readOnly
Type: boolean
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Required: no
If this value is true, the container has read-only access to the volume. If this value is false, then
the container can write to the volume. The default value is false.
"mountPoints": [
{
"sourceVolume": "string",
"containerPath": "string",
"readOnly": true|false
}
]
volumesFrom
Type: object array
Required: no
Data volumes to mount from another container. This parameter maps to VolumesFrom in the Create a
container section of the Docker Remote API and the --volumes-from option to docker run.
sourceContainer
Type: string
Required: yes, when volumesFrom is used
The name of the container to mount volumes from.
readOnly
Type: Boolean
Required: no
If this value is true, the container has read-only access to the volume. If this value is false, then
the container can write to the volume. The default value is false.
"volumesFrom": [
{
"sourceContainer": "string",
"readOnly": true|false
}
]
logConfiguration
Type: LogConfiguration object
Required: no
The log configuration specification for the container. This parameter maps to LogConfig in the
Create a container section of the Docker Remote API and the --log-driver option to docker run.
By default, containers use the same logging driver that the Docker daemon uses; however the
container may use a different logging driver than the Docker daemon by specifying a log driver
with this parameter in the container definition. To use a different logging driver for a container, the
log system must be configured properly on the container instance (or on a different log server for
remote logging options). For more information on the options for different supported log drivers,
see Configure logging drivers in the Docker documentation.
For more information on using the awslogs log driver in task definitions to send your container logs
to CloudWatch Logs, see Using the awslogs Log Driver (p. 117).
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Note
Amazon ECS currently supports a subset of the logging drivers available to the Docker
daemon (shown in the valid values below). Additional log drivers may be available in future
releases of the Amazon ECS container agent.
This parameter requires version 1.18 of the Docker Remote API or greater on your container
instance. To check the Docker Remote API version on your container instance, log into your container
instance, run the following command, and look for the server API version in the output:
$ sudo docker version
Note
The Amazon ECS container agent running on a container instance must register the logging
drivers available on that instance with the ECS_AVAILABLE_LOGGING_DRIVERS environment
variable before containers placed on that instance can use these log configuration options.
For more information, see Amazon ECS Container Agent Configuration (p. 79).
"logConfiguration": {
"logDriver": "json-file"|"syslog"|"journald"|"gelf"|"fluentd"|"awslogs"|"splunk",
"options": {"string": "string"
...}
logDriver
Type: string
Valid values: "json-file" | "syslog" | "journald" | "gelf" | "fluentd" | "awslogs" |
"splunk"
Required: yes, when logConfiguration is used
The log driver to use for the container. The valid values listed above are log drivers that the
Amazon ECS container agent can communicate with by default.
Note
If you have a custom driver that is not listed above that you would like to work with
the Amazon ECS container agent, you can fork the Amazon ECS container agent project
that is available on GitHub and customize it to work with that driver. We encourage
you to submit pull requests for changes that you would like to have included. However,
Amazon Web Services does not currently provide support for running modified copies
of this software.
This parameter requires version 1.18 of the Docker Remote API or greater on your container
instance. To check the Docker Remote API version on your container instance, log into your
container instance, run the following command, and look for the server API version in the
output:
$ sudo docker version
options
Type: string to string map
Required: no
The configuration options to send to the log driver. This parameter requires version 1.19 of
the Docker Remote API or greater on your container instance. To check the Docker Remote
API version on your container instance, log into your container instance, run the following
command, and look for the server API version in the output:
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$ sudo docker version
Security
privileged
Type: Boolean
Required: no
When this parameter is true, the container is given elevated privileges on the host container instance
(similar to the root user). This parameter maps to Privileged in the Create a container section of
the Docker Remote API and the --privileged option to docker run.
"privileged": true|false
user
Type: string
Required: no
The user name to use inside the container. This parameter maps to User in the Create a container
section of the Docker Remote API and the --user option to docker run.
"user": "string"
dockerSecurityOptions
Type: string array
Required: no
A list of strings to provide custom labels for SELinux and AppArmor multi-level security systems.
This parameter maps to SecurityOpt in the Create a container section of the Docker Remote API and
the --security-opt option to docker run.
"dockerSecurityOptions": ["string", ...]
Note
The Amazon ECS container agent running on a container instance must register with the
ECS_SELINUX_CAPABLE=true or ECS_APPARMOR_CAPABLE=true environment variables before
containers placed on that instance can use these security options. For more information, see
Amazon ECS Container Agent Configuration (p. 79).
Resource Limits
ulimits
Type: object array
Required: no
A list of ulimits to set in the container. This parameter maps to Ulimits in the Create a container
section of the Docker Remote API and the --ulimit option to docker run. This parameter requires
version 1.18 of the Docker Remote API or greater on your container instance. To check the Docker
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Remote API version on your container instance, log into your container instance, run the following
command, and look for the server API version in the output:
$ sudo docker version
"ulimits": [
{
"name":
"core"|"cpu"|"data"|"fsize"|"locks"|"memlock"|"msgqueue"|"nice"|"nofile"|"nproc"|"rss"|"rtprio"|"rttime"|"sigpending"|"stack",
"softLimit": integer,
"hardLimit": integer
}
...
]
name
Type: string
Valid values: "core" | "cpu" | "data" | "fsize" | "locks" | "memlock" | "msgqueue" |
"nice" | "nofile" | "nproc" | "rss" | "rtprio" | "rttime" | "sigpending" | "stack"
Required: yes, when ulimits are used
The type of the ulimit.
hardLimit
Type: integer
Required: yes, when ulimits are used
The hard limit for the ulimit type.
softLimit
Type: integer
Required: yes, when ulimits are used
The soft limit for the ulimit type.
Docker Labels
dockerLabels
Type: string to string map
Required: no
A key/value map of labels to add to the container. This parameter maps to Labels in the Create a
container section of the Docker Remote API and the --label option to docker run. This parameter
requires version 1.18 of the Docker Remote API or greater on your container instance. To check the
Docker Remote API version on your container instance, log into your container instance, run the
following command, and look for the server API version in the output:
$ sudo docker version
"dockerLabels": {"string": "string"
...}
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Task Placement Constraints
When you register a task definition, you can provide task placement constraints that customize
how Amazon ECS places tasks. For example, you can use constraints to place tasks based on
Availability Zone, instance type, or attributes. For more information, see Amazon ECS Task Placement
Constraints (p. 130). The following parameters are allowed in a container definition:
expression
Type: string
Required: no
A cluster query language expression to apply to the constraint. Note you cannot specify an
expression if the constraint type is distinctInstance. For more information, see Cluster Query
Language (p. 134).
type
Type: string
Required: yes
The type of constraint. Use memberOf to restrict selection to a group of valid candidates. Note that
distinctInstance is not supported in task definitions.
Volumes
When you register a task definition, you can optionally specify a list of volumes that will be passed to the
Docker daemon on a container instance and become available for other containers on the same container
instance to access. For more information, see Using Data Volumes in Tasks (p. 112). The following
parameters are allowed in a container definition:
name
Type: string
Required: yes
The name of the volume. Up to 255 letters (uppercase and lowercase), numbers, hyphens, and
underscores are allowed. This name is referenced in the sourceVolume parameter of container
definition mountPoints.
host
Type: object
Required: no
The contents of the host parameter determine whether your data volume persists on the host
container instance and where it is stored. If the host parameter is empty, then the Docker daemon
assigns a host path for your data volume, but the data is not guaranteed to persist after the
containers associated with it stop running.
By default, Docker-managed volumes are created in /var/lib/docker/vfs/dir/. You can change
this default location by writing OPTIONS="-g=/my/path/for/docker/volumes" to /etc/sysconfig/
docker on the container instance.
sourcePath
Type: string
Required: no
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The path on the host container instance that is presented to the container. If this parameter is
empty, then the Docker daemon assigns a host path for you.
If the host parameter contains a sourcePath file location, then the data volume persists at the
specified location on the host container instance until you delete it manually. If the sourcePath
value does not exist on the host container instance, the Docker daemon creates it. If the location
does exist, the contents of the source path folder are exported.
[
{
"name": "string",
"host": {
"sourcePath": "string"
}
}
]
Using Data Volumes in Tasks
There are several use cases for using data volumes in Amazon ECS task definitions. Some common
examples are to provide persistent data volumes for use with containers, to define an empty,
nonpersistent data volume and mount it on multiple containers on the same container instance, and to
share defined data volumes at different locations on different containers on the same container instance.
Note
For operating systems that use devicemapper (such as Amazon Linux and the Amazon ECS-
optimized AMI), only file systems that are available when the Docker daemon is started will be
available to Docker containers. You can use a cloud boothook to mount your file system before
the Docker daemon starts, or you can restart the Docker daemon and the Amazon ECS container
agent after the file system is mounted to make the file system available to your container
volume mounts.
To provide persistent data volumes for containers
When a volume is defined with a sourcePath value, the data volume persists even after all containers
that referenced it have stopped. Any files that exist at the sourcePath are presented to the containers
at the containerPath value, and any files that are written to the containerPath value by running
containers that mount the data volume are written to the sourcePath value on the container instance.
Important
Amazon ECS does not sync your data volumes across container instances. Tasks that use
persistent data volumes can be placed on any container instance in your cluster that has
available capacity. If your tasks require persistent data volumes after stopping and restarting,
you should always specify the same container instance at task launch time with the AWS CLI
start-task command.
1. In the task definition volumes section, define a data volume with name and sourcePath values.
"volumes": [
{
"name": "webdata",
"host": {
"sourcePath": "/ecs/webdata"
}
}
]
2. In the containerDefinitions section, define a container with mountPoints that reference the name
of the defined volume and the containerPath value to mount the volume at on the container.
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"containerDefinitions": [
{
"name": "web",
"image": "nginx",
"cpu": 99,
"memory": 100,
"portMappings": [
{
"containerPort": 80,
"hostPort": 80
}
],
"essential": true,
"mountPoints": [
{
"sourceVolume": "webdata",
"containerPath": "/usr/share/nginx/html"
}
]
}
]
To provide nonpersistent empty data volumes for containers
In some cases, you want containers to share the same empty data volume, but you aren't interested in
keeping the data after the task has finished. For example, you may have two database containers that
need to access the same scratch file storage location during a task.
1. In the task definition volumes section, define a data volume with the name database_scratch.
Note
Because the database_scratch volume does not specify a source path, the Docker
daemon manages the volume for you. When no containers reference this volume, the
Amazon ECS container agent task cleanup service eventually deletes it (by default, this
happens 3 hours after the container exits, but you can configure this duration with the
ECS_ENGINE_TASK_CLEANUP_WAIT_DURATION agent variable). For more information, see
Amazon ECS Container Agent Configuration (p. 79). If you need this data to persist, specify
a sourcePath value for the volume.
"volumes": [
{
"name": "database_scratch",
"host": {}
}
]
2. In the containerDefinitions section, create the database container definitions so they mount the
nonpersistent data volumes.
"containerDefinitions": [
{
"name": "database1",
"image": "my-repo/database",
"cpu": 100,
"memory": 100,
"essential": true,
"mountPoints": [
{
"sourceVolume": "database_scratch",
"containerPath": "/var/scratch"
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}
]
},
{
"name": "database2",
"image": "my-repo/database",
"cpu": 100,
"memory": 100,
"essential": true,
"mountPoints": [
{
"sourceVolume": "database_scratch",
"containerPath": "/var/scratch"
}
]
}
]
To mount a defined volume on multiple containers
You can define a data volume in a task definition and mount that volume at different locations on
different containers. For example, your host container has a website data folder at /data/webroot, and
you may want to mount that data volume as read-only on two different web servers that have different
document roots.
1. In the task definition volumes section, define a data volume with the name webroot and the source
path /data/webroot.
"volumes": [
{
"name": "webroot",
"host": {
"sourcePath": "/data/webroot"
}
}
]
2. In the containerDefinitions section, define a container for each web server with mountPoints
values that associate the webroot volume with the containerPath value pointing to the document
root for that container.
"containerDefinitions": [
{
"name": "web-server-1",
"image": "my-repo/ubuntu-apache",
"cpu": 100,
"memory": 100,
"portMappings": [
{
"containerPort": 80,
"hostPort": 80
}
],
"essential": true,
"mountPoints": [
{
"sourceVolume": "webroot",
"containerPath": "/var/www/html",
"readOnly": true
}
]
},
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{
"name": "web-server-2",
"image": "my-repo/sles11-apache",
"cpu": 100,
"memory": 100,
"portMappings": [
{
"containerPort": 8080,
"hostPort": 8080
}
],
"essential": true,
"mountPoints": [
{
"sourceVolume": "webroot",
"containerPath": "/srv/www/htdocs",
"readOnly": true
}
]
}
]
To mount volumes from another container using volumesFrom
You can define one or more volumes on a container, and then use the volumesFrom parameter
in a different container definition (within the same task) to mount all of the volumes from the
sourceContainer at their originally defined mount points. The volumesFrom parameter applies to
volumes defined in the task definition, and those that are built into the image with a Dockerfile.
1. (Optional) To share a volume that is built into an image, you need to build the image with the
volume declared in a VOLUME instruction. The following example Dockerfile uses an httpd image and
then adds a volume and mounts it at dockerfile_volume in the Apache document root (which is the
folder used by the httpd web server):
FROM httpd
VOLUME ["/usr/local/apache2/htdocs/dockerfile_volume"]
You can build an image with this Dockerfile and push it to a repository, such as Docker Hub, and
use it in your task definition. The example my-repo/httpd_dockerfile_volume image used in the
following steps was built with the above Dockerfile.
2. Create a task definition that defines your other volumes and mount points for the containers. In this
example volumes section, you create an empty volume called empty, which the Docker daemon will
manage. There is also a host volume defined called host_etc, which exports the /etc folder on the
host container instance.
{
"family": "test-volumes-from",
"volumes": [
{
"name": "empty",
"host": {}
},
{
"name": "host_etc",
"host": {
"sourcePath": "/etc"
}
}
],
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In the container definitions section, create a container that mounts the volumes defined earlier. In
this example, the web container (which uses the image built with a volume in the Dockerfile) mounts
the empty and host_etc volumes.
"containerDefinitions": [
{
"name": "web",
"image": "my-repo/httpd_dockerfile_volume",
"cpu": 100,
"memory": 500,
"portMappings": [
{
"containerPort": 80,
"hostPort": 80
}
],
"mountPoints": [
{
"sourceVolume": "empty",
"containerPath": "/usr/local/apache2/htdocs/empty_volume"
},
{
"sourceVolume": "host_etc",
"containerPath": "/usr/local/apache2/htdocs/host_etc"
}
],
"essential": true
},
Create another container that uses volumesFrom to mount all of the volumes that are associated
with the web container. All of the volumes on the web container will likewise be mounted on the
busybox container (including the volume specified in the Dockerfile that was used to build the my-
repo/httpd_dockerfile_volume image).
{
"name": "busybox",
"image": "busybox",
"volumesFrom": [
{
"sourceContainer": "web"
}
],
"cpu": 100,
"memory": 500,
"entryPoint": [
"sh",
"-c"
],
"command": [
"echo $(date) > /usr/local/apache2/htdocs/empty_volume/date && echo $(date)
> /usr/local/apache2/htdocs/host_etc/date && echo $(date) > /usr/local/apache2/htdocs/
dockerfile_volume/date"
],
"essential": false
}
]
}
When this task is run, the two containers mount the volumes, and the command in the busybox
container writes the date and time to a file called date in each of the volume folders, which are then
visible at the web site displayed by the web container.
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Using the awslogs Log Driver
Note
Because the busybox container runs a quick command and then exits, it needs to be set as
"essential": false in the container definition to prevent it from stopping the entire task
when it exits.
Using the awslogs Log Driver
You can configure the containers in your tasks to send log information to CloudWatch Logs. This enables
you to view different logs from your containers in one convenient location, and it prevents your container
logs from taking up disk space on your container instances. This topic helps you get started using the
awslogs log driver in your task definitions.
To send system logs from your Amazon ECS container instances to CloudWatch Logs, see Using
CloudWatch Logs with Container Instances (p. 52). For more information about CloudWatch Logs, see
Monitoring Log Files in the Amazon CloudWatch User Guide.
Topics
•Enabling the awslogs Log Driver on your Container Instances (p. 117)
•Creating Your Log Groups (p. 117)
•Available awslogs Log Driver Options (p. 118)
•Specifying a Log Configuration in your Task Definition (p. 119)
•Viewing awslogs Container Logs in CloudWatch Logs (p. 120)
Enabling the awslogs Log Driver on your Container
Instances
Your Amazon ECS container instances require at least version 1.9.0 of the container agent to enable the
awslogs log driver. For information about checking your agent version and updating to the latest version,
see Updating the Amazon ECS Container Agent (p. 73).
Note
If you are not using the Amazon ECS-optimized AMI (with at least version 1.9.0-1 of the ecs-
init package) for your container instances, you also need to specify that the awslogs logging
driver is available on the container instance when you start the agent by using the following
environment variable in your docker run statement or environment variable file. For more
information, see Installing the Amazon ECS Container Agent (p. 68).
ECS_AVAILABLE_LOGGING_DRIVERS='["json-file","awslogs"]'
Your Amazon ECS container instances also require logs:CreateLogStream and logs:PutLogEvents
permission on the IAM role with which you launch your container instances. If you created your Amazon
ECS container instance role before awslogs log driver support was enabled in Amazon ECS, then you
might need to add this permission. If your container instances use the managed IAM policy for container
instances, then your container instances should have the correct permissions. For information about
checking your Amazon ECS container instance role and attaching the managed IAM policy for container
instances, see To check for the ecsInstanceRole in the IAM console (p. 211).
Creating Your Log Groups
The awslogs log driver can send log streams to existing log groups in CloudWatch Logs, but it cannot
create log groups. Before you launch any tasks that use the awslogs log driver, you must create the log
groups that you intend your containers to use.
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Available awslogs Log Driver Options
As an example, you could have a task with a WordPress container (which uses the awslogs-wordpress log
group) that is linked to a MySQL container (which uses the awslogs-mysql log group). The sections below
show how to create these log groups with the AWS CLI and with the CloudWatch console.
Creating a Log Group with the AWS CLI
The AWS Command Line Interface (AWS CLI) is a unified tool to manage your AWS services. With just
one tool to download and configure, you can control multiple AWS services from the command line and
automate them through scripts. For more information, see the AWS Command Line Interface User Guide.
If you have a working installation of the AWS CLI, you can use it to create your log groups. The command
below creates a log group called awslogs-wordpress in the ap-northeast-1 region. Run this command
for each log group to create, replacing the log group name with your value and region name to the
desired log destination.
aws logs create-log-group --log-group-name awslogs-wordpress --region ap-northeast-1
Creating a Log Group with the CloudWatch Console
The following procedure creates a log group in the CloudWatch console.
To create a log group in the CloudWatch console
1. Open the CloudWatch console at https://console.aws.amazon.com/cloudwatch/.
2. In the left navigation pane, choose Logs.
3. Choose Actions, Create log group.
4. For Log Group Name, enter the name of the log group to create.
5. Choose Create log group to finish.
Available awslogs Log Driver Options
The awslogs log driver supports the following options in Amazon ECS task definitions:
awslogs-region
Required: Yes
Specify the region to which the awslogs log driver should send your Docker logs. You can choose to
send all of your logs from clusters in different regions to a single region in CloudWatch Logs so that
they are all visible in one location, or you can separate them by region for more granularity. Be sure
that the specified log group exists in the region that you specify with this option.
awslogs-group
Required: Yes
You must specify a log group to which the awslogs log driver will send its log streams. For more
information, see Creating Your Log Groups (p. 117).
awslogs-stream-prefix
Required: No
The awslogs-stream-prefix option allows you to associate a log stream with the specified prefix,
the container name, and the ID of the Amazon ECS task to which the container belongs. If you
specify a prefix with this option, then the log stream takes the following format:
prefix-name/container-name/ecs-task-id
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Specifying a Log Configuration in your Task Definition
If you do not specify a prefix with this option, then the log stream is named after the container ID
that is assigned by the Docker daemon on the container instance. Because it is difficult to trace logs
back to the container that sent them with just the Docker container ID (which is only available on the
container instance), we recommend that you specify a prefix with this option.
For Amazon ECS services, you could use the service name as the prefix, which would allow you to
trace log streams to the service that the container belongs to, the name of the container that sent
them, and the ID of the task to which the container belongs.
Specifying a Log Configuration in your Task
Definition
Before your containers can send logs to CloudWatch, you must specify the awslogs log driver for
containers in your task definition. This section describes the log configuration for a container to use the
awslogs log driver. For more information, see Creating a Task Definition (p. 95).
The task definition JSON shown below has a logConfiguration object specified for each container; one
for the WordPress container that sends logs to a log group called awslogs-wordpress, and one for a
MySQL container that sends logs to a log group called awslogs-mysql. Both containers use the awslogs-
example log stream prefix.
{
"containerDefinitions": [
{
"name": "wordpress",
"links": [
"mysql"
],
"image": "wordpress",
"essential": true,
"portMappings": [
{
"containerPort": 80,
"hostPort": 80
}
],
"logConfiguration": {
"logDriver": "awslogs",
"options": {
"awslogs-group": "awslogs-wordpress",
"awslogs-region": "ap-northeast-1",
"awslogs-stream-prefix": "awslogs-example"
}
},
"memory": 500,
"cpu": 10
},
{
"environment": [
{
"name": "MYSQL_ROOT_PASSWORD",
"value": "password"
}
],
"name": "mysql",
"image": "mysql",
"cpu": 10,
"memory": 500,
"essential": true,
"logConfiguration": {
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"logDriver": "awslogs",
"options": {
"awslogs-group": "awslogs-mysql",
"awslogs-region": "ap-northeast-1",
"awslogs-stream-prefix": "awslogs-example"
}
}
}
],
"family": "awslogs-example"
}
In the Amazon ECS console, the log configuration for the wordpress container is specified as shown in
the image below.
After you have registered a task definition with the awslogs log driver in a container definition log
configuration, you can run a task or create a service with that task definition to start sending logs to
CloudWatch Logs. For more information, see Running Tasks (p. 127) and Creating a Service (p. 160).
Viewing awslogs Container Logs in CloudWatch Logs
After your container instance role has the proper permissions to send logs to CloudWatch Logs, your
container agents are updated to at least version 1.9.0, and you have configured and started a task with
containers that use the awslogs log driver, your configured containers should be sending their log data to
CloudWatch Logs. You can view and search these logs in the console.
To view your CloudWatch Logs data for a container from the Amazon ECS console
1. Open the Amazon ECS console at https://console.aws.amazon.com/ecs/.
2. On the Clusters page, select the cluster that contains the task to view.
3. On the Cluster: cluster_name page, choose Tasks and select the task to view.
4. On the Task: task_id page, expand the container view by choosing the arrow to the left of the
container name.
5. In the Log Configuration section, choose View logs in CloudWatch, which opens the associated log
stream in the CloudWatch console.
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To view your CloudWatch Logs data in the CloudWatch console
1. Open the CloudWatch console at https://console.aws.amazon.com/cloudwatch/.
2. In the left navigation pane, choose Logs.
3. Select a log group to view. You should see the log groups that you created in Creating Your Log
Groups (p. 117).
4. Choose a log stream to view.
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Example Task Definitions
Below are some task definition examples that you can use to start creating your own task definitions. For
more information, see Task Definition Parameters (p. 98) and Creating a Task Definition (p. 95).
Topics
•WordPress and MySQL (p. 122)
•awslogs Log Driver (p. 123)
•Amazon ECR Image and Task Definition IAM Role (p. 124)
•Entrypoint with Command (p. 124)
WordPress and MySQL
The following task definition specifies a WordPress container and a MySQL container that are linked
together. These WordPress container exposes the container port 80 on the host port 80. The security
group on the container instance would need to open port 80 in order for this WordPress installation to
be accessible from a web browser.
For more information about the WordPress container, go to the official WordPress Docker Hub repository
at https://registry.hub.docker.com/_/wordpress/. For more information about the MySQL container, go
to the official MySQL Docker Hub repository at https://registry.hub.docker.com/_/mysql/.
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Important
If you use this task definition with a load balancer, you need to complete the WordPress
setup installation through the web interface on the container instance immediately after the
container starts. The load balancer health check ping expects a 200 response from the server,
but WordPress returns a 301 until the installation is completed. If the load balancer health check
fails, the load balancer deregisters the instance.
{
"containerDefinitions": [
{
"name": "wordpress",
"links": [
"mysql"
],
"image": "wordpress",
"essential": true,
"portMappings": [
{
"containerPort": 80,
"hostPort": 80
}
],
"memory": 500,
"cpu": 10
},
{
"environment": [
{
"name": "MYSQL_ROOT_PASSWORD",
"value": "password"
}
],
"name": "mysql",
"image": "mysql",
"cpu": 10,
"memory": 500,
"essential": true
}
],
"family": "hello_world"
}
awslogs Log Driver
The following example demonstrates how to use the awslogs log driver in a task definition. The nginx
container will send its logs to the ecs-log-streaming log group in the us-west-2 region. For more
information, see Using the awslogs Log Driver (p. 117).
{
"containerDefinitions": [
{
"memory": 128,
"portMappings": [
{
"hostPort": 80,
"containerPort": 80,
"protocol": "tcp"
}
],
"essential": true,
"name": "nginx-container",
"image": "nginx",
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"logConfiguration": {
"logDriver": "awslogs",
"options": {
"awslogs-group": "ecs-log-streaming",
"awslogs-region": "us-west-2"
}
},
"cpu": 0
}
],
"family": "example_task_1"
}
Amazon ECR Image and Task Definition IAM Role
The following example uses an Amazon ECR image called aws-nodejs-sample with the v1 tag from the
123456789012.dkr.ecr.us-west-2.amazonaws.com registry. The container in this task will inherit IAM
permissions from the arn:aws:iam::123456789012:role/AmazonECSTaskS3BucketRole role. For more
information, see IAM Roles for Tasks (p. 216).
{
"containerDefinitions": [
{
"name": "sample-app",
"image": "123456789012.dkr.ecr.us-west-2.amazonaws.com/aws-nodejs-sample:v1",
"memory": "200",
"cpu": "10",
"essential": true
}
],
"family": "example_task_3",
"taskRoleArn": "arn:aws:iam::123456789012:role/AmazonECSTaskS3BucketRole"
}
Entrypoint with Command
The following example demonstrates the syntax for a Docker container that uses an entry point and a
command argument. This container will ping google.com 4 times and then exit.
{
"containerDefinitions": [
{
"memory": 32,
"essential": true,
"entryPoint": [
"ping"
],
"name": "alpine_ping",
"readonlyRootFilesystem": true,
"image": "alpine:3.4",
"command": [
"-c",
"4",
"google.com"
],
"cpu": 16
}
],
"family": "example_task_2"
}
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Updating a Task Definition
Updating a Task Definition
To update a task definition you create a task definition revision. Then if the task definition is used in a
service, you can update that service to use it.
To create a task definition revision
1. Open the Amazon ECS console at https://console.aws.amazon.com/ecs/.
2. From the navigation bar, choose the Region that contains your task definition.
3. In the navigation pane, choose Task Definitions.
4. On the Task Definitions page, select the box to the left of the task definition you want to revise and
then choose Create new revision.
5. On the Create new revision of Task Definition page, make the changes you want. For example, if
you want to change the existing container definitions (such as the container image, memory limits,
or port mappings), select the Container Name to make the changes and then choose Update.
6. Verify the information and then choose Create.
7. If your task definition is used in a service, update your service with the updated task definition. See
Updating a Service (p. 165).
Deregistering Task Definitions
If you decide that you no longer need a task definition in Amazon ECS, you can deregister the task
definition so that it no longer displays in your ListTaskDefinition API calls or in the console when you
want to run a task or update a service.
When you deregister a task definition, it is immediately marked as INACTIVE. Existing tasks and services
that reference an INACTIVE task definition continue to run without disruption, and existing services that
reference an INACTIVE task definition can still scale up or down by modifying the service's desired count.
You cannot use an INACTIVE task definition to run new tasks or create new services, and you cannot
update an existing service to reference an INACTIVE task definition (although there may be up to a 10
minute window following deregistration where these restrictions have not yet taken effect).
Note
At this time, INACTIVE task definitions remain discoverable in your account indefinitely; however,
this behavior is subject to change in the future, so you should not rely on INACTIVE task
definitions persisting beyond the life cycle of any associated tasks and services.
Use the following procedure to deregister a task definition.
To deregister a task definition
1. Open the Amazon ECS console at https://console.aws.amazon.com/ecs/.
2. From the navigation bar, choose the region that contains your task definition.
3. In the navigation pane, choose Task Definitions.
4. On the Task Definitions page, choose the task definition name that contains one or more revisions
that you want to deregister.
5. On the Task Definition name page, select the box to the left of each task definition revision you
want to deregister.
6. Choose Actions, and then choose Deregister.
7. Verify the information in the Deregister Task Definition window, and choose Deregister to finish.
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Scheduling Amazon ECS Tasks
Amazon EC2 Container Service (Amazon ECS) is a shared state, optimistic concurrency system that
provides flexible scheduling capabilities for your tasks and containers. The Amazon ECS schedulers
leverage the same cluster state information provided by the Amazon ECS API to make appropriate
placement decisions.
Amazon ECS provides a service scheduler (for long-running tasks and applications), the ability to run
tasks manually (for batch jobs or single run tasks), with Amazon ECS placing tasks on your cluster for
you, and the ability to run tasks on the container instance that you specify, so that you can integrate with
custom or third-party schedulers or place a task manually on a specific container instance.
Service Scheduler
The service scheduler is ideally suited for long running stateless services and applications. The service
scheduler ensures that the specified number of tasks are constantly running and reschedules tasks when
a task fails (for example, if the underlying container instance fails for some reason). The service scheduler
optionally also makes sure that tasks are registered against an Elastic Load Balancing load balancer. You
can update your services that are maintained by the service scheduler, such as deploying a new task
definition, or changing the running number of desired tasks. By default, the service scheduler spreads
tasks across Availability Zones, but you can use task placement strategies and constraints to customize
task placement decisions. For more information, see Services (p. 138).
Manually Running Tasks
The RunTask action is ideally suited for processes such as batch jobs that perform work and then stop.
For example, you could have a process call RunTask when work comes into a queue. The task pulls
work from the queue, performs the work, and then exits. Using RunTask, you can allow the default task
placement strategy to distribute tasks randomly across your cluster, which minimizes the chances that a
single instance gets a disproportionate number of tasks. Alternatively, you can use RunTask to customize
how the scheduler places tasks using task placement strategies and constraints. For more information,
see RunTask in the Amazon EC2 Container Service API Reference.
Custom Schedulers
Amazon ECS allows you to create your own schedulers that meet the needs of your business, or to
leverage third party schedulers. Blox is an open source project that gives you more control over how your
containerized applications run on Amazon ECS. It enables you to build schedulers and integrate third-
party schedulers with Amazon ECS while leveraging Amazon ECS to fully manage and scale your clusters.
For more information, see StartTask in the Amazon EC2 Container Service API Reference.
Task Placement
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Running Tasks
The RunTask and CreateService actions enable you to specify task placement constraints and task
placement strategies to customize how Amazon ECS places your tasks. For more information, see
Amazon ECS Task Placement (p. 128).
Contents
•Running Tasks (p. 127)
•Amazon ECS Task Placement (p. 128)
•Task Life Cycle (p. 136)
Running Tasks
Running tasks manually is ideal in certain situations. For example, suppose that you are developing a
task but you are not ready to deploy this task with the service scheduler. Perhaps your task is a one-time
or periodic batch job that does not make sense to keep running or restart when it finishes.
To keep a specified number of tasks running or to place your tasks behind a load balancer, use the
Amazon ECS service scheduler instead. For more information, see Services (p. 138).
To run a task
1. Open the Amazon ECS console at https://console.aws.amazon.com/ecs/.
2. From the navigation bar, select the region that your cluster is in.
3. In the navigation pane, choose Task Definitions and select the task definition to run.
• To run the latest revision of a task definition shown here, select the box to the left of the task
definition to run.
• To run an earlier revision of a task definition shown here, select the task definition to view all
active revisions, then select the revision to run.
4. Choose Actions, Run Task.
5. For Cluster, choose the cluster to use. For Number of tasks, type the number of tasks to launch with
this task definition. For Task Group, type the name of the task group.
6. (Optional) For Task Placement, you can specify how tasks are placed using task placement strategies
and constraints. Choose from the following options:
•AZ Balanced Spread - distribute tasks across Availability Zones and across container instances in
the Availability Zone.
•AZ Balanced BinPack - distribute tasks across Availability Zones and across container instances
with the least available memory.
•BinPack - distribute tasks based on the least available amount of CPU or memory.
•One Task Per Host - place, at most, one task from the service on each container instance.
•Custom - define your own task placement strategy. See Amazon ECS Task Placement (p. 128) for
examples.
For more information, see Amazon ECS Task Placement (p. 128).
7. (Optional) To send command or environment variable overrides to one or more containers in your
task definition, or to specify an IAM role task override, choose Advanced Options and complete the
following steps:
a. For Task Role Override, choose an IAM role that provides permissions for containers in your
task to make calls to AWS APIs on your behalf. For more information, see IAM Roles for
Tasks (p. 216).
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Note that only roles with the Amazon EC2 Container Service Task Role trust relationship are
shown here. For more information about creating an IAM role for your tasks, see Creating an
IAM Role and Policy for your Tasks (p. 218).
b. For Container Overrides, choose a container to which to send a command or environment
variable override.
•For a command override: For Command override, type the command override to send. If
your container definition does not specify an ENTRYPOINT, the format should be a comma-
separated list of non-quoted strings. For example:
/bin/sh,-c,echo,$DATE
If your container definition does specify an ENTRYPOINT (such as sh,-c), the format should be
an unquoted string, which is surrounded with double quotes and passed as an argument to
the ENTRYPOINT command. For example:
while true; do echo $DATE > /var/www/html/index.html; sleep 1; done
•For environment variable overrides: Choose Add Environment Variable. For Key, type the
name of your environment variable. For Value, type a string value for your environment value
(without surrounding quotes).
This environment variable override is sent to the container as:
MY_ENV_VAR="This variable contains a string."
8. Review your task information and choose Run Task.
Note
If your task moves from PENDING to STOPPED, or if it displays a PENDING status and then
disappears from the listed tasks, your task may be stopping due to an error. For more
information, see Checking Stopped Tasks for Errors (p. 273) in the troubleshooting
section.
Amazon ECS Task Placement
When you launch a task into a cluster, Amazon ECS must determine where to place the task based on the
requirements specified in the task definition, such as CPU and memory. Similarly, when you scale down
the task count, Amazon ECS must determine which tasks to terminate. You can apply task placement
strategies and constraints to customize how Amazon ECS places and terminates tasks.
A task placement strategy is an algorithm for selecting instances for task placement or tasks for
termination. For example, Amazon ECS can select instances at random or it can select instances such
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that tasks are distributed evenly across a group of instances. A task placement constraint is a rule that
is considered during task placement. For example, you can use constraints to place tasks based on
Availability Zone or instance type. You can associate attributes, which are name/value pairs, with your
container instances and then use a constraint to place tasks based on attribute.
You can use strategies and constraints together. For example, you can distribute tasks across Availability
Zones and bin pack tasks based on memory within each Availability Zone, but only for G2 instances.
When Amazon ECS places tasks, it uses the following process to select container instances:
1. Identify the instances that satisfy the CPU, memory, and port requirements in the task definition.
2. Identify the instances that satisfy the task placement constraints.
3. Identify the instances that satisfy the task placement strategies.
4. Select the instances for task placement.
Contents
•Amazon ECS Task Placement Strategies (p. 129)
•Amazon ECS Task Placement Constraints (p. 130)
•Cluster Query Language (p. 134)
Amazon ECS Task Placement Strategies
A task placement strategy is an algorithm for selecting instances for task placement or tasks for
termination. For more information, see Amazon ECS Task Placement (p. 128).
Strategy Types
Amazon ECS supports the following task placement strategies:
binpack
Place tasks based on the least available amount of CPU or memory. This minimizes the number of
instances in use.
random
Place tasks randomly.
spread
Place tasks evenly based on the specified value. Accepted values are attribute key:value pairs,
instanceId, or host. Service tasks are spread based on the tasks from that service.
Example Strategies
You can specify task placement strategies with the following actions: CreateService and RunTask.
The following strategy distributes tasks evenly across Availability Zones.
"placementStrategy": [
{
"field": "attribute:ecs.availability-zone",
"type": "spread"
}
]
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The following strategy distributes tasks evenly across all instances.
"placementStrategy": [
{
"field": "instanceId",
"type": "spread"
}
]
The following strategy bin packs tasks based on memory.
"placementStrategy": [
{
"field": "memory",
"type": "binpack"
}
]
The following strategy places tasks randomly.
"placementStrategy": [
{
"type": "random"
}
]
The following strategy distributes tasks evenly across Availability Zones and then distributes tasks evenly
across the instances within each Availability Zone.
"placementStrategy": [
{
"field": "attribute:ecs.availability-zone",
"type": "spread”
},
{
"field": "instanceId",
"type": "spread"
}
]
The following strategy distributes tasks evenly across Availability Zones and then bin packs tasks based
on memory within each Availability Zone.
"placementStrategy": [
{
"field": "attribute:ecs.availability-zone",
"type": "spread”
},
{
"field": "memory",
"type": "binpack"
}
]
Amazon ECS Task Placement Constraints
A task placement constraint is a rule that is considered during task placement. For more information, see
Amazon ECS Task Placement (p. 128).
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Constraint Types
Amazon ECS supports the following types of task placement constraints:
distinctInstance
Place each task on a different container instance.
memberOf
Place tasks on container instances that satisfy an expression.
For more information about expression syntax, see Cluster Query Language (p. 134).
Attributes
You can add custom metadata to your container instances, known as attributes. Each attribute has a
name and an optional string value. You can use the built-in attributes provided by Amazon ECS or define
custom attributes.
Built-in Attributes
Amazon ECS automatically applies the following attributes to your container instances.
ecs.ami-id
The ID of the AMI used to launch the instance. An example value for this attribute is "ami-eca289fb".
ecs.availability-zone
The Availability Zone for the instance. An example value for this attribute is "us-east-1a".
ecs.instance-type
The instance type for the instance. An example value for this attribute is "g2.2xlarge".
ecs.os-type
The operating system for the instance. The possible values for this attribute are "linux" and
"windows".
Custom Attributes
You can apply custom attributes to your container instances. For example, you can define an attribute
with the name "stack" and a value of "prod".
Adding an Attribute
You can add custom attributes at instance registration time using the container agent or manually, using
the AWS Management Console. For more information about using the container agent, see Amazon ECS
Container Agent Configuration Parameters (p. ).
To add custom attributes using the console
1. Open the Amazon ECS console at https://console.aws.amazon.com/ecs/.
2. In the navigation pane, choose Clusters and select a cluster.
3. On the ECS Instances tab, select the check box for the container instance.
4. Choose Actions, View/Edit Attributes.
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5. For each attribute, do the following:
a. Choose Add attribute.
b. Type a name and a value for the attribute.
c. Choose the checkmark icon to save the attribute.
6. When you are finished adding attributes, choose Close.
Adding custom attributes using the AWS CLI
The following examples demonstrate how to add custom attributes using the put-attributes command.
Example: Single Attribute
The following example adds the custom attribute "stack=prod" to the specified container instance in the
default cluster.
aws ecs put-attributes --attributes name=stack,value=prod,targetId=arn
Example: Multiple Attributes
The following example adds the custom attributes "stack=prod" and "project=a" to the specified
container instance in the default cluster.
aws ecs put-attributes --attributes name=stack,value=prod,targetId=arn
name=project,value=a,targetId=arn
Filtering by Attribute
You can apply a filter for your container instances, allowing you to see custom attributes.
Filter container instances by attribute using the console
1. Open the Amazon EC2 console at https://console.aws.amazon.com/ec2/.
2. Choose a cluster that has container instances.
3. Choose ECS Instances.
4. Set column visibility preferences by choosing the gear icon ( ) and selecting the attributes to
display. This setting persists across all container clusters associated with your account.
5. Using the Filter by attributes text field, type or select the attributes you would like to filter by. The
format must be AttributeName:AttributeValue.
For Filter by attributes, type or select the attributes by which to filter. After you select the attribute
name, you are prompted for the attribute value.
6. Add additional attributes to the filter as needed. Remove an attribute by choosing the X next to it.
Filter container instances by attribute using the AWS CLI
The following examples demonstrate how to filter container instances by attribute using the list-
constainer-instances command. For more information about the filter syntax, see Cluster Query
Language (p. 134).
Example: Built-in Attribute
The following example uses built-in attributes to list the g2.2xlarge instances.
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aws ecs list-container-instances --filter "attribute:ecs.instance-type == g2.2xlarge"
Example: Custom Attribute
The following example lists the instances with the custom attribute "stack=prod".
aws ecs list-container-instances --filter "attribute:stack == prod"
Example: Exclude an Attribute Value
The following example lists the instances with the custom attribute "stack" unless the attribute value is
"prod".
aws ecs list-container-instances --filter "attribute:stack != prod"
Example: Multiple Attribute Values
The following example uses built-in attributes to list the instances of type t2.small or t2.medium.
aws ecs list-container-instances --filter "attribute:ecs.instance-type in [t2.small,
t2.medium]"
Example: Multiple Attributes
The following example uses built-in attributes to list the T2 instances in Availability Zone us-east-1a.
aws ecs list-container-instances --filter "attribute:ecs.instance-type =~ t2.* and
attribute:ecs.availability-zone == us-east-1a"
Task Groups
You can identify a set of related tasks as a task group. All tasks with the same task group name are
considered as a set when performing spread placement. For example, suppose that you are running
different applications in one cluster, such as databases and web servers. To ensure that your databases
are balanced across Availability Zones, add them to a task group named "databases" and then use this
task group as a constraint for task placement.
When you launch a task using the RunTask or StartTask action, you can specify the name of the task
group for the task. If you don't specify a task group for the task, the default name is the family name of
the task definition (for example, family:my-task-definition).
For tasks launched by the service scheduler, the task group name is the name of the service (for example,
service:my-service-name).
Limits
• A task group name must be 255 characters or less.
• Each task can be in exactly one group.
• After launching a task, you cannot modify its task group.
Example Constraints
You can specify task placement constraints with the following actions: CreateService,
RegisterTaskDefinition, and RunTask.
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The following constraint places tasks on T2 instances.
"placementConstraints": [
{
"expression": "attribute:ecs.instance-type =~ t2.*",
"type": "memberOf"
}
]
The following constraint places tasks on instances in the databases task group.
"placementConstraints": [
{
"expression": "task:group == databases",
"type": "memberOf"
}
]
The following constraint places each task in the group on a different instance.
"placementConstraints": [
{
"type": "distinctInstance"
}
]
Cluster Query Language
Cluster queries are expressions that enable you to group objects. For example, you can group container
instances by attributes such as Availability Zone, instance type, or custom metadata. For more
information, see Attributes (p. 131).
After you have defined a group of container instances, you can customize Amazon ECS to place tasks on
container instances based on group. For more information, see Running Tasks (p. 127) and Creating
a Service (p. 160). You can also apply a group filter when listing container instances. For more
information, see Filtering by Attribute (p. 132).
Expression Syntax
Expressions have the following syntax:
subject operator [argument]
Subject
The attribute or field to be evaluated.
You can select container instances by attribute. Specify attributes as follows:
attribute:attribute-name
You can also select container instances by task group. Specify task groups as follows:
task:group
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Operator
The comparison operator. The following operators are supported.
Operator Description
==, equals String equality
!=, not_equals String inequality
>, greater_than Greater than
>=, greater_than_equal Greater than or equal to
<, less_than Less than
<=, less_than_equal Less than or equal to
exists Subject exists
!exists, not_exists Subject does not exist
in Value in argument list
!in, not_in Value not in argument list
=~, matches Pattern match
!~, not_matches Pattern mismatch
Argument
For many operators, the argument is a literal value.
The in and not_in operators expect an argument list as the argument. You specify an argument list as
follows:
[argument1, argument2, ..., argumentN]
The matches and not_matches operators expect an argument that conforms to the Java regular
expression syntax. For more information, see java.util.regex.Pattern.
Compound Expressions
You can combine expressions using the following Boolean operators:
• &&, and
• ||, or
• !, not
You can specify precedence using parentheses:
(expression1 or expression2) and expression3
Example Expressions
The following are example expressions.
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Example: String Equality
The following expression selects instances with the specified instance type.
attribute:ecs.instance-type == t2.small
Example: Argument List
The following expression selects instances in the us-east-1a or us-east-1b Availability Zone.
attribute:ecs.availability-zone in [us-east-1a, us-east-1b]
Example: Compound Expression
The following expression selects G2 instances that are not in the us-east-1d Availability Zone.
attribute:ecs.instance-type =~ g2.* and attribute:ecs.availability-zone != us-east-1d
Example: Task Affinity
The following expression selects instances that are hosting tasks in the service:production group.
task:group == service:production
Example: Task Anti-Affinity
The following expression selects instances that are not hosting tasks in the database group.
not(task:group == database)
Task Life Cycle
When a task is started on a container instance, either manually or as part of a service, it can pass through
several states before it finishes on its own or is stopped manually. Some tasks are meant to run as batch
jobs that naturally progress through from PENDING to RUNNING to STOPPED. Other tasks, which can be part
of a service, are meant to continue running indefinitely, or to be scaled up and down as needed.
When task status changes are requested, such as stopping a task or updating the desired count of a
service to scale it up or down, the Amazon ECS container agent tracks these changes as the last known
status of the task and the desired status of the task. The flow chart below shows the different paths that
task status can take, based on the action that causes the status change.
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Task Life Cycle
The center path shows the natural progression of a batch job that stops on its own. A persistent task that
is not meant to finish would also be on the center path, but it would stop at the RUNNING:RUNNING stage.
The paths to the right show what happens at a given state if an API call reaches the agent to stop the
task or a container instance. The paths to the left show what happens if the container instance a task is
running on is removed, whether by forcefully deregistering it or by terminating the instance.
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Services
Amazon ECS allows you to run and maintain a specified number (the "desired count") of instances of a
task definition simultaneously in an ECS cluster. This is called a service. If any of your tasks should fail or
stop for any reason, the Amazon ECS service scheduler launches another instance of your task definition
to replace it and maintain the desired count of tasks in the service.
In addition to maintaining the desired count of tasks in your service, you can optionally run your service
behind a load balancer. The load balancer distributes traffic across the tasks that are associated with the
service.
Topics
•Service Concepts (p. 138)
•Service Definition Parameters (p. 139)
•Service Load Balancing (p. 141)
•Service Auto Scaling (p. 152)
•Creating a Service (p. 160)
•Updating a Service (p. 165)
•Deleting a Service (p. 166)
Service Concepts
• If a task in a service stops, the task is killed and restarted. This process continues until your service
reaches the number of desired running tasks.
• You can optionally run your service behind a load balancer. For more information, see Service Load
Balancing (p. 141).
• You can optionally specify a deployment configuration for your service. During a deployment (which is
triggered by updating the task definition or desired count of a service), the service scheduler uses the
minimum healthy percent and maximum percent parameters to determine the deployment strategy.
For more information, see Service Definition Parameters (p. 139).
• When the service scheduler launches new tasks, it attempts to balance them across the Availability
Zones in your cluster with the following logic:
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• Determine which of the container instances in your cluster can support your service's task definition
(for example, they have the required CPU, memory, ports, and container instance attributes).
• Sort the valid container instances by the fewest number of running tasks for this service in the same
Availability Zone as the instance. For example, if zone A has one running service task and zones
B and C each have zero, valid container instances in either zone B or C are considered optimal for
placement.
• Place the new service task on a valid container instance in an optimal Availability Zone (based on
the previous steps), favoring container instances with the fewest number of running tasks for this
service.
• When the service scheduler stops running tasks, it attempts to maintain balance across the Availability
Zones in your cluster with the following logic:
• Sort the container instances by the largest number of running tasks for this service in the same
Availability Zone as the instance. For example, if zone A has one running service task and zones
B and C each have two, container instances in either zone B or C are considered optimal for
termination.
• Stop the task on a container instance in an optimal Availability Zone (based on the previous steps),
favoring container instances with the largest number of running tasks for this service.
Service Definition Parameters
A service definition defines which task definition to use with your service, how many instantiations of
that task to run, and which load balancers (if any) to associate with your tasks.
{
"cluster": "",
"serviceName": "",
"taskDefinition": "",
"loadBalancers": [
{
"targetGroupArn": "",
"loadBalancerName": "",
"containerName": "",
"containerPort": 0
}
],
"desiredCount": 0,
"clientToken": "",
"role": "",
"deploymentConfiguration": {
"maximumPercent": 0,
"minimumHealthyPercent": 0
}
}
Note
You can create the above service definition template with the following AWS CLI command.
aws ecs create-service --generate-cli-skeleton
You can specify the following parameters in a service definition.
cluster
The short name or full Amazon Resource Name (ARN) of the cluster on which to run your service. If
you do not specify a cluster, the default cluster is assumed.
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serviceName
The name of your service. Up to 255 letters (uppercase and lowercase), numbers, hyphens, and
underscores are allowed. Service names must be unique within a cluster, but you can have similarly
named services in multiple clusters within a region or across multiple regions.
taskDefinition
The family and revision (family:revision) or full ARN of the task definition to run in your service.
If a revision is not specified, the latest ACTIVE revision is used.
loadBalancers
A load balancer object representing the load balancer to use with your service. Currently, you are
limited to one load balancer or target group per service. After you create a service, the load balancer
name or target group ARN, container name, and container port specified in the service definition are
immutable.
For Elastic Load Balancing Classic Load Balancers, this object must contain the load balancer name,
the container name (as it appears in a container definition), and the container port to access from
the load balancer. When a task from this service is placed on a container instance, the container
instance is registered with the load balancer specified here.
For Elastic Load Balancing Application Load Balancers, this object must contain the load balancer
target group ARN, the container name (as it appears in a container definition), and the container
port to access from the load balancer. When a task from this service is placed on a container
instance, the container instance and port combination is registered as a target in the target group
specified here.
targetGroupArn
The full Amazon Resource Name (ARN) of the Elastic Load Balancing target group associated
with a service.
loadBalancerName
The name of the load balancer.
containerName
The name of the container (as it appears in a container definition) to associate with the load
balancer.
containerPort
The port on the container to associate with the load balancer. This port must correspond to a
containerPort in the service's task definition. Your container instances must allow ingress traffic
on the hostPort of the port mapping.
desiredCount
The number of instantiations of the specified task definition to place and keep running on your
cluster.
clientToken
Unique, case-sensitive identifier you provide to ensure the idempotency of the request. Up to 32
ASCII characters are allowed.
role
The name or full Amazon Resource Name (ARN) of the IAM role that allows Amazon ECS to make
calls to your load balancer on your behalf. This parameter is required if you are using a load balancer
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with your service. If you specify the role parameter, you must also specify a load balancer object
with the loadBalancers parameter.
If your specified role has a path other than /, then you must either specify the full role ARN (this is
recommended) or prefix the role name with the path. For example, if a role with the name bar has a
path of /foo/ then you would specify /foo/bar as the role name. For more information, see Friendly
Names and Paths in the IAM User Guide.
deploymentConfiguration
Optional deployment parameters that control how many tasks run during the deployment and the
ordering of stopping and starting tasks.
maximumPercent
The maximumPercent parameter represents an upper limit on the number of your service's tasks
that are allowed in the RUNNING or PENDING state during a deployment, as a percentage of the
desiredCount (rounded down to the nearest integer). This parameter enables you to define
the deployment batch size. For example, if your service has a desiredCount of four tasks and a
maximumPercent value of 200%, the scheduler may start four new tasks before stopping the four
older tasks (provided that the cluster resources required to do this are available). The default
value for maximumPercent is 200%.
The maximum number of tasks during a deployment is the desiredCount multiplied by the
maximumPercent/100, rounded down to the nearest integer value.
minimumHealthyPercent
The minimumHealthyPercent represents a lower limit on the number of your service's tasks that
must remain in the RUNNING state during a deployment, as a percentage of the desiredCount
(rounded up to the nearest integer). This parameter enables you to deploy without using
additional cluster capacity. For example, if your service has a desiredCount of four tasks and a
minimumHealthyPercent of 50%, the scheduler may stop two existing tasks to free up cluster
capacity before starting two new tasks. Tasks for services that do not use a load balancer are
considered healthy if they are in the RUNNING state; tasks for services that do use a load balancer
are considered healthy if they are in the RUNNING state and the container instance it is hosted
on is reported as healthy by the load balancer. The default value for minimumHealthyPercent is
50% in the console and 100% for the AWS CLI, the AWS SDKs, and the APIs.
The minimum healthy tasks during a deployment is the desiredCount multiplied by the
minimumHealthyPercent/100, rounded up to the nearest integer value.
placementConstraints
An array of placement constraint objects to use for tasks in your service. You can specify a maximum
of 10 constraints per task (this limit includes constraints in the task definition and those specified at
run time).
placementStrategy
The placement strategy objects to use for tasks in your service. You can specify a maximum of 5
strategy rules per service.
Service Load Balancing
Your Amazon ECS service can optionally be configured to use Elastic Load Balancing to distribute traffic
evenly across the tasks in your service.
Elastic Load Balancing provides two types of load balancers: Application Load Balancers and Classic Load
Balancers.
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Application Load Balancer
An Application Load Balancer makes routing decisions at the application layer (HTTP/HTTPS), supports
path-based routing, and can route requests to one or more ports on each container instance in your
cluster. Application Load Balancers support dynamic host port mapping. For example, if your task's
container definition specifies port 80 for an NGINX container port, and port 0 for the host port, then the
host port is dynamically chosen from the ephemeral port range of the container instance (such as 32768
to 61000 on the latest Amazon ECS-optimized AMI). When the task is launched, the NGINX container
is registered with the Application Load Balancer as an instance ID and port combination, and traffic is
distributed to the instance ID and port corresponding to that container. This dynamic mapping allows
you to have multiple tasks from a single service on the same container instance. For more information,
see the Application Load Balancer Guide.
Classic Load Balancer
A Classic Load Balancer makes routing decisions at either the transport layer (TCP/SSL) or the application
layer (HTTP/HTTPS). Classic Load Balancers currently require a fixed relationship between the load
balancer port and the container instance port. For example, it is possible to map the load balancer
port 80 to the container instance port 3030 and the load balancer port 4040 to the container instance
port 4040. However, it is not possible to map the load balancer port 80 to port 3030 on one container
instance and port 4040 on another container instance. This static mapping requires that your cluster
has at least as many container instances as the desired count of a single service that uses a Classic Load
Balancer. For more information, see the Classic Load Balancer Guide.
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Amazon ECS services can use either type of load balancer. However, Application Load Balancers offer
several new features that make them particularly attractive for use with Amazon ECS services:
• Application Load Balancers allow containers to use dynamic host port mapping (so that multiple tasks
from the same service are allowed per container instance).
• Application Load Balancers support path-based routing and priority rules (so that multiple services can
use the same listener port on a single Application Load Balancer).
We recommend using Application Load Balancers for your Amazon ECS services so that you can
take advantage of these latest features. For more information about Elastic Load Balancing and the
differences between the two load balancer types, see the Elastic Load Balancing User Guide.
Note
Currently, Amazon ECS services can only specify a single load balancer or target group. If your
service requires access to multiple load balanced ports (for example, port 80 and port 443 for
an HTTP/HTTPS service), you must use a Classic Load Balancer with multiple listeners. To use
an Application Load Balancer, separate the single HTTP/HTTPS service into two services, where
each handles requests for different ports. Then, each service could use a different target group
behind a single Application Load Balancer.
Topics
•Load Balancing Concepts (p. 144)
•Check the Service Role for your Account (p. 144)
•Creating a Load Balancer (p. 145)
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Load Balancing Concepts
• All of the containers that are launched in a single task definition are always placed on the same
container instance. For Classic Load Balancers, you may choose to put multiple containers (in the same
task definition) behind the same load balancer by defining multiple host ports in the service definition
and adding those listener ports to the load balancer. For example, if a task definition consists of
Elasticsearch using port 3030 on the container instance, with Logstash and Kibana using port 4040 on
the container instance, the same load balancer can route traffic to Elasticsearch and Kibana through
two listeners. For more information, see Listeners for Your Classic Load Balancer in the Classic Load
Balancer Guide.
Important
We do not recommend connecting multiple services to the same Classic Load Balancer.
Because entire container instances are registered and deregistered with Classic Load Balancers
(and not host and port combinations), this configuration can cause issues if a task from one
service stops, causing the entire container instance to be deregistered from the Classic Load
Balancer while another task from a different service on the same container instance is still
using it. If you want to connect multiple services to a single load balancer (for example, to
save costs), we recommend using an Application Load Balancer.
• There is a limit of one load balancer or target group per service.
• Your load balancer subnet configuration must include all subnets that your container instances reside
in.
• After you create a service, the target group ARN or load balancer name, container name, and container
port specified in the service definition are immutable. You cannot add, remove, or change the load
balancer configuration of an existing service. If you update the task definition for the service, the
container name and container port that were specified when the service was created must remain in
the task definition.
• If a service's task fails the load balancer health check criteria, the task is killed and restarted. This
process continues until your service reaches the number of desired running tasks.
• If you are experiencing problems with your load balancer-enabled services, see Troubleshooting
Service Load Balancers (p. 278).
Check the Service Role for your Account
Amazon ECS needs permission to register and deregister container instances with your load balancer
when tasks are created and stopped.
In most cases, the Amazon ECS service role is automatically created for you in the Amazon ECS console
first run experience. You can use the following procedure to check and see if your account already has an
Amazon ECS service role.
To check for the ecsServiceRole in the IAM console
1. Open the IAM console at https://console.aws.amazon.com/iam/.
2. In the navigation pane, choose Roles.
3. Search the list of roles for ecsServiceRole. If the role does not exist, see Amazon ECS Service
Scheduler IAM Role (p. 212) to create the role. If the role does exist, select the role to view the
attached policies.
4. Choose Permissions.
5. In the Managed Policies section, ensure that the AmazonEC2ContainerServiceRole managed policy
is attached to the role. If the policy is attached, your Amazon ECS service role is properly configured.
If not, follow the substeps below to attach the policy.
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a. Choose Attach Policy.
b. For Filter, type AmazonEC2ContainerServiceRole to narrow the available policies to attach.
c. Select the box to the left of the AmazonEC2ContainerServiceRole policy and choose Attach
Policy.
6. Choose Trust Relationships, Edit Trust Relationship.
7. Verify that the trust relationship contains the following policy. If the trust relationship matches the
policy below, choose Cancel. If the trust relationship does not match, copy the policy into the Policy
Document window and choose Update Trust Policy.
{
"Version": "2008-10-17",
"Statement": [
{
"Sid": "",
"Effect": "Allow",
"Principal": {
"Service": "ecs.amazonaws.com"
},
"Action": "sts:AssumeRole"
}
]
}
Creating a Load Balancer
This section provides a hands-on introduction to using Elastic Load Balancing through the AWS
Management Console to use with your Amazon ECS services. In this section, you create an external load
balancer that receives public HTTP traffic and routes it to your Amazon ECS container instances.
Elastic Load Balancing provides two types of load balancers: Application Load Balancers and Classic Load
Balancers, and Amazon ECS services can use either type of load balancer. However, Application Load
Balancers offer several new features that make them particularly attractive for use with Amazon ECS
services:
• Application Load Balancers allow containers to use dynamic host port mapping (so that multiple tasks
from the same service are allowed per container instance).
• Application Load Balancers support path-based routing and priority rules (so that multiple services can
use the same listener port on a single Application Load Balancer).
We recommend that you use Application Load Balancers for your Amazon ECS services so that you can
take advantage of these latest features. For more information about Elastic Load Balancing and the
differences between the two load balancer types, see the Elastic Load Balancing User Guide.
Note
Currently, Amazon ECS services can only specify a single load balancer or target group. If your
service requires access to multiple load balanced ports (for example, port 80 and port 443 for
an HTTP/HTTPS service), you must use a Classic Load Balancer with multiple listeners. To use
an Application Load Balancer, separate the single HTTP/HTTPS service into two services, where
each handles requests for different ports. Then, each service could use a different target group
behind a single Application Load Balancer.
Topics
•Creating an Application Load Balancer (p. 146)
•Creating a Classic Load Balancer (p. 149)
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Creating an Application Load Balancer
This section walks you through the process of creating an Application Load Balancer in the AWS
Management Console.
Define Your Load Balancer
First, provide some basic configuration information for your load balancer, such as a name, a network,
and a listener.
A listener is a process that checks for connection requests. It is configured with a protocol and a port for
front-end (client to load balancer) connections, and protocol and a port for back-end (load balancer to
back-end instance) connections. In this example, you configure a listener that accepts HTTP requests on
port 80 and sends them to the containers in your tasks on port 80 using HTTP.
To define your load balancer
1. Open the Amazon EC2 console at https://console.aws.amazon.com/ec2/.
2. From the navigation bar, select a region for your load balancer. Be sure to select the same region
that you selected for your Amazon ECS container instances.
3. In the navigation pane, under LOAD BALANCING, choose Load Balancers.
4. Choose Create Load Balancer.
5. On the Select load balancer type page, choose Application Load Balancer and then choose
Continue.
6. Complete the Configure Load Balancer page as follows:
a. For Name, type a name for your load balancer.
b. For Scheme, an Internet-facing load balancer routes requests from clients over the Internet to
targets. An internal load balancer routes requests to targets using private IP addresses.
c. For IP address type, choose ipv4 to support IPv4 addresses only or dualstack to support both
IPv4 and IPv6 addresses.
d. For Listeners, the default is a listener that accepts HTTP traffic on port 80. You can keep the
default listener settings, modify the protocol or port of the listener, or choose Add to add
another listener.
Note
If you plan on routing traffic to more than one target group, see ListenerRules for
details on how to add host or path-based rules.
e. For VPC, select the same VPC that you used for the container instances on which you intend to
run your service.
f. For Availability Zones, select the check box for the Availability Zone(s) to enable for your load
balancer. If there is one subnet for that Availability Zone, it is selected. If there is more than one
subnet for that Availability Zone, select one of the subnets. Note that you can select only one
subnet per Availability Zone. Your load balancer subnet configuration must include all subnets
that your container instances reside in.
g. Choose Next: Configure Security Settings.
(Optional) Configure Security Settings
If you created a secure listener in the previous step, complete the Configure Security Settings page as
follows; otherwise, choose Next: Configure Security Groups.
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To configure security settings
1. If you have a certificate from AWS Certificate Manager, choose Choose an existing certificate from
AWS Certificate Manager (ACM), and then choose the certificate from Certificate name.
2. If you have already uploaded a certificate using IAM, choose Choose an existing certificate from
AWS Identity and Access Management (IAM), and then choose your certificate from Certificate
name.
3. If you have a certificate ready to upload, choose Upload a new SSL Certificate to AWS Identity and
Access Management (IAM). For Certificate name, type a name for the certificate. For Private Key,
copy and paste the contents of the private key file (PEM-encoded). In Public Key Certificate, copy
and paste the contents of the public key certificate file (PEM-encoded). In Certificate Chain, copy
and paste the contents of the certificate chain file (PEM-encoded), unless you are using a self-signed
certificate and it's not important that browsers implicitly accept the certificate.
4. For Select policy, choose a predefined security policy. For details on the security policies, see
Security Policies.
5. Choose Next: Configure Security Groups.
Configure Security Groups
You must assign a security group to your load balancer that allows inbound traffic to the ports that you
specified for your listeners. Amazon ECS does not automatically update the security groups associated
with Elastic Load Balancing load balancers or Amazon ECS container instances.
To assign a security group to your load balancer
1. On the Assign Security Groups page, choose Create a new security group.
2. Enter a name and description for your security group, or leave the default name and description.
This new security group contains a rule that allows traffic to the port that you configured your
listener to use.
Note
Later in this topic, you will create a security group rule for your container instances
that allows traffic on all ports coming from the security group created here, so that the
Application Load Balancer can route traffic to dynamically assigned host ports on your
container instances.
3. Choose Next: Configure Routing to go to the next page in the wizard.
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Configure Routing
In this section, you create a target group for your load balancer and the health check criteria for targets
that are registered within that group.
To create a target group and configure health checks
1. For Target group, keep the default, New target group.
2. For Name, type a name for the new target group.
3. Set Protocol and Port as needed.
4. For Health checks, keep the default health check settings.
5. Choose Next: Register Targets.
Register Targets
Your load balancer distributes traffic between the targets that are registered to its target groups.
When you associate a target group to an Amazon ECS service, Amazon ECS automatically registers and
deregisters containers with your target group. Because Amazon ECS handles target registration, you do
not add targets to your target group at this time.
To skip target registration
1. In the Registered instances section, ensure that no instances are selected for registration.
2. Choose Next: Review to go to the next page in the wizard.
Review and Create
Review your load balancer and target group configuration and choose Create to create your load
balancer.
Create a Security Group Rule for your Container Instances
After your Application Load Balancer has been created, you must add an inbound rule to your container
instance security group that allows traffic from your load balancer to reach the containers.
To allow inbound traffic from your load balancer to your container instances
1. Open the Amazon EC2 console at https://console.aws.amazon.com/ec2/.
2. In the left navigation, choose Security Groups.
3. Choose the security group that your container instances use. If you created your container instances
by using the Amazon ECS first run wizard, this security group may have the description, ECS Allowed
Ports.
4. Choose the Inbound tab, and then choose Edit.
5. For Type, choose All traffic.
6. For Source, choose Custom, and then type the name of your Application Load Balancer security
group that you created in Configure Security Groups (p. 147). This rule allows all traffic from your
Application Load Balancer to reach the containers in your tasks that are registered with your load
balancer.
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7. Choose Save to finish.
Create an Amazon ECS Service
After your load balancer and target group are created, you can specify the target group in a service
definition when you create a service. When each task for your service is started, the container and port
combination specified in the service definition is registered with your target group and traffic is routed
from the load balancer to that container. For more information, see Creating a Service (p. 160).
Creating a Classic Load Balancer
This section walks you through the process of creating a Classic Load Balancer in the AWS Management
Console.
Note that you can create your Classic Load Balancer for use with EC2-Classic or a VPC. Some of the tasks
described in these procedures apply only to load balancers in a VPC.
Define Your Load Balancer
First, provide some basic configuration information for your load balancer, such as a name, a network,
and a listener.
A listener is a process that checks for connection requests. It is configured with a protocol and a port
for front-end (client to load balancer) connections and a protocol, and protocol and a port for back-end
(load balancer to back-end instance) connections. In this example, you configure a listener that accepts
HTTP requests on port 80 and sends them to the back-end instances on port 80 using HTTP.
To define your load balancer
1. Open the Amazon EC2 console at https://console.aws.amazon.com/ec2/.
2. From the navigation bar, select a region for your load balancer. Be sure to select the same region
that you selected for your Amazon ECS container instances.
3. In the navigation pane, under LOAD BALANCING, choose Load Balancers.
4. Choose Create Load Balancer.
5. On the Select load balancer type page, choose Classic Load Balancer.
6. For Load Balancer name, enter a unique name for your load balancer.
The load balancer name you choose must be unique within your set of load balancers, must have a
maximum of 32 characters, and must only contain alphanumeric characters or hyphens.
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7. For Create LB inside, select the same network that your container instances are located in: EC2-
Classic or a specific VPC.
8. The default values configure an HTTP load balancer that forwards traffic from port 80 at the
load balancer to port 80 of your container instances, but you can modify these values for your
application. For more information, see Listeners for Your Classic Load Balancer in the Classic Load
Balancer Guide.
9. [EC2-VPC] To improve the availability of your load balancer, select at least two subnets in different
Availability Zones. Your load balancer subnet configuration must include all subnets that your
container instances reside in. In the Select Subnets section, under Available Subnets, select the
subnets. The subnets that you select are moved under Selected Subnets.
Note
If you selected EC2-Classic as your network, or you have a default VPC but did not choose
Enable advanced VPC configuration, you do not see Select Subnets.
10. Choose Next: Assign Security Groups to go to the next page in the wizard.
Assign a Security Group to Your Load Balancer in a VPC
If you created your load balancer in a VPC, you must assign it a security group that allows inbound traffic
to the ports that you specified for your load balancer and the health checks for your load balancer.
Amazon ECS does not automatically update the security groups associated with Elastic Load Balancing
load balancers or Amazon ECS container instances.
Note
If you selected EC2-Classic as your network, you do not see this page in the wizard and you can
go to the next step. Elastic Load Balancing provides a security group that is assigned to your
load balancer for EC2-Classic automatically.
To assign a security group to your load balancer
1. On the Assign Security Groups page, choose Create a new security group.
2. Enter a name and description for your security group, or leave the default name and description.
This new security group contains a rule that allows traffic to the port that you configured your load
balancer to use. If you specified a different port for the health checks, you must choose Add Rule to
add a rule that allows inbound traffic to that port as well.
Note
You should also assign this security group to container instances in your service, or another
security group with the same rules.
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3. Choose Next: Configure Security Settings to go to the next page in the wizard.
(Optional) Configure Security Settings
For this tutorial, you can choose Next: Configure Health Check to continue to the next step. For more
information about creating a HTTPS load balancer and using additional security features, see HTTPS
Load Balancers in the Classic Load Balancer Guide.
Configure Health Checks for Your EC2 Instances
Elastic Load Balancing automatically checks the health of the tasks in your service. If Elastic Load
Balancing finds an unhealthy task, it stops sending traffic to the instance and reroutes traffic to healthy
instances. Amazon ECS stops your unhealthy task and starts another instance of that task.
Note
The following procedure configures an HTTP (port 80) load balancer, but you can modify these
values for your application.
To configure a health check for your instances
1. On the Configure Health Check page, do the following:
a. Leave Ping Protocol set to its default value of HTTP.
b. Leave Ping Port set to its default value of 80.
c. For Ping Path, replace the default value with a single forward slash ("/"). This tells Elastic Load
Balancing to send health check queries to the default home page for your web server, such as
index.html or default.html.
d. Leave the other fields at their default values.
2. Choose Next: Add EC2 Instances to go to the next page in the wizard.
Load Balancer Instance Registration
Your load balancer distributes traffic between the instances that are registered to it. When you assign
your load balancer to an Amazon ECS service, Amazon ECS automatically registers and deregisters
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container instances when tasks from your service are running on them. Because Amazon ECS handles
container instance registration, you do not add container instances to your load balancer at this time.
To skip instance registration and tag the load balancer
1. On the Add EC2 Instances page, for Add Instances to Load Balancer, ensure that no instances are
selected for registration.
2. Leave the other fields at their default values.
3. Choose Next: Add Tags to go to the next page in the wizard.
Tag Your Load Balancer (Optional)
You can tag your load balancer, or continue to the next step. Note that you can tag your load balancer
later on; for more information, see Tag Your Classic Load Balancer in the Classic Load Balancer Guide.
To add tags to your load balancer
1. On the Add Tags page, specify a key and a value for the tag.
2. To add another tag, choose Create Tag and specify a key and a value for the tag.
3. After you are finished adding tags, choose Review and Create.
Create and Verify Your Load Balancer
Before you create the load balancer, review the settings that you selected. After creating the load
balancer, you can create a service that uses it to verify that it's sending traffic to your container instances.
To finish creating your load balancer
1. On the Review page, check your settings. If you need to make changes to the initial settings, choose
the corresponding edit link.
2. Choose Create to create your load balancer.
3. After you are notified that your load balancer was created, choose Close.
Create an Amazon ECS Service
After your load balancer is created, you can specify it in a service definition when you create a service.
For more information, see Creating a Service (p. 160).
Service Auto Scaling
Your Amazon ECS service can optionally be configured to use Service Auto Scaling to adjust its desired
count up or down in response to CloudWatch alarms. Service Auto Scaling is available in all regions that
support Amazon ECS.
Amazon ECS publishes CloudWatch metrics with your service’s average CPU and memory usage. You can
use these service utilization metrics to scale your service up to deal with high demand at peak times, and
to scale your service down to reduce costs during periods of low utilization. For more information, see
Service Utilization (p. 177).
You can also use CloudWatch metrics published by other services, or custom metrics that are specific to
your application. For example, a web service could increase the number of tasks based on Elastic Load
Balancing metrics such as SurgeQueueLength, and a batch job could increase the number of tasks based
on Amazon SQS metrics like ApproximateNumberOfMessagesVisible.
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Service Auto Scaling Required IAM Permissions
You can also use Service Auto Scaling in conjunction with Auto Scaling for Amazon EC2 on your ECS
cluster to scale your cluster, and your service, as a result to the demand. For more information, see
Tutorial: Scaling Container Instances with CloudWatch Alarms (p. 182).
Service Auto Scaling Required IAM Permissions
Service Auto Scaling is made possible by a combination of the Amazon ECS, CloudWatch, and Application
Auto Scaling APIs. Services are created and updated with Amazon ECS, alarms are created with
CloudWatch, and scaling policies are created with Application Auto Scaling. IAM users must have
the appropriate permissions for these services before they can use Service Auto Scaling in the AWS
Management Console or with the AWS CLI or SDKs. In addition to the standard IAM permissions for
creating and updating services, Service Auto Scaling requires the following permissions:
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Action": [
"application-autoscaling:*",
"cloudwatch:DescribeAlarms",
"cloudwatch:PutMetricAlarm"
],
"Resource": [
"*"
]
}
]
}
The Create Services (p. 226) and Update Services (p. 227) IAM policy examples show the permissions
that are required for IAM users to use Service Auto Scaling in the AWS Management Console.
The Application Auto Scaling service needs permission to describe your ECS services and CloudWatch
alarms, as well as permissions to modify your service's desired count on your behalf. You must create
an IAM role (ecsAutoscaleRole) for your ECS services to provide these permissions and then associate
that role with your service before it can use Application Auto Scaling. If an IAM user has the required
permissions to use Service Auto Scaling in the Amazon ECS console, create IAM roles, and attach IAM
role policies to them, then that user can create this role automatically as part of the Amazon ECS
console create service (p. ) or update service (p. 165) workflows, and then use the role for any
other service later (in the console or with the CLI/SDKs). You can also create the role by following the
procedures in Amazon ECS Service Auto Scaling IAM Role (p. 214).
Service Auto Scaling Concepts
• The ECS service scheduler respects the desired count at all times, but as long as you have active scaling
policies and alarms on a service, Service Auto Scaling could change a desired count that was manually
set by you.
• If a service's desired count is set below its minimum capacity value, and an alarm triggers a scale out
activity, Application Auto Scaling scales the desired count up to the minimum capacity value and then
continues to scale out as required, based on the scaling policy associated with the alarm. However, a
scale in activity will not adjust the desired count, because it is already below the minimum capacity
value.
• If a service's desired count is set above its maximum capacity value, and an alarm triggers a scale in
activity, Application Auto Scaling scales the desired count down to the maximum capacity value and
then continues to scale in as required, based on the scaling policy associated with the alarm. However,
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a scale out activity will not adjust the desired count, because it is already above the maximum capacity
value.
• During scaling activities, the actual running task count in a service is the value that Service Auto
Scaling uses as its starting point, as opposed to the desired count, which is what processing capacity
is supposed to be. This prevents excessive (runaway) scaling that could not be satisfied, for example,
if there are not enough container instance resources to place the additional tasks. If the container
instance capacity is available later, the pending scaling activity may succeed, and then further scaling
activities can continue after the cool down period.
Amazon ECS Console Experience
The Amazon ECS console's service creation and service update workflows support Service Auto
Scaling. The ECS console handles the ecsAutoscaleRole and policy creation, provided that the IAM
user who is using the console has the permissions described in Service Auto Scaling Required IAM
Permissions (p. 153), and that they can create IAM roles and attach policies to them.
When you configure a service to use Service Auto Scaling in the console, your service is automatically
registered as a scalable target with Application Auto Scaling so that you can configure scaling policies
that scale your service up and down. You can also create and update the scaling policies and CloudWatch
alarms that trigger them in the Amazon ECS console.
To create a new ECS service that uses Service Auto Scaling, see Creating a Service (p. 160).
To update an existing service to use Service Auto Scaling, see Updating a Service (p. 165).
AWS CLI and SDK Experience
You can configure Service Auto Scaling by using the AWS CLI or the AWS SDKs, but you must observe the
following considerations.
• Service Auto Scaling is made possible by a combination of the Amazon ECS, CloudWatch, and
Application Auto Scaling APIs. Services are created and updated with Amazon ECS, alarms are created
with CloudWatch, and scaling policies are created with Application Auto Scaling. For more information
about these specific API operations, see the Amazon EC2 Container Service API Reference, the Amazon
CloudWatch API Reference, and the Application Auto Scaling API Reference. For more information
about the AWS CLI commands for these services, see the ecs, cloudwatch, and application-autoscaling
sections of the AWS Command Line Interface Reference.
• Before your service can use Service Auto Scaling, you must register it as a scalable target with the
Application Auto Scaling RegisterScalableTarget API operation.
• After your ECS service is registered as a scalable target, you can create scaling policies with the
Application Auto Scaling PutScalingPolicy API operation to specify what should happen when your
CloudWatch alarms are triggered.
• After you create the scaling policies for your service, you can create the CloudWatch alarms that
trigger the scaling events for your service with the CloudWatch PutMetricAlarm API operation.
Tutorial: Service Auto Scaling with CloudWatch
Service Utilization Metrics
The following procedures help you to create an Amazon ECS cluster and a service that uses Service Auto
Scaling to scale up (and down) using CloudWatch alarms.
Amazon ECS publishes CloudWatch metrics with your service’s average CPU and memory usage. You can
use these service utilization metrics to scale your service up to deal with high demand at peak times, and
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to scale your service down to reduce costs during periods of low utilization. For more information, see
Service Utilization (p. 177).
In this tutorial, you create a cluster and a service (that runs behind an Elastic Load Balancing load
balancer) using the Amazon ECS first run wizard. Then you configure Service Auto Scaling on the
service with CloudWatch alarms that use the CPUUtilization metric to scale your service up or down,
depending on the current application load.
When the CPU utilization of your service rises above 75% (meaning that more than 75% of the CPU that
is reserved for the service is being used), the scale out alarm triggers Service Auto Scaling to add another
task to your service to help out with the increased load. Conversely, when the CPU utilization of your
service drops below 25%, the scale in alarm triggers a decrease in the service's desired count to free up
those cluster resources for other tasks and services.
Prerequisites
This tutorial assumes that you have an AWS account and an IAM administrative user with permissions to
perform all of the actions described within, and an Amazon EC2 key pair in the current region. If you do
not have these resources, or your are not sure, you can create them by following the steps in Setting Up
with Amazon ECS (p. 8).
Your Amazon ECS container instances also require ecs:StartTelemetrySession permission on the
IAM role that you launch your container instances with. If you created your Amazon ECS container
instance role before CloudWatch metrics were available for Amazon ECS, then you might need to add
this permission. For information about checking your Amazon ECS container instance role and attaching
the managed IAM policy for container instances, see To check for the ecsInstanceRole in the IAM
console (p. 211).
Step 1: Create a Cluster and a Service
After you have enabled CloudWatch metrics for your clusters and services, you can create a cluster and
service using the Amazon ECS first run wizard. The first run wizard takes care of creating the necessary
IAM roles and policies for this tutorial, an Auto Scaling group for your container instances, and it creates
a service that runs behind a load balancer. The wizard also makes the later clean up process much easier,
because you can delete the entire AWS CloudFormation stack in one step.
For this tutorial, you create a cluster called service-autoscaling and a service called sample-webapp.
To create your cluster and service
1. Open the Amazon ECS console first run wizard at https://console.aws.amazon.com/ecs/home#/
firstRun.
2. By default, you are given the option to create an image repository and push an image to Amazon
ECR.
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For this tutorial, you will not use Amazon ECR, so be sure to clear the lower option. Choose Continue
to proceed.
3. On the Create a task definition page, leave all of the default options and choose Next step.
4. On the Configure service page, for Container name: host port, choose simple-app:80.
Important
Elastic Load Balancing load balancers do incur cost while they exist in your AWS resources.
For more information, see Elastic Load Balancing Pricing.
5. For Select IAM role for service, choose an existing Amazon ECS service (ecsServiceRole) role that
you have already created, or choose Create new role to create the required IAM role for your service.
6. The remaining default values here are set up for the sample application, so leave them as they are
and choose Next step.
7. On the Configure cluster page, enter the following information:
a. For Cluster name, type service-autoscaling.
b. For instance type, choose any available instance type. The default t2.micro works fine for this
tutorial.
c. For Number of instances, enter the number of instances to launch into your cluster. For the
purposes of this tutorial, two instances are sufficient.
Important
Your AWS account incurs the standard Amazon EC2 usage fees for these instances from
the time that you launch the instances until you terminate them (which is the final task
of this tutorial), even if they remain idle.
d. (Optional) For Key pair, choose a key pair to use for SSH access to your instances. This is not
required, but it can be useful for diagnostic purposes if you need to troubleshoot your instances
later.
e. For Container instance IAM role, choose an existing Amazon ECS container instance
(ecsInstanceRole) role that you have already created, or choose Create new role to create the
required IAM role for your container instances.
f. Choose Review and Launch to proceed. Review your configurations and choose Launch
instance & run service to finish.
You are directed to a Launch Status page that shows the status of your launch and describes each
step of the process (this can take a few minutes to complete while your Auto Scaling group is
created and populated).
8. When your cluster and service are created, choose View service to view your new service.
Step 2: Configure Service Auto Scaling
Now that you have launched a cluster and created a service in that cluster that is running behind a load
balancer, you can configure Service Auto Scaling by creating scaling policies to scale your service up and
down in response to CloudWatch alarms.
To configure basic Service Auto Scaling parameters
1. On the Service: sample-webapp page, your service configuration should look similar to the image
below (although the task definition revision and load balancer name will likely be different). Choose
Update to update your new service.
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2. On the Update service page, choose Configure Service Auto Scaling.
3. For Service Auto Scaling, choose Configure Service Auto Scaling to adjust your service’s desired
count.
4. For Minimum number of tasks, enter 1 for the lower limit of the number of tasks for Service Auto
Scaling to use. Your service's desired count will not be automatically adjusted below this amount.
5. For Desired number of tasks, this field is pre-populated with the value you entered earlier. This
value must be between the minimum and maximum number of tasks specified on this page. Leave
this value at 1.
6. For Maximum number of tasks, enter 2 for the upper limit of the number of tasks for Service Auto
Scaling to use. Your service's desired count will not be automatically adjusted above this amount.
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7. For IAM role for Service Auto Scaling, choose an IAM role to authorize the Application Auto Scaling
service to adjust your service's desired count on your behalf. If you have not previously created such
a role, choose Create new role and the role is created for you. For future reference, the role that is
created for you is called ecsAutoscaleRole. For more information, see Amazon ECS Service Auto
Scaling IAM Role (p. 214).
To configure scaling policies for your service
These steps will help you create scaling policies and CloudWatch alarms that can be used to trigger
scaling activities for your service. You can create a scale out alarm to increase the desired count of your
service, and a scale in alarm to decrease the desired count of your service.
1. On the Service Auto Scaling (optional) page, choose Add scaling policy to configure your
ScaleOutPolicy.
2. For Policy name, enter ScaleOutPolicy
3. For Execute policy when, choose Create new alarm.
a. For Alarm name, enter sample-webapp-cpu-gt-75.
b. For ECS service metric, choose CPUUtilization.
c. For Alarm threshold, enter the following information to match the image below. This causes
the CloudWatch alarm to trigger when the service's CPU utilization is greater than 75% for one
minute.
d. Choose Save to save your alarm.
4. For Scaling action, enter the following information to match the image below. This causes your
service's desired count to increase by 1 task when the alarm is triggered.
5. For Cooldown period, enter 60 for the number of seconds between scaling actions and choose Save
to save your ScaleOutPolicy.
6. After you return to the Service Auto Scaling (optional) page, choose Add scaling policy to
configure your ScaleInPolicy.
7. For Policy name, enter ScaleInPolicy
8. For Execute policy when, choose Create new alarm.
a. For Alarm name, enter sample-webapp-cpu-lt-25.
b. For ECS service metric, choose CPUUtilization.
c. For Alarm threshold, enter the following information to match the image below. This causes
the CloudWatch alarm to trigger when the service's CPU utilization is less than 25% for one
minute.
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d. Choose Save to save your alarm.
9. For Scaling action, enter the following information to match the image below. This causes your
service's desired count to decrease by 1 task when the alarm is triggered.
10. For Cooldown period, enter 60 for the number of seconds between scaling actions and choose Save
to save your ScaleInPolicy.
11. After you return to the Service Auto Scaling (optional) page, choose Save to finish your Service
Auto Scaling configuration.
12. On the Update Service page, choose Update Service.
13. When your service status is finished updating, choose View Service.
Step 3: Trigger a Scaling Activity
After your service is configured with Service Auto Scaling, you can trigger a scaling activity by pushing
your service's CPU utilization into the ALARM state. Because the example in this tutorial is a web
application that is running behind a load balancer, you can send thousands of HTTP requests to your
service (using the ApacheBench utility) to spike the service CPU utilization above our threshold amount.
This spike should trigger the alarm, which in turn triggers a scaling activity to add one task to your
service.
After the ApacheBench utility finishes the requests, the service CPU utilization should drop below your
25% threshold, triggering a scale in activity that returns the service's desired count to 1.
To trigger a scaling activity for your service
1. From your service's main view page in the console, choose the load balancer name to view its details
in the Amazon EC2 console. You need the load balancer's DNS name, which should look something
like this: EC2Contai-EcsElast-SMAKV74U23PH-96652279.us-east-1.elb.amazonaws.com.
2. Use the ApacheBench (ab) utility to make thousands of HTTP requests to your load balancer in a
short period of time.
Note
This command is installed by default on Mac OSX, and it is available for many Linux
distributions, as well. For example, you can install ab on Amazon Linux with the following
command:
$ sudo yum install -y httpd24-tools
Run the following command, substituting your load balancer's DNS name.
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$ ab -n 100000 -c 1000 http://EC2Contai-EcsElast-SMAKV74U23PH-96652279.us-
east-1.elb.amazonaws.com/
3. Open the CloudWatch console at https://console.aws.amazon.com/cloudwatch/.
4. Choose Alarms in the left navigation pane.
5. Wait for your ab HTTP requests to trigger the scale out alarm in the CloudWatch console. You should
see your Amazon ECS service scale out and add 1 task to your service's desired count.
6. Shortly after your ab HTTP requests complete (between 1 and 2 minutes), your scale in alarm should
trigger and the scale in policy reduces your service's desired count back to 1.
Step 4: Cleaning Up
When you have completed this tutorial, you may choose to keep your cluster, Auto Scaling group, load
balancer, and EC2 instances. However, if you are not actively using these resources, you should consider
cleaning them up so that your account does not incur unnecessary charges.
To delete your cluster and CloudWatch alarms
1. In the Amazon ECS console, switch to Clusters in the left navigation pane.
2. On the Clusters page, choose the x in the upper right hand corner of the service-autoscaling cluster
to delete the cluster.
3. Review and choose Delete to confirm your cluster deletion. It may take a few minutes for the cluster
AWS CloudFormation stack to finish cleaning up.
4. In the CloudWatch console Alarms view, select the alarms that begin with sample-webapp-cpu- and
then choose Delete to delete the alarms.
5. Choose Yes, Delete to confirm your alarm deletion.
Creating a Service
When you create an Amazon ECS service, you specify the basic parameters that define what makes up
your service and how it should behave. These parameters create a service definition.
You can optionally configure additional features, such as an Elastic Load Balancing load balancer
to distribute traffic across the containers in your service, For more information, see Service Load
Balancing (p. 141). You must verify that your container instances can receive traffic from your load
balancers. You can allow traffic to all ports on your container instances from your load balancer's security
group to ensure that traffic can reach any containers that use dynamically assigned ports.
Configuring Basic Service Parameters
All services require some basic configuration parameters that define the service, such as the task
definition to use, which cluster the service should run on, how many tasks should be placed for the
service, and so on; this is called the service definition. For more information about the parameters
defined in a service definition, see Service Definition Parameters (p. 139).
This procedure covers creating a service with the basic service definition parameters that are required.
After you have configured these parameters, you can create your service or move on to the procedures
for optional service definition configuration, such as configuring your service to use a load balancer.
To configure the basic service definition parameters
1. Open the Amazon ECS console at https://console.aws.amazon.com/ecs/.
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2. On the navigation bar, select the region that your cluster is in.
3. In the navigation pane, choose Task Definitions and select the task definition from which to create
your service.
4. On the Task Definition name page, select the revision of the task definition from which to create
your service.
5. Review the task definition, and choose Create Service.
6. On the Create Service page, for Cluster, select the cluster in which to create your service. For
Service name, type a unique name for your service. For Number of tasks, type the number of tasks
to launch and maintain on your cluster. If your task definition uses static host port mappings on your
container instances, then you need at least one container instance with the specified port available
in your cluster for each task in your service. This restriction does not apply if your task definition
uses dynamic host port mappings. For more information, see portMappings (p. 100).
7. (Optional) You can specify deployment parameters that control how many tasks run during the
deployment and the ordering of stopping and starting tasks.
•Minimum healthy percent: Specify a lower limit on the number of your service's tasks that must
remain in the RUNNING state during a deployment, as a percentage of the service's desired number
of tasks (rounded up to the nearest integer). For example, if your service has a desired number of
four tasks and a minimum healthy percent of 50%, the scheduler may stop two existing tasks to
free up cluster capacity before starting two new tasks. Tasks for services that do not use a load
balancer are considered healthy if they are in the RUNNING state; tasks for services that do use a
load balancer are considered healthy if they are in the RUNNING state and the container instance it
is hosted on is reported as healthy by the load balancer. The default value for minimum healthy
percent is 50% in the console, and 100% with the AWS CLI or SDKs.
•Maximum percent: Specify an upper limit on the number of your service's tasks that are allowed
in the RUNNING or PENDING state during a deployment, as a percentage of the service's desired
number of tasks (rounded down to the nearest integer). For example, if your service has a desired
number of four tasks and a maximum percent value of 200%, the scheduler may start four new
tasks before stopping the four older tasks (provided that the cluster resources required to do this
are available). The default value for maximum percent is 200%.
8. (Optional) For Task Placement, you can specify how tasks are placed using task placement strategies
and constraints. Choose from the following options:
•AZ Balanced Spread - distribute tasks across Availability Zones and across container instances in
the Availability Zone.
•AZ Balanced BinPack - distribute tasks across Availability Zones and across container instances
with the least available memory.
•BinPack - distribute tasks based on the least available amount of CPU or memory.
•One Task Per Host - place, at most, one task from the service on each container instance.
•Custom - define your own task placement strategy. See Amazon ECS Task Placement (p. 128) for
examples.
For more information, see Amazon ECS Task Placement (p. 128).
(Optional) Configuring Your Service to Use a Load
Balancer
If you have an available Elastic Load Balancing load balancer configured, you can attach it to your service
with the following procedures, or you can configure a new load balancer. For more information see
Creating a Load Balancer (p. 145).
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Note
You must create your Elastic Load Balancing load balancer resources prior to following these
procedures.
First, you must choose the load balancer type to use with your service. Then you can configure your
service to work with the load balancer.
To choose a load balancer type
1. If you have not done so already, follow the basic service creation procedures in Configuring Basic
Service Parameters (p. 160).
2. On the Create Service page, choose Configure ELB.
3. Choose the load balancer type to use with your service:
Application Load Balancer
Allows containers to use dynamic host port mapping (multiple tasks allowed per container
instance). Multiple services can use the same listener port on a single load balancer with rule-
based routing and paths.
Classic Load Balancer
Requires static host port mappings (only one task allowed per container instance); rule-based
routing and paths are not supported.
We recommend that you use Application Load Balancers for your Amazon ECS services so that you
can take advantage of the advanced features available to them.
4. For Select IAM role for service, choose Create new role to create a new role for your service, or
select an existing IAM role to use for your service (by default, this is ecsServiceRole).
Important
If you choose to use an existing ecsServiceRole IAM role, you must verify that the role has
the proper permissions to use Application Load Balancers and Classic Load Balancers, as
shown in Amazon ECS Service Scheduler IAM Role (p. 212).
5. For ELB Name, choose the name of the load balancer to use with your service. Only load balancers
that correspond to the load balancer type you selected earlier are visible here.
6. The following steps differ based on the load balancer type for your service. If you've chosen an
Application Load Balancer, follow the steps in To configure an Application Load Balancer (p. 162).
If you've chosen a Classic Load Balancer, follow the steps in To configure a Classic Load
Balancer (p. 163).
To configure an Application Load Balancer
1. For Select a Container, choose the container and port combination from your task definition that
your load balancer should distribute traffic to, and choose Add to ELB.
2. For Listener port, choose the listener port and protocol of the listener that you created in Creating
an Application Load Balancer (p. 146) (if applicable), or choose create new to create a new listener
and then enter a port number and choose a port protocol in Listener protocol.
3. For Target group name, choose the target group that you created in Creating an Application Load
Balancer (p. 146) (if applicable), or choose create new to create a new target group.
4. (Optional) If you chose to create a new target group, complete the following fields as follows:
• For Target group name, enter a name for your target group.
• For Target group protocol, enter the protocol to use for routing traffic to your tasks.
• For Path pattern, if your listener does not have any existing rules, the default path pattern (/) is
used. If your listener already has a default rule, then you must enter a path pattern that matches
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traffic that you want to have sent to your service's target group. For example, if your service is a
web application called web-app, and you want traffic that matches http://my-elb-url/web-app to
route to your service, then you would enter /web-app* as your path pattern. For more information,
see ListenerRules in the Application Load Balancer Guide.
• For Health check path, enter the path to which the load balancer should send health check pings.
5. When you are finished configuring your Application Load Balancer, choose Save to save your
configuration and proceed to Review and Create Your Service (p. 165).
To configure a Classic Load Balancer
1. The Health check port, Health check protocol, and Health check path fields are all pre-populated
with the values you configured in Creating a Classic Load Balancer (p. 149) (if applicable). You can
update these settings in the Amazon EC2 console.
2. For Container for ELB health check, choose the container to send health checks.
3. When you are finished configuring your Classic Load Balancer, choose Save to save your
configuration and proceed to Review and Create Your Service (p. 165).
(Optional) Configuring Your Service to Use Service
Auto Scaling
Your Amazon ECS service can optionally be configured to use Auto Scaling to adjust its desired count up
or down in response to CloudWatch alarms. For more information see Service Auto Scaling (p. 152).
To configure basic Service Auto Scaling parameters
1. If you have not done so already, follow the basic service creation procedures in Configuring Basic
Service Parameters (p. 160).
2. On the Create Service page, choose Configure Service Auto Scaling.
3. On the Service Auto Scaling page, select Configure Service Auto Scaling to adjust your service’s
desired count.
4. For Minimum number of tasks, enter the lower limit of the number of tasks for Service Auto Scaling
to use. Your service's desired count will not be automatically adjusted below this amount.
5. For Desired number of tasks, this field is pre-populated with the value you entered earlier. You can
change your service's desired count at this time, but this value must be between the minimum and
maximum number of tasks specified on this page.
6. For Maximum number of tasks, enter the upper limit of the number of tasks for Service Auto
Scaling to use. Your service's desired count will not be automatically adjusted above this amount.
7. For IAM role for Service Auto Scaling, choose an IAM role to authorize the Application Auto Scaling
service to adjust your service's desired count on your behalf. If you have not previously created such
a role, choose Create new role and the role will be created for you. For future reference, the role
that is created for you is called ecsAutoscaleRole. For more information, see Amazon ECS Service
Auto Scaling IAM Role (p. 214).
To configure scaling policies for your service
These steps will help you create scaling policies and CloudWatch alarms that can be used to trigger
scaling activities for your service. You can create a Scale out alarm to increase the desired count of your
service, and a Scale in alarm to decrease the desired count of your service.
1. For Policy name, enter a descriptive name for your policy, or use the default policy name that is
already entered.
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2. For Execute policy when, select the CloudWatch alarm that you want to use to scale your service up
or down.
You can use an existing CloudWatch alarm that you have previously created, or you can choose to
create a new alarm. The Create new alarm workflow allows you to create CloudWatch alarms that
are based on the CPUUtilization and MemoryUtilization of the service that you are creating. To
use other metrics, you can create your alarm in the CloudWatch console and then return to this
wizard to choose that alarm.
3. (Optional) If you've chosen to create a new alarm, complete the following steps.
a. For Alarm name, enter a descriptive name for your alarm. For example, if your alarm should
trigger when your service CPU utilization exceeds 75%, you could call the alarm service_name-
cpu-gt-75.
b. For ECS service metric, choose the service metric to use for your alarm. For more information
about these service utilization metrics, see Service Utilization (p. 177).
c. For Alarm threshold, enter the following information to configure your alarm:
• Choose the CloudWatch statistic for your alarm (the default value of Average works in many
cases). For more information, see Statistics in the Amazon CloudWatch User Guide.
• Choose the comparison operator for your alarm and enter the value that the comparison
operator checks against (for example, > and 75).
• Enter the number of consecutive periods before the alarm is triggered and the period length.
For example, a 2 consecutive periods of 5 minutes would take 10 minutes before the alarm
triggered. Because your Amazon ECS tasks can scale up and down quickly, you should consider
using a low number of consecutive periods and a short period duration to react to alarms as
soon as possible.
d. Choose Save to save your alarm.
4. For Scaling action, enter the following information to configure how your service responds to the
alarm:
• Choose whether to add to, subtract from, or set a specific desired count for your service.
• If you chose to add or subtract tasks, enter the number of tasks (or percent of existing tasks) to
add or subtract when the scaling action is triggered. If you chose to set the desired count, enter
the desired count that your service should be set to when the scaling action is triggered.
• (Optional) If you chose to add or subtract tasks, choose whether the previous value is used as an
integer or a percent value of the existing desired count.
• Enter the lower boundary of your step scaling adjustment. By default, for your first scaling action,
this value is the metric amount where your alarm is triggered. For example, the following scaling
action adds 100% of the existing desired count when the CPU utilization is greater than 75%.
5. (Optional) You can repeat Step 4 (p. 164) to configure multiple scaling actions for a single
alarm (for example, to add 1 task if CPU utilization is between 75-85%, and to add 2 tasks if CPU
utilization is greater than 85%).
6. (Optional) If you chose to add or subtract a percentage of the existing desired count, enter a
minimum increment value for Add tasks in increments of N task(s).
7. For Cooldown period, enter the number of seconds between scaling actions.
8. Repeat Step 1 (p. 163) through Step 7 (p. 164) for the Scale in policy and choose Save to save
your Service Auto Scaling configuration.
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Review and Create Your Service
After you have configured your basic service definition parameters and optionally configured your
service to use a load balancer, you can review your configuration and then choose Create Service to
finish creating your service.
Note
After you create a service, the target group ARN or load balancer name, container name, and
container port specified in the service definition are immutable. You cannot add, remove, or
change the load balancer configuration of an existing service. If you update the task definition
for the service, the container name and container port that were specified when the service was
created must remain in the task definition.
Updating a Service
You can update a running service to change the number of tasks that are maintained by a service or
which task definition is used by the tasks. If you have an application that needs more capacity, you can
scale up your service to use more of your container instances (as long as they are available). If you have
unused capacity that you would like to scale down, you can reduce the number of desired tasks in your
service and free up resources.
If you have updated the Docker image of your application, you can create a new task definition with
that image and deploy it to your service. The service scheduler uses the minimum healthy percent and
maximum percent parameters (in the service's deployment configuration) to determine the deployment
strategy.
The minimum healthy percent represents a lower limit on the number of your service's tasks that must
remain in the RUNNING state during a deployment, as a percentage of the desired number of tasks
(rounded up to the nearest integer). This parameter enables you to deploy without using additional
cluster capacity. For example, if your service has a desired number of four tasks and a minimum healthy
percent of 50%, the scheduler may stop two existing tasks to free up cluster capacity before starting
two new tasks. Tasks for services that do not use a load balancer are considered healthy if they are in
the RUNNING state; tasks for services that do use a load balancer are considered healthy if they are in the
RUNNING state and the container instance it is hosted on is reported as healthy by the load balancer. The
default value for minimum healthy percent is 50% in the console and 100% for the AWS CLI, the AWS
SDKs, and the APIs.
The maximum percent parameter represents an upper limit on the number of your service's tasks that
are allowed in the RUNNING or PENDING state during a deployment, as a percentage of the desired number
of tasks (rounded down to the nearest integer). This parameter enables you to define the deployment
batch size. For example, if your service has a desired number of four tasks and a maximum percent value
of 200%, the scheduler may start four new tasks before stopping the four older tasks (provided that the
cluster resources required to do this are available). The default value for maximum percent is 200%.
When the service scheduler replaces a task during an update, if a load balancer is used by the service,
the service first removes the task from the load balancer and waits for the connections to drain. Then
the equivalent of docker stop is issued to the containers running in the task. This results in a SIGTERM
signal and a 30-second timeout, after which SIGKILL is sent and the containers are forcibly stopped. If
the container handles the SIGTERM signal gracefully and exits within 30 seconds from receiving it, no
SIGKILL signal is sent. The service scheduler starts and stops tasks as defined by your minimum healthy
percent and maximum percent settings.
Important
If you are changing the ports used by containers in a task definition, you may need to update
your container instance security groups to work with the updated ports.
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Deleting a Service
If your service uses a load balancer, the load balancer configuration defined for your service
when it was created cannot be changed. If you update the task definition for the service, the
container name and container port that were specified when the service was created must
remain in the task definition.
To change the load balancer name, the container name, or the container port associated with a
service load balancer configuration, you must create a new service.
Amazon ECS does not automatically update the security groups associated with Elastic Load
Balancing load balancers or Amazon ECS container instances.
To update a running service
1. Open the Amazon ECS console at https://console.aws.amazon.com/ecs/.
2. On the navigation bar, select the region that your cluster is in.
3. In the navigation pane, choose Clusters.
4. On the Clusters page, select the name of the cluster that your service resides in.
5. On the Cluster: name page, choose Services.
6. Check the box to the left of the service to update and choose Update.
7. On the Update Service page, your service information is pre-populated. Change the task definition,
deployment configuration, or number of desired tasks (or any combination of these).
8. (Optional) You can use Service Auto Scaling to scale your service up and down automatically in
response to CloudWatch alarms.
a. Under Optional configurations, choose Configure Service Auto Scaling.
b. Proceed to Step 3 (p. 163) of (Optional) Configuring Your Service to Use Service Auto
Scaling (p. 163).
c. Complete the steps in that section and then return here.
9. Choose Update Service to finish and update your service.
Deleting a Service
You can delete a service if you have no running tasks in it and the desired task count is zero. If the service
is actively maintaining tasks, you cannot delete it, and you must update the service to a desired task
count of zero. For more information, see Updating a Service (p. 165).
Note
When you delete a service, if there are still running tasks that require cleanup, the service
status moves from ACTIVE to DRAINING, and the service is no longer visible in the console or
in ListServices API operations. After the tasks have stopped, then the service status moves
from DRAINING to INACTIVE. Services in the DRAINING or INACTIVE status can still be viewed with
DescribeServices API operations; however, in the future, INACTIVE services may be cleaned up
and purged from Amazon ECS record keeping, and DescribeServices API operations on those
services will return a ServiceNotFoundException error.
Use the following procedure to delete an empty service.
To delete an empty service
1. Open the Amazon ECS console at https://console.aws.amazon.com/ecs/.
2. On the navigation bar, select the region that your cluster is in.
3. In the navigation pane, choose Clusters.
4. On the Clusters page, select the name of the cluster that your service resides in.
5. On the Cluster : name page, choose Services.
6. Check the box to the left of the service to update and choose Delete.
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Note
Your service must have zero desired or running tasks before it can be deleted.
7. Choose Yes, Delete to confirm your service deletion.
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Amazon ECR Repositories
Amazon ECR is a managed AWS Docker registry service. Customers can use the familiar Docker CLI to
push, pull, and manage images. Amazon ECR provides a secure, scalable, and reliable registry. Amazon
ECR supports private Docker repositories with resource-based permissions using AWS IAM so that specific
users or Amazon EC2 instances can access repositories and images. Developers can use the Docker CLI to
author and manage images.
Note
Amazon ECR is available in the following regions:
Region Name Region
US East (N. Virginia) us-east-1
US East (Ohio) us-east-2
US West (N.
California)
us-west-1
US West (Oregon) us-west-2
EU (Ireland) eu-west-1
EU (London) eu-west-2
EU (Frankfurt) eu-central-1
Asia Pacific (Tokyo) ap-northeast-1
Asia Pacific
(Singapore)
ap-southeast-1
Asia Pacific (Sydney) ap-southeast-2
Canada (Central) ca-central-1
For more information on how to create repositories, push and pull images from Amazon ECR, and set
access controls on your repositories, see the Amazon EC2 Container Registry User Guide.
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Using Amazon ECR Images with Amazon ECS
You can use your ECR images with Amazon ECS, but you need to satisfy some prerequisites:
• Your container instances must be using at least version 1.7.0 of the Amazon ECS container agent. The
latest version of the Amazon ECS–optimized AMI supports ECR images in task definitions. For more
information, including the latest Amazon ECS–optimized AMI IDs, see Amazon ECS Container Agent
Versions (p. 71).
• The Amazon ECS container instance role (ecsInstanceRole) that you use with your container instances
must possess the following IAM policy permissions for Amazon ECR.
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Action": [
"ecr:BatchCheckLayerAvailability",
"ecr:BatchGetImage",
"ecr:GetDownloadUrlForLayer",
"ecr:GetAuthorizationToken"
],
"Resource": "*"
}
]
}
If you use the AmazonEC2ContainerServiceforEC2Role managed policy for your container instances,
then your role has the proper permissions. To check that your role supports Amazon ECR, see Amazon
ECS Container Instance IAM Role (p. 210).
• In your ECS task definitions, make sure that you are using the full registry/repository:tag naming
for your ECR images. For example, aws_account_id.dkr.ecr.region.amazonaws.com/my-web-
app:latest.
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Monitoring Amazon ECS
You can monitor your Amazon ECS resources using Amazon CloudWatch, which collects and processes
raw data from Amazon ECS into readable, near real-time metrics. These statistics are recorded for a
period of two weeks, so that you can access historical information and gain a better perspective on how
your clusters or services are performing. Amazon ECS metric data is automatically sent to CloudWatch in
1-minute periods. For more information about CloudWatch, see the Amazon CloudWatch User Guide.
Monitoring is an important part of maintaining the reliability, availability, and performance of Amazon
ECS and your AWS solutions. You should collect monitoring data from all of the parts of your AWS
solution so that you can more easily debug a multi-point failure if one occurs. Before you start
monitoring Amazon ECS; however, you should create a monitoring plan that includes answers to the
following questions:
• What are your monitoring goals?
• What resources will you monitor?
• How often will you monitor these resources?
• What monitoring tools will you use?
• Who will perform the monitoring tasks?
• Who should be notified when something goes wrong?
The next step is to establish a baseline for normal Amazon ECS performance in your environment, by
measuring performance at various times and under different load conditions. As you monitor Amazon
ECS, store historical monitoring data so that you can compare it with current performance data, identify
normal performance patterns and performance anomalies, and devise methods to address issues.
To establish a baseline, you should, at a minimum, monitor the following items:
• The CPU and memory reservation and utilization metrics for your Amazon ECS clusters.
• The CPU and memory utilization metrics for your Amazon ECS services.
Topics
•Monitoring Tools (p. 171)
•Amazon ECS CloudWatch Metrics (p. 172)
•Amazon ECS Event Stream for CloudWatch Events (p. 187)
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Monitoring Tools
AWS provides various tools that you can use to monitor Amazon ECS. You can configure some of these
tools to do the monitoring for you, while some of the tools require manual intervention. We recommend
that you automate monitoring tasks as much as possible.
Automated Monitoring Tools
You can use the following automated monitoring tools to watch Amazon ECS and report when
something is wrong:
• Amazon CloudWatch alarms – Watch a single metric over a time period that you specify, and perform
one or more actions based on the value of the metric relative to a given threshold over a number of
time periods. The action is a notification sent to an Amazon Simple Notification Service (Amazon SNS)
topic or Auto Scaling policy. CloudWatch alarms do not invoke actions simply because they are in a
particular state; the state must have changed and been maintained for a specified number of periods.
For more information, see Amazon ECS CloudWatch Metrics (p. 172).
You can use CloudWatch alarms to scale in and scale out the container instances based on CloudWatch
metrics, such as cluster memory reservation. For more information, see Tutorial: Scaling Container
Instances with CloudWatch Alarms (p. 182)
• Amazon CloudWatch Logs – Monitor, store, and access the operating system and Amazon ECS
container agent log files from your Amazon ECS container instances. For more information, see Using
CloudWatch Logs with Container Instances (p. 52).
You can also monitor, store, and access the log files from the containers in your Amazon ECS tasks by
specifying the awslogs log driver in your task definitions. For more information, see Using the awslogs
Log Driver (p. 117).
• Amazon CloudWatch Events – Match events and route them to one or more target functions or
streams to make changes, capture state information, and take corrective action. For more information,
see Amazon ECS Event Stream for CloudWatch Events (p. 187) in this guide and Using Events in the
Amazon CloudWatch User Guide.
• AWS CloudTrail log monitoring – Share log files between accounts, monitor CloudTrail log files in real
time by sending them to CloudWatch Logs, write log processing applications in Java, and validate
that your log files have not changed after delivery by CloudTrail. For more information, see Logging
Amazon ECS API Calls By Using AWS CloudTrail (p. 271) in this guide, and Working with CloudTrail
Log Files in the AWS CloudTrail User Guide.
Manual Monitoring Tools
Another important part of monitoring Amazon ECS involves manually monitoring those items that the
CloudWatch alarms don't cover. The CloudWatch, Trusted Advisor, and other AWS console dashboards
provide an at-a-glance view of the state of your AWS environment. We recommend that you also check
the log files on your container instances and the containers in your tasks.
• CloudWatch home page:
• Current alarms and status
• Graphs of alarms and resources
• Service health status
In addition, you can use CloudWatch to do the following:
• Create customized dashboards to monitor the services you care about
• Graph metric data to troubleshoot issues and discover trends
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• Search and browse all your AWS resource metrics
• Create and edit alarms to be notified of problems
• AWS Trusted Advisor can help you monitor your AWS resources to improve performance, reliability,
security, and cost effectiveness. Four Trusted Advisor checks are available to all users; more than 50
checks are available to users with a Business or Enterprise support plan. For more information, see
AWS Trusted Advisor.
Amazon ECS CloudWatch Metrics
You can monitor your Amazon ECS resources using Amazon CloudWatch, which collects and processes
raw data from Amazon ECS into readable, near real-time metrics. These statistics are recorded for a
period of two weeks, so that you can access historical information and gain a better perspective on how
your clusters or services are performing. Amazon ECS metric data is automatically sent to CloudWatch in
1-minute periods. For more information about CloudWatch, see the Amazon CloudWatch User Guide.
Topics
•Enabling CloudWatch Metrics (p. 172)
•Available Metrics and Dimensions (p. 172)
•Cluster Reservation (p. 175)
•Cluster Utilization (p. 176)
•Service Utilization (p. 177)
•Service RUNNING Task Count (p. 177)
•Viewing Amazon ECS Metrics (p. 178)
•Tutorial: Scaling Container Instances with CloudWatch Alarms (p. 182)
Enabling CloudWatch Metrics
Your Amazon ECS container instances require at least version 1.4.0 of the container agent to enable
CloudWatch metrics; however, we recommend using the latest container agent version. For information
about checking your agent version and updating to the latest version, see Updating the Amazon ECS
Container Agent (p. 73).
If you are starting your agent manually (for example, if you are not using the Amazon ECS-optimized AMI
for your container instances), be sure to add volume mounts for the cgroup virtual file system and the
execdriver path. For more information about an example run command with these volume mounts, see
Manually Updating the Amazon ECS Container Agent (for Non-Amazon ECS-optimized AMIs) (p. 77).
Your Amazon ECS container instances also require ecs:StartTelemetrySession permission on the
IAM role that you launch your container instances with. If you created your Amazon ECS container
instance role before CloudWatch metrics were available for Amazon ECS, then you might need to add
this permission. For information about checking your Amazon ECS container instance role and attaching
the managed IAM policy for container instances, see To check for the ecsInstanceRole in the IAM
console (p. 211).
Note
You can disable CloudWatch metrics collection by setting ECS_DISABLE_METRICS=true in your
Amazon ECS container agent configuration. For more information, see Amazon ECS Container
Agent Configuration (p. 79).
Available Metrics and Dimensions
The metrics and dimensions that Amazon ECS sends to Amazon CloudWatch are listed below.
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Amazon ECS Metrics
Amazon ECS provides metrics for you to monitor the CPU and memory reservation and utilization across
your cluster as a whole, and the CPU and memory utilization on the services in your clusters.
Amazon ECS sends the following metrics to CloudWatch every minute. When Amazon ECS collects
metrics, it collects multiple data points per customer instance per minute. It then aggregates them to
one data point before sending the data to CloudWatch. So in CloudWatch, one sample count is actually
the aggregate of multiple data points per instance during one minute.
Metric Description
CPUReservation The percentage of CPU units that are reserved by
running tasks in the cluster.
Cluster CPU reservation (this metric can only be filtered
by ClusterName) is measured as the total CPU units
that are reserved by Amazon ECS tasks on the cluster,
divided by the total CPU units that were registered for
all of the container instances in the cluster.
Valid Dimensions: ClusterName, ServiceName
Valid Statistics: Average, Minimum, Maximum, Sum,
Data Samples.
Unit: Percent
CPUUtilization The percentage of CPU units that are used in the cluster
or service.
Cluster CPU utilization (metrics that are filtered by
ClusterName without ServiceName) is measured as
the total CPU units in use by Amazon ECS tasks on
the cluster, divided by the total CPU units that were
registered for all of the container instances in the
cluster.
Service CPU utilization (metrics that are filtered by
ClusterName and ServiceName) is measured as the
total CPU units in use by the tasks that belong to the
service, divided by the total number of CPU units that
are reserved for the tasks that belong to the service.
Valid Dimensions: ClusterName, ServiceName
Valid Statistics: Average, Minimum, Maximum, Sum,
Data Samples.
Unit: Percent
MemoryReservation The percentage of memory that is reserved by running
tasks in the cluster.
Cluster memory reservation (this metric can only
be filtered by ClusterName) is measured as the total
memory that is reserved by Amazon ECS tasks on the
cluster, divided by the total amount of memory that
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Metric Description
was registered for all of the container instances in the
cluster.
Valid Dimensions: ClusterName, ServiceName
Valid Statistics: Average, Minimum, Maximum, Sum,
Data Samples.
Unit: Percent
MemoryUtilization The percentage of memory that is used in the cluster or
service.
Cluster memory utilization (metrics that are filtered
by ClusterName without ServiceName) is measured as
the total memory in use by Amazon ECS tasks on the
cluster, divided by the total amount of memory that
was registered for all of the container instances in the
cluster.
Service memory utilization (metrics that are filtered by
ClusterName and ServiceName) is measured as the total
memory in use by the tasks that belong to the service,
divided by the total memory that is reserved for the
tasks that belong to the service.
Valid Dimensions: ClusterName, ServiceName
Valid Statistics: Average, Minimum, Maximum, Sum,
Data Samples.
Unit: Percent
Note
On Linux instances, the Amazon ECS container agent relies on Linux cgroup metrics to gather
CPU and memory data for each container running on the instance. If you are using an Amazon
ECS agent prior to version 1.14.0, ECS includes filesystem cache usage when reporting memory
utilization to CloudWatch so your CloudWatch graphs show a higher than actual memory
utilization for tasks. To remediate this, starting with Amazon ECS agent version 1.14.0, the
Amazon ECS container agent excludes the filesystem cache usage from the memory utilization
metric. This change does not impact the out-of-memory behavior of containers.
Dimensions for Amazon ECS Metrics
Amazon ECS metrics use the AWS/ECS namespace and provide metrics for the following dimensions:
Dimension Description
ClusterName This dimension filters the data you request for all
resources in a specified cluster. All Amazon ECS metrics
are filtered by ClusterName.
ServiceName This dimension filters the data you request for all
resources in a specified service within a specified cluster.
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Cluster Reservation
Cluster Reservation
Cluster reservation metrics are measured as the percentage of CPU and memory that is reserved by all
Amazon ECS tasks on a cluster when compared to the aggregate CPU and memory that was registered
for each active container instance in the cluster.
(Total CPU units reserved by tasks in cluster) x 100
Cluster CPU reservation = --------------------------------------------------------------
(Total CPU units registered by container instances in cluster)
(Total MiB of memory reserved by tasks in cluster x
100)
Cluster memory reservation =
------------------------------------------------------------------
(Total MiB of memory registered by container instances in
cluster)
When you run a task in a cluster, Amazon ECS parses its task definition and reserves the aggregate
CPU units and MiB of memory that is specified in its container definitions. Each minute, Amazon ECS
calculates the number of CPU units and MiB of memory that are currently reserved for each task that is
running in the cluster. The total amount of CPU and memory reserved for all tasks running on the cluster
is calculated, and those numbers are reported to CloudWatch as a percentage of the total registered
resources for the cluster.
For example, a cluster has two active container instances registered, a c4.4xlarge instance and a
c4.large instance. The c4.4xlarge instance registers into the cluster with 16,384 CPU units and 30,158
MiB of memory. The c4.large instance registers with 2,048 CPU units and 3,768 MiB of memory. The
aggregate resources of this cluster are 18,432 CPU units and 33,926 MiB of memory.
If a task definition reserves 1,024 CPU units and 2,048 MiB of memory, and ten tasks are started with
this task definition on this cluster (and no other tasks are currently running), a total of 10,240 CPU units
and 20,480 MiB of memory are reserved, which is reported to CloudWatch as 55% CPU reservation and
60% memory reservation for the cluster.
The illustration below shows the total registered CPU units in a cluster and what their reservation and
utilization means to existing tasks and new task placement. The lower (Reserved, utilized) and center
(Reserved, not utilized) blocks represent the total CPU units that are reserved for the existing tasks
that are running on the cluster, or the CPUReservation CloudWatch metric. The lower block represents
the reserved CPU units that the running tasks are actually using on the cluster, or the CPUUtilization
CloudWatch metric. The upper block represents CPU units that are not reserved by existing tasks; these
CPU units are available for new task placement. Existing tasks can utilize these unreserved CPU units as
well, if their need for CPU resources increases. For more information, see the cpu (p. 102) task definition
parameter documentation.
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Cluster Utilization
Cluster utilization is measured as the percentage of CPU and memory that is used by all Amazon ECS
tasks on a cluster when compared to the aggregate CPU and memory that was registered for each active
container instance in the cluster.
(Total CPU units used by tasks in cluster) x 100
Cluster CPU utilization = --------------------------------------------------------------
(Total CPU units registered by container instances in cluster)
(Total MiB of memory used by tasks in cluster x 100)
Cluster memory utilization =
------------------------------------------------------------------
(Total MiB of memory registered by container instances in
cluster)
Each minute, the Amazon ECS container agent on each container instance calculates the number of CPU
units and MiB of memory that are currently being used for each task that is running on that container
instance, and this information is reported back to Amazon ECS. The total amount of CPU and memory
used for all tasks running on the cluster is calculated, and those numbers are reported to CloudWatch as
a percentage of the total registered resources for the cluster.
For example, a cluster has two active container instances registered, a c4.4xlarge instance and a
c4.large instance. The c4.4xlarge instance registers into the cluster with 16,384 CPU units and 30,158
MiB of memory. The c4.large instance registers with 2,048 CPU units and 3,768 MiB of memory. The
aggregate resources of this cluster are 18,432 CPU units and 33,926 MiB of memory.
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Service Utilization
If ten tasks are running on this cluster that each consume 1,024 CPU units and 2,048 MiB of memory,
a total of 10,240 CPU units and 20,480 MiB of memory are utilized on the cluster, which is reported to
CloudWatch as 55% CPU utilization and 60% memory utilization for the cluster.
Service Utilization
Service utilization is measured as the percentage of CPU and memory that is used by the Amazon ECS
tasks that belong to a service on a cluster when compared to the CPU and memory that is defined in the
service's task definition.
(Total CPU units used by tasks in service) x 100
Service CPU utilization =
----------------------------------------------------------------------------
(Total CPU units reserved in task definition) x (number of tasks
in service)
(Total MiB of memory used by tasks in service) x
100
Service memory utilization =
--------------------------------------------------------------------------------
(Total MiB of memory reserved in task definition) x (number
of tasks in service)
Each minute, the Amazon ECS container agent on each container instance calculates the number of CPU
units and MiB of memory that are currently being used for each task owned by the service that is running
on that container instance, and this information is reported back to Amazon ECS. The total amount of
CPU and memory used for all tasks owned by the service that are running on the cluster is calculated,
and those numbers are reported to CloudWatch as a percentage of the total resources that are reserved
for the service in the service's task definition. If you specify a soft limit (memoryReservation), then it will
be used to calculate the amount of reserved memory. Otherwise, the hard limit (memory) is used. For
more information about hard and soft limits, see Task Definition Parameters.
For example, the task definition for a service reserves a total of 512 CPU units and 1,024 MiB of memory
for all of its containers. The service has a desired count of 1 running task, the service is running on a
cluster with 1 c4.large container instance (with 2,048 CPU units and 3,768 MiB of memory), and there
are no other tasks running on the cluster. Although the task has 512 CPU units reserved, because it is the
only running task on a container instance with 2,048 CPU units, it has the ability to use up to four times
the reserved amount (2,048 / 512); however, the memory reservation of 1,024 MiB is a hard limit and it
cannot be exceeded, so service memory utilization cannot exceed 100%.
If this task is performing CPU-intensive work during a period and using all 2,048 of the available
CPU units and 512 MiB of memory, then the service reports 400% CPU utilization and 50% memory
utilization. If the task is idle and using 128 CPU units and 128 MiB of memory, then the service reports
25% CPU utilization and 12.5% memory utilization.
Service RUNNING Task Count
You can use CloudWatch metrics to view the number of tasks in your services that are in the RUNNING
state. For example, you can set a CloudWatch alarm for this metric to alert you if the number of running
tasks in your service falls below a specified value.
To view the number of running tasks in a service
1. Open the CloudWatch console at https://console.aws.amazon.com/cloudwatch/.
2. Choose Metrics section on the navigation pane.
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3. On the All metrics tab, choose ECS.
4. Choose ClusterName, ServiceName and choose any metric (either CPUUtilization or
MemoryUtilization) that corresponds to the service to view running tasks in.
5. On the Graphed metrics tab, change the Period to 1 Minute and the Statistic to Data Samples.
6. The value displayed in the graph indicates the number of RUNNING tasks in the service.
Viewing Amazon ECS Metrics
After you have enabled CloudWatch metrics for Amazon ECS, you can view those metrics in both
the Amazon ECS and CloudWatch consoles. The Amazon ECS console provides a 24-hour maximum,
minimum, and average view of your cluster and service metrics, while the CloudWatch console provides
a fine-grained and customizable display of your resources, as well as the number of running tasks in a
service.
Topics
•Viewing Cluster Metrics in the Amazon ECS Console (p. 179)
•Viewing Service Metrics in the Amazon ECS Console (p. 180)
•Viewing Amazon ECS Metrics in the CloudWatch Console (p. 181)
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Viewing Cluster Metrics in the Amazon ECS Console
Cluster and service metrics are available in the Amazon ECS console. The view provided for cluster
metrics shows the average, minimum, and maximum values for the previous 24-hour period, with
data points available in 5-minute intervals. For more information about cluster metrics, see Cluster
Reservation (p. 175) and Cluster Utilization (p. 176).
To view cluster metrics in the console
1. Open the Amazon ECS console at https://console.aws.amazon.com/ecs/.
2. Choose the cluster to view metrics with.
3. On the Cluster: cluster-name page, choose the Metrics tab to view cluster metrics.
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Viewing Service Metrics in the Amazon ECS Console
Service CPU and memory utilization metrics are available in the Amazon ECS console. The view provided
for service metrics shows the average, minimum, and maximum values for the previous 24-hour period,
with data points available in 5-minute intervals. For more information about service utilization metrics,
see Service Utilization (p. 177).
To view service metrics in the console
1. Open the Amazon ECS console at https://console.aws.amazon.com/ecs/.
2. Choose the cluster that contains the service to view metrics with.
3. On the Cluster: cluster-name page, choose the Services tab to view the services in that cluster.
4. Choose the service to view metrics with.
5. On the Service: service-name page, choose the Metrics tab to view service metrics.
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Viewing Amazon ECS Metrics in the CloudWatch Console
Amazon ECS cluster and service metrics can also be viewed in the CloudWatch console. The CloudWatch
console provides the most detailed view of Amazon ECS metrics, and you can tailor the views to
suit your needs. You can view Cluster Reservation (p. 175), Cluster Utilization (p. 176), Service
Utilization (p. 177), and the Service RUNNING Task Count (p. 177). For more information about
CloudWatch, see the Amazon CloudWatch User Guide.
To view metrics in the CloudWatch console
1. Open the CloudWatch console at https://console.aws.amazon.com/cloudwatch/.
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2. In the Metrics section in the left navigation, choose ECS.
3. Choose the metrics to view. Cluster metrics are scoped as ECS > ClusterName and service utilization
metrics are scoped as ECS > ClusterName, ServiceName. The example below shows cluster CPU and
memory utilization.
Tutorial: Scaling Container Instances with
CloudWatch Alarms
The following procedures help you to create an Auto Scaling group for an Amazon ECS cluster that you
can scale up (and down) using CloudWatch alarms.
Depending on the Amazon EC2 instance types you use in your clusters, and quantity of container
instances you have in a cluster, your tasks have a limited amount of resources that they can use when
they are run. ECS monitors the resources available in the cluster to work with the schedulers to place
tasks. If your cluster runs low on any of these resources, such as memory, you will eventually be unable
to launch more tasks until you add more container instances, reduce the number of desired tasks in a
service, or stop some of the running tasks in your cluster to free up the constrained resource.
In this tutorial, you create a CloudWatch alarm using the MemoryReservation metric for your cluster.
When the memory reservation of your cluster rises above 75% (meaning that only 25% of the memory
in your cluster is available to for new tasks to reserve), the alarm triggers the Auto Scaling group to add
another instance and provide more resources for your tasks and services.
Prerequisites
This tutorial assumes that you have enabled CloudWatch metrics for your clusters and services. Metrics
are not available until the clusters and services send the metrics to CloudWatch, and you cannot create
CloudWatch alarms for metrics that do not exist yet.
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Your Amazon ECS container instances require at least version 1.4.0 of the container agent to enable
CloudWatch metrics. For information about checking your agent version and updating to the latest
version, see Updating the Amazon ECS Container Agent (p. 73).
Your Amazon ECS container instances also require ecs:StartTelemetrySession permission on the
IAM role that you launch your container instances with. If you created your Amazon ECS container
instance role before CloudWatch metrics were available for Amazon ECS, then you might need to add
this permission. For information about checking your Amazon ECS container instance role and attaching
the managed IAM policy for container instances, see To check for the ecsInstanceRole in the IAM
console (p. 211).
Step 1: Create a CloudWatch Alarm for a Metric
After you have enabled CloudWatch metrics for your clusters and services, and the metrics for your
cluster are visible in the CloudWatch console, you can set alarms on the metrics. For more information,
see Creating Amazon CloudWatch Alarms in the Amazon CloudWatch User Guide.
For this tutorial, you create an alarm on the cluster MemoryReservation metric to alert when the cluster's
memory reservation is above 75%.
To create a CloudWatch alarm on a metric
1. Open the CloudWatch console at https://console.aws.amazon.com/cloudwatch/.
2. On the left navigation, choose Alarms.
3. Choose Create Alarm.
4. In the CloudWatch Metrics by Category section, choose ECS > ClusterName.
5. On the Modify Alarm page, choose the MemoryReservation metric for the default cluster and
choose Next.
6. In the Alarm Threshold section, enter a name and description for your alarm.
•Name: memory-above-75-pct
•Description: Cluster memory reservation above 75%
7. Set the threshold and time period requirement to MemoryReservation greater than 75% for 1
period.
8. (Optional) Configure a notification to send when the alarm is triggered. You can also choose to
delete the notification if you don't want to configure one now.
9. Choose Create Alarm. Now you can use this alarm to trigger your Auto Scaling group to add a
container instance when the memory reservation is above 75%.
10. (Optional) You can also create another alarm that triggers when the memory reservation is below
25%, which you can use to remove a container instance from your Auto Scaling group.
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Step 2: Create a Launch Configuration for an Auto Scaling
Group
Now that you have enabled CloudWatch metrics and created an alarm based on one of those metrics,
you can create a launch configuration and an Auto Scaling group for your cluster. For more information
and other configuration options, see the Auto Scaling User Guide.
To create an Auto Scaling launch configuration
1. Open the Amazon EC2 console at https://console.aws.amazon.com/ec2/.
2. On the left navigation, choose Auto Scaling Groups.
3. On the Welcome to Auto Scaling page, choose Create Auto Scaling Group.
4. On the Create Auto Scaling Group page, choose Create launch configuration.
5. On the Choose AMI step of the Create Auto Scaling Group wizard, choose Community AMIs.
6. Choose the ECS-optimized AMI for your Auto Scaling group.
To use the Amazon ECS-optimized AMI, type amazon-ecs-optimized in the Search community
AMIs field and press the Enter key. Choose Select next to the amzn-ami-2016.09.g-amazon-ecs-
optimized AMI. The current Amazon ECS–optimized AMI IDs by region are listed below for reference.
Region AMI Name AMI ID EC2 console link
us-east-1 amzn-ami-2016.09.g-
amazon-ecs-
optimized
ami-275ffe31 Launch instance
us-east-2 amzn-ami-2016.09.g-
amazon-ecs-
optimized
ami-62745007 Launch instance
us-west-1 amzn-ami-2016.09.g-
amazon-ecs-
optimized
ami-689bc208 Launch instance
us-west-2 amzn-ami-2016.09.g-
amazon-ecs-
optimized
ami-62d35c02 Launch instance
eu-west-1 amzn-ami-2016.09.g-
amazon-ecs-
optimized
ami-95f8d2f3 Launch instance
eu-west-2 amzn-ami-2016.09.g-
amazon-ecs-
optimized
ami-bf9481db Launch instance
eu-central-1 amzn-ami-2016.09.g-
amazon-ecs-
optimized
ami-085e8a67 Launch instance
ap-northeast-1 amzn-ami-2016.09.g-
amazon-ecs-
optimized
ami-f63f6f91 Launch instance
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Region AMI Name AMI ID EC2 console link
ap-southeast-1 amzn-ami-2016.09.g-
amazon-ecs-
optimized
ami-b4ae1dd7 Launch instance
ap-southeast-2 amzn-ami-2016.09.g-
amazon-ecs-
optimized
ami-fbe9eb98 Launch instance
ca-central-1 amzn-ami-2016.09.g-
amazon-ecs-
optimized
ami-ee58e58a Launch instance
7. On the Choose Instance Type step of the Create Auto Scaling Group wizard, choose an instance
type for your Auto Scaling group and choose Next: Configure details.
8. On the Configure details step of the Create Auto Scaling Group wizard, enter the following
information. The other fields are optional. For more information, see Creating Launch Configurations
in the Auto Scaling User Guide.
•Name: Enter a name for your launch configuration.
•IAM role: Select the ecsInstanceRole for your container instances. If you do not have this role
configured, see Amazon ECS Container Instance IAM Role (p. 210).
•IP Address Type: Choose the IP address type option that you want for your container instances. If
you want external traffic to be able to reach your containers, choose Assign a public IP address to
every instance.
9. (Optional) If you have configuration information that you want to pass to your container instances
with EC2 user data, choose Advanced Details and enter your user data in the User data field. For
more information, see Amazon ECS Container Agent Configuration (p. 79).
10. Choose Next: Add Storage.
11. On the Add Storage step of the Create Auto Scaling Group wizard, make any storage configuration
changes you need for your instances and choose Next: Configure Security Group.
12. On the Configure Security Group step of the Create Auto Scaling Group wizard, select an existing
security group that meets the needs of your containers, or create a new security group and choose
Review.
13. Review your launch configuration and choose Create launch configuration.
14. Select a private key to use for connecting to your instances with SSH and choose Create launch
configuration to finish and move on to creating an Auto Scaling group with your new launch
configuration.
Step 3: Create an Auto Scaling Group for your Cluster
After the launch configuration is complete, continue with the following procedure to create an Auto
Scaling group that uses your launch configuration.
To create an Auto Scaling group
1. On the Configure Auto Scaling group details step of the Create Auto Scaling Group wizard, enter
the following information and choose Next: Configure scaling policies.
•Group name: Enter a name for your Auto Scaling group.
•Group size: Specify the number of container instances your Auto Scaling group should start with.
•Network: Choose a VPC to launch your container instances into.
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•Subnet: Choose the subnets you would like to launch your container instances into. For a highly
available cluster, we recommend that you enable all of the subnets in the region.
2. On the Configure scaling policies step of the Create Auto Scaling Group wizard, choose Use
scaling policies to adjust the capacity of this group.
3. Enter the minimum and maximum number of container instances for your Auto Scaling group.
4. In the Increase Group Size section, enter the following information.
•Execute policy when: Choose the memory-above-75-pct CloudWatch alarm you configured earlier.
•Take the action: Enter the number of instances you would like to add to your cluster when the
alarm is triggered.
5. If you configured an alarm to trigger a group size reduction, set that alarm in the Decrease Group
Size section and specify how many instances to remove if that alarm is triggered. Otherwise,
collapse the Decrease Group Size section by clicking the X in the upper-right-hand corner of the
section.
Note
If you configure your Auto Scaling group to remove container instances, any tasks running
on the removed container instances are killed. If your tasks are running as part of a service,
Amazon ECS restarts those tasks on another instance if the required resources are available
(CPU, memory, ports); however, tasks that were started manually will are not restarted
automatically.
6. Choose Review to review your Auto Scaling group and then choose Create Auto Scaling Group to
finish.
Step 4: Verify and Test your Auto Scaling Group
Now that you've created your Auto Scaling group, you should be able to see your instances launching in
the Amazon EC2 console Instances page. These instances should register into your Amazon ECS cluster
as well after they launch.
To test that your Auto Scaling group is configured properly, you can create some tasks that consume a
considerable amount of memory and start launching them into your cluster. After your cluster exceeds
the 75% memory reservation from the CloudWatch alarm for the specified number of periods, you
should see a new instance launch in the EC2 console.
Step 5: Cleaning Up
When you have completed this tutorial, you may choose to keep your Auto Scaling group and Amazon
EC2 instances in service for your cluster. However, if you are not actively using these resources, you
should consider cleaning them up so your account does not incur unnecessary charges. You can delete
your Auto Scaling group to terminate the Amazon EC2 instances within it, but your launch configuration
remains intact and you can create a new Auto Scaling group with it later if you choose.
To delete your Auto Scaling group
1. Open the Amazon EC2 console at https://console.aws.amazon.com/ec2/.
2. On the left navigation, choose Auto Scaling Groups.
3. Choose the Auto Scaling group you created for this tutorial.
4. Choose Actions and then choose Delete.
5. Choose Yes, Delete to delete your Auto Scaling group.
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CloudWatch Events
Amazon ECS Event Stream for CloudWatch Events
You can use Amazon ECS event stream for CloudWatch Events to receive near real-time notifications
regarding the current state of both the container instances within an Amazon ECS cluster, and the
current state of all tasks running on those container instances.
Using CloudWatch Events, you can build custom schedulers on top of Amazon ECS that are responsible
for orchestrating tasks across clusters, and to monitor the state of clusters in near real time. With
Amazon ECS CloudWatch events, you can eliminate scheduling and monitoring code that continuously
polls the Amazon ECS service for status changes, and instead handle Amazon ECS state changes
asynchronously using any CloudWatch Events target, such as AWS Lambda, Amazon Simple Queue
Service, Amazon Simple Notification Service, and Amazon Kinesis Streams.
Events from Amazon ECS Event Stream are ensured to be delivered at least one time. In the event
that duplicate events are sent, the event provides enough information to identify duplicates. For more
information, see Handling Events (p. 192)
Events are relatively ordered, so that you can easily tell when an event occurred in relation to other
events.
Topics
•Amazon ECS Events (p. 187)
•Handling Events (p. 192)
•Tutorial: Listening for Amazon ECS CloudWatch Events (p. 194)
•Tutorial: Sending Amazon Simple Notification Service Alerts for Task Stopped Events (p. 195)
Amazon ECS Events
Amazon ECS sends two types of events following events to CloudWatch Events: container instance
events and task events. Amazon ECS tracks the state of your container instances and tasks. If either of
those resources changes, an event is triggered. These events are classified as either container instance
state change events or task state change events. These events and their possible causes are described in
greater detail in the following sections.
Note
Amazon ECS may add other event types, sources, and details in the future. If you are
programmatically deserializing event JSON data, make sure that your application is prepared to
handle unknown properties to avoid issues if and when these additional properties are added.
In some cases, multiple events are triggered for the same activity. For example, when a task is started
on a container instance, a task state change event is triggered for the new task, and a container instance
state change event is triggered to account for the change in available resources (such as CPU, memory,
and available ports) on the container instance. Likewise, if a container instance is terminated, events
are triggered for the container instance, the container agent connection status, and every task that was
running on the container instance.
Events contain two version fields; one in the main body of the event, and one in the detail object of
the event.
• The version in the main body of the event is set to 0 on all events. For more information about
CloudWatch Events parameters, see Events and Event Patterns in the Amazon CloudWatch Events User
Guide.
• The version in the detail object of the event describes the version of the associated resource. Each
time a resource changes state, this version is incremented. Because events can be sent multiple times,
this field allows you to identify duplicate events (they will have the same version in the detail object).
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If you are replicating your Amazon ECS container instance and task state with CloudWatch events, you
can compare the version of a resource reported by the Amazon ECS APIs with the version reported in
CloudWatch events for the resource (inside the detail object) to verify that the version in your event
stream is current.
Topics
•Container Instance State Change Events (p. 188)
•Task State Change Events (p. 191)
Container Instance State Change Events
The following scenarios trigger container instance state change events:
You call the StartTask, RunTask, or StopTask API operations (either directly, or with the AWS
Management Console or SDKs)
Placing or stopping tasks on a container instance modifies the available resources on the container
instance (such as CPU, memory, and available ports).
The Amazon ECS service scheduler starts or stops a task
Placing or stopping tasks on a container instance modifies the available resources on the container
instance (such as CPU, memory, and available ports).
The Amazon ECS container agent calls the SubmitTaskStateChange API operation with a STOPPED status
for a task with a desired status of RUNNING
The Amazon ECS container agent monitors the state of tasks on your container instances, and it
reports any state changes. If a task that is supposed to be RUNNING is transitioned to STOPPED, the
agent releases the resources that were allocated to the stopped task (such as CPU, memory, and
available ports).
You deregister the container instance with the DeregisterContainerInstance API operation (either
directly, or with the AWS Management Console or SDKs)
Deregistering a container instance changes the status of the container instance and the connection
status of the Amazon ECS container agent.
A task was stopped when EC2 instance was stopped
When you stop a container instance, the tasks that are running on it are transitioned to the STOPPED
status.
The Amazon ECS container agent registers a container instance for the first time
The first time the Amazon ECS container agent registers a container instance (at launch or when first
run manually), this creates a state change event for the instance.
The Amazon ECS container agent connects or disconnects from Amazon ECS
When the Amazon ECS container agent connects or disconnects from the Amazon ECS back end, it
changes the agentConnected status of the container instance.
Note
The Amazon ECS container agent periodically disconnects and reconnects (several times per
hour) as a part of its normal operation, so agent connection events should be expected and
they are not an indication that there is an issue with the container agent or your container
instance.
You upgrade the Amazon ECS container agent on an instance
The container instance detail contains an object for the container agent version. If you upgrade the
agent, this version information changes and triggers an event.
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Example Container Instance State Change Event
Container instance state change events are delivered in the following format (the detail section
below resembles the ContainerInstance object that is returned from a DescribeContainerInstances API
operation in the Amazon EC2 Container Service API Reference). For more information about CloudWatch
Events parameters, see Events and Event Patterns in the Amazon CloudWatch Events User Guide.
Note
Amazon ECS may add other event types, sources, and details in the future. If you are
programmatically deserializing event JSON data, make sure that your application is prepared to
handle unknown properties to avoid issues if and when these additional properties are added.
{
"version": "0",
"id": "8952ba83-7be2-4ab5-9c32-6687532d15a2",
"detail-type": "ECS Container Instance State Change",
"source": "aws.ecs",
"account": "111122223333",
"time": "2016-12-06T16:41:06Z",
"region": "us-east-1",
"resources": [
"arn:aws:ecs:us-east-1:111122223333:container-instance/
b54a2a04-046f-4331-9d74-3f6d7f6ca315"
],
"detail": {
"agentConnected": true,
"attributes": [
{
"name": "com.amazonaws.ecs.capability.logging-driver.syslog"
},
{
"name": "com.amazonaws.ecs.capability.task-iam-role-network-host"
},
{
"name": "com.amazonaws.ecs.capability.logging-driver.awslogs"
},
{
"name": "com.amazonaws.ecs.capability.logging-driver.json-file"
},
{
"name": "com.amazonaws.ecs.capability.docker-remote-api.1.17"
},
{
"name": "com.amazonaws.ecs.capability.privileged-container"
},
{
"name": "com.amazonaws.ecs.capability.docker-remote-api.1.18"
},
{
"name": "com.amazonaws.ecs.capability.docker-remote-api.1.19"
},
{
"name": "com.amazonaws.ecs.capability.ecr-auth"
},
{
"name": "com.amazonaws.ecs.capability.docker-remote-api.1.20"
},
{
"name": "com.amazonaws.ecs.capability.docker-remote-api.1.21"
},
{
"name": "com.amazonaws.ecs.capability.docker-remote-api.1.22"
},
{
"name": "com.amazonaws.ecs.capability.docker-remote-api.1.23"
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},
{
"name": "com.amazonaws.ecs.capability.task-iam-role"
}
],
"clusterArn": "arn:aws:ecs:us-east-1:111122223333:cluster/default",
"containerInstanceArn": "arn:aws:ecs:us-east-1:111122223333:container-instance/
b54a2a04-046f-4331-9d74-3f6d7f6ca315",
"ec2InstanceId": "i-f3a8506b",
"registeredResources": [
{
"name": "CPU",
"type": "INTEGER",
"integerValue": 2048
},
{
"name": "MEMORY",
"type": "INTEGER",
"integerValue": 3767
},
{
"name": "PORTS",
"type": "STRINGSET",
"stringSetValue": [
"22",
"2376",
"2375",
"51678",
"51679"
]
},
{
"name": "PORTS_UDP",
"type": "STRINGSET",
"stringSetValue": []
}
],
"remainingResources": [
{
"name": "CPU",
"type": "INTEGER",
"integerValue": 1988
},
{
"name": "MEMORY",
"type": "INTEGER",
"integerValue": 767
},
{
"name": "PORTS",
"type": "STRINGSET",
"stringSetValue": [
"22",
"2376",
"2375",
"51678",
"51679"
]
},
{
"name": "PORTS_UDP",
"type": "STRINGSET",
"stringSetValue": []
}
],
"status": "ACTIVE",
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"version": 14801,
"versionInfo": {
"agentHash": "aebcbca",
"agentVersion": "1.13.0",
"dockerVersion": "DockerVersion: 1.11.2"
},
"updatedAt": "2016-12-06T16:41:06.991Z"
}
}
Task State Change Events
The following scenarios trigger task state change events:
You call the StartTask, RunTask, or StopTask API operations (either directly, or with the AWS
Management Console or SDKs)
Starting or stopping tasks creates new task resources or modifies the state of existing task resources.
The Amazon ECS service scheduler starts or stops a task
Starting or stopping tasks creates new task resources or modifies the state of existing task resources.
The Amazon ECS container agent calls the SubmitTaskStateChange API operation
The Amazon ECS container agent monitors the state of tasks on your container instances, and it
reports any state changes (for example, from PENDING to RUNNING, or from RUNNING to STOPPED.
You force deregistration of the underlying container instance with the DeregisterContainerInstance
API operation and the force flag (either directly, or with the AWS Management Console or SDKs)
Deregistering a container instance changes the status of the container instance and the connection
status of the Amazon ECS container agent. If tasks are running on the container instance, the force
flag must be set to allow deregistration. This stops all tasks on the instance.
The underlying container instance is stopped or terminated
When you stop or terminate a container instance, the tasks that are running on it are transitioned to
the STOPPED status.
A container in the task changes state
The Amazon ECS container agent monitors the state of containers within tasks. For example, if a
container that is running within a task stops, this container state change triggers an event.
Example Task State Change Event
Task state change events are delivered in the following format (the detail section below resembles the
Task object that is returned from a DescribeTasks API operation in the Amazon EC2 Container Service API
Reference). For more information about CloudWatch Events parameters, see Events and Event Patterns in
the Amazon CloudWatch Events User Guide.
Note
Amazon ECS may add other event types, sources, and details in the future. If you are
programmatically deserializing event JSON data, make sure that your application is prepared to
handle unknown properties to avoid issues if and when these additional properties are added.
{
"version": "0",
"id": "9bcdac79-b31f-4d3d-9410-fbd727c29fab",
"detail-type": "ECS Task State Change",
"source": "aws.ecs",
"account": "111122223333",
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"time": "2016-12-06T16:41:06Z",
"region": "us-east-1",
"resources": [
"arn:aws:ecs:us-east-1:111122223333:task/b99d40b3-5176-4f71-9a52-9dbd6f1cebef"
],
"detail": {
"clusterArn": "arn:aws:ecs:us-east-1:111122223333:cluster/default",
"containerInstanceArn": "arn:aws:ecs:us-east-1:111122223333:container-instance/
b54a2a04-046f-4331-9d74-3f6d7f6ca315",
"containers": [
{
"containerArn": "arn:aws:ecs:us-east-1:111122223333:container/3305bea1-
bd16-4217-803d-3e0482170a17",
"exitCode": 0,
"lastStatus": "STOPPED",
"name": "xray",
"taskArn": "arn:aws:ecs:us-east-1:111122223333:task/
b99d40b3-5176-4f71-9a52-9dbd6f1cebef"
}
],
"createdAt": "2016-12-06T16:41:05.702Z",
"desiredStatus": "RUNNING",
"lastStatus": "RUNNING",
"overrides": {
"containerOverrides": [
{
"name": "xray"
}
]
},
"startedAt": "2016-12-06T16:41:06.8Z",
"startedBy": "ecs-svc/9223370556150183303",
"updatedAt": "2016-12-06T16:41:06.975Z",
"taskArn": "arn:aws:ecs:us-east-1:111122223333:task/
b99d40b3-5176-4f71-9a52-9dbd6f1cebef",
"taskDefinitionArn": "arn:aws:ecs:us-east-1:111122223333:task-definition/xray:2",
"version": 4
}
}
Handling Events
Amazon ECS sends events on an "at least once" basis. This means you may receive more than a single
copy of a given event. Additionally, events may not be delivered to your event listeners in the order in
which the events occurred.
To enable proper ordering of events, the detail section of each event contains a version property.
Events with a higher version property number should be treated as occurring later than events with
lower version numbers. Events with matching version numbers can be treated as duplicates.
Example: Handling Events in an AWS Lambda Function
The following example shows a Lambda function written in Python 2.7 that captures both task and
container instance state change events, and saves them to one of two Amazon DynamoDB tables:
•ECSCtrInstanceState: Stores the latest state for a container instance. The table ID is the
containerInstanceArn value of the container instance.
•ECSTaskState: Stores the latest state for a task. The table ID is the taskArn value of the task.
import json
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import boto3
def lambda_handler(event, context):
id_name = ""
new_record = {}
# For debugging so you can see raw event format.
print('Here is the event:')
print(json.dumps(event))
if event["source"] != "aws.ecs":
raise ValueError("Function only supports input from events with a source type of:
aws.ecs")
# Switch on task/container events.
table_name = ""
if event["detail-type"] == "ECS Task State Change":
table_name = "ECSTaskState"
id_name = "taskArn"
event_id = event["detail"]["taskArn"]
elif event["detail-type"] == "ECS Container Instance State Change":
table_name = "ECSCtrInstanceState"
id_name = "containerInstanceArn"
event_id = event["detail"]["containerInstanceArn"]
else:
raise ValueError("detail-type for event is not a supported type. Exiting without
saving event.")
new_record["cw_version"] = event["version"]
new_record.update(event["detail"])
# "status" is a reserved word in DDB, but it appears in containerPort
# state change messages.
if "status" in event:
new_record["current_status"] = event["status"]
new_record.pop("status")
# Look first to see if you have received a newer version of an event ID.
# If the version is OLDER than what you have on file, do not process it.
# Otherwise, update the associated record with this latest information.
print("Looking for recent event with same ID...")
dynamodb = boto3.resource("dynamodb", region_name="us-east-1")
table = dynamodb.Table(table_name)
saved_event = table.get_item(
Key={
id_name : event_id
}
)
if "Item" in saved_event:
# Compare events and reconcile.
print("EXISTING EVENT DETECTED: Id " + event_id + " - reconciling")
if saved_event["Item"]["version"] < event["detail"]["version"]:
print("Received event is more recent version than stored event - updating")
table.put_item(
Item=new_record
)
else:
print("Received event is more recent version than stored event - ignoring")
else:
print("Saving new event - ID " + event_id)
table.put_item(
Item=new_record
)
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Tutorial: Listening for Amazon ECS CloudWatch
Events
In this tutorial, you set up a simple AWS Lambda function that listens for Amazon ECS task events and
writes them out to a CloudWatch Logs log stream.
Step 1: Set Up a Test Cluster
If you do not have a running cluster to capture events from, follow the steps in Getting Started with
Amazon ECS (p. 20) to create one. At the end of this tutorial, you run a task on this cluster to test that
you have configured your Lambda function correctly.
Step 2: Create the Lambda Function
In this procedure, you will create a simple Lambda function to serve as a target for Amazon ECS event
stream messages.
1. Open the AWS Lambda console at https://console.aws.amazon.com/lambda/.
2. Choose Create a Lambda function.
3. On the Select blueprint screen, for Select runtime, choose Python 2.7 and choose hello-world-
python.
4. In the Lambda function code section, edit the sample code to match the following example:
import json
def lambda_handler(event, context):
if event["source"] != "aws.ecs":
raise ValueError("Function only supports input from events with a source type
of: aws.ecs")
print('Here is the event:')
print(json.dumps(event))
This is a simple Python 2.7 function that prints the event sent by Amazon ECS. If everything is
configured correctly, at the end of this tutorial, you see the event details appear in the CloudWatch
Logs log stream associated with this Lambda function.
5. On the Configure triggers screen, choose Next. (You configure your event source later.)
6. On the Configure function screen, for Name, enter eventstream-handler.
7. In the Lambda function handler and role section, for Role, choose Create a custom role. A new
window pops up enabling you to create a new role for your Lambda function.
8. On the AWS Lambda requires access to your resources screen, accept the defaults and choose
Allow.
9. On the Configure function screen, choose Next, Create function.
Step 3: Register Event Rule
Next, you create a CloudWatch Events event rule that captures task events coming from your Amazon
ECS clusters. This rule captures all events coming from all clusters within the account where it is defined.
The task messages themselves contain information about the event source, including the cluster on
which it resides, that you can use to filter and sort events programmatically.
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Service Alerts for Task Stopped Events
Note
When you use the AWS Management Console to create an event rule, the console automatically
adds the IAM permissions necessary to grant CloudWatch Events permission to call your Lambda
function. If you are creating an event rule using the AWS CLI, you need to grant this permission
explicitly. For more information, see Events and Event Patterns in the Amazon CloudWatch User
Guide.
To route events to your Lambda function
1. Open the CloudWatch console at https://console.aws.amazon.com/cloudwatch/.
2. On the navigation pane, choose Events, Create rule.
3. For Event selector, choose ECS as the event source. By default, the rule applies to all Amazon ECS
events for all of your Amazon ECS groups. Alternatively, you can select specific events or a specific
Amazon ECS group.
4. For Targets, choose Add target, for Target type, choose Lambda function, and then select your
Lambda function.
5. Choose Configure details.
6. For Rule definition, type a name and description for your rule and choose Create rule.
Step 4: Test Your Rule
Finally, you create a CloudWatch Events event rule that captures task events coming from your Amazon
ECS clusters. This rule captures all events coming from all clusters within the account where it is defined.
The task messages themselves contain information about the event source, including the cluster on
which it resides, that you can use to filter and sort events programmatically.
To test your rule
1. Open the Amazon ECS console at https://console.aws.amazon.com/ecs/.
2. Choose Clusters, default.
3. On the Cluster : default screen, choose Tasks, Run new Task.
4. For Task Definition, select the latest version of console-sample-app-static and choose Run Task.
5. Open the CloudWatch console at https://console.aws.amazon.com/cloudwatch/.
6. On the navigation pane, choose Logs and select the log group for your Lambda function (for
example, /aws/lambda/my-function).
7. Select a log stream to view the event data.
Tutorial: Sending Amazon Simple Notification Service
Alerts for Task Stopped Events
In this tutorial, you configure a CloudWatch Events event rule that only captures task events where the
task has stopped running because one of its essential containers has terminated. The event sends only
task events with a specific stoppedReason property to the designated Amazon SNS topic.
Step 1: Set Up a Test Cluster
If you do not have a running cluster to capture events from, follow the steps in Getting Started with
Amazon ECS (p. 20) to create one. At the end of this tutorial, you run a task on this cluster to test that
you have configured your Amazon SNS topic and CloudWatch Events event rule correctly.
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Step 2: Create and Subscribe to an Amazon SNS Topic
For this tutorial, you configure an Amazon SNS topic to serve as an event target for your new event rule.
To create a Amazon SNS topic
1. Open the Amazon SNS console at https://console.aws.amazon.com/sns/v2/home.
2. Choose Topics, Create new topic.
3. On the Create new topic window, for Topic name, enter TaskStoppedAlert and choose Create
topic.
4. On the Topics window, select the topic that you just created. On the Topic details:
TaskStoppedAlert screen, choose Create subscription.
5. On the Create Subscription window, for Protocol, choose Email. For Endpoint, enter an email
address to which you currently have access and choose Create subscription.
6. Check your email account, and wait to receive a subscription confirmation email message. When you
receive it, choose Confirm subscription.
Step 3: Register Event Rule
Next, you register an event rule that captures only task-stopped events for tasks with stopped
containers.
To create an event rule
1. Open the CloudWatch console at https://console.aws.amazon.com/cloudwatch/.
2. On the navigation pane, choose Events, Create rule.
3. Choose Show advanced options, edit.
4. For Build a pattern that selects events for processing by your targets, replace the existing text
with the following text:
{
"source": [
"aws.ecs"
],
"detail-type": [
"ECS Task State Change"
],
"detail": {
"lastStatus": [
"STOPPED"
],
"stoppedReason" : [
"Essential container in task exited"
]
}
}
This code defines a CloudWatch Events event rule that matches any event where the lastStatus and
stoppedReason fields match the indicated values. For more information about event patterns, see
Events and Event Patterns in the Amazon CloudWatch User Guide.
5. For Targets, choose Add target. For Target type, choose SNS topic, and then choose
TaskStoppedAlert.
6. Choose Configure details.
7. For Rule definition, type a name and description for your rule and then choose Create rule.
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Step 4: Test Your Rule
To test your rule, you attempt to run a task that exits shortly after it starts. If your event rule is
configured correctly, you receive an email message within a few minutes with the event text.
To test a rule
1. Open the Amazon ECS console at https://console.aws.amazon.com/ecs/.
2. Choose Task Definitions, Create new Task Definition.
3. For Task Definition Name, type WordPressFailure and choose Add Container.
4. For Container name, type Wordpress, for Image, type wordpress, and for Maximum memory (MB),
type 128.
5. Choose Add, Create.
6. On the Task Definition screen, choose Actions, Run Task.
7. For Cluster, choose default and then Run Task.
8. On the Tasks tab for your cluster, periodically choose the refresh icon until you no longer see your
task running. For Desired task status, choose Stopped to verify that your task has stopped.
9. Check your email to confirm that you have received an email alert for the stopped notification.
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Amazon ECS IAM Policies, Roles, and
Permissions
By default, IAM users don't have permission to create or modify Amazon ECS resources, or perform tasks
using the Amazon ECS API. (This means that they also can't do so using the Amazon ECS console or the
AWS CLI.) To allow IAM users to create or modify resources and perform tasks, you must create IAM
policies that grant IAM users permission to use the specific resources and API actions they'll need, and
then attach those policies to the IAM users or groups that require those permissions.
When you attach a policy to a user or group of users, it allows or denies the users permission to perform
the specified tasks on the specified resources. For more general information about IAM policies, see
Permissions and Policies in the IAM User Guide. For more information about managing and creating
custom IAM policies, see Managing IAM Policies.
Likewise, Amazon ECS container instances make calls to the Amazon ECS and Amazon EC2 APIs on
your behalf, so they need to authenticate with your credentials. This authentication is accomplished by
creating an IAM role for your container instances and associating that role with your container instances
when you launch them. For more information, see Amazon ECS Container Instance IAM Role (p. 210). If
you use an Elastic Load Balancing load balancer with your Amazon ECS services, calls to the Amazon EC2
and Elastic Load Balancing APIs are made on your behalf to register and deregister container instances
with your load balancers. For more information, see Amazon ECS Service Scheduler IAM Role (p. 212).
For more general information about IAM roles, see IAM Roles in the IAM User Guide.
Getting Started
An IAM policy must grant or deny permission to use one or more Amazon ECS actions. It must also
specify the resources that can be used with the action, which can be all resources, or in some cases,
specific resources. The policy can also include conditions that you apply to the resource.
Amazon ECS partially supports resource-level permissions. This means that for some Amazon ECS API
actions, you cannot specify which resource a user is allowed to work with for that action; instead, you
have to allow users to work with all resources for that action.
Topics
•Policy Structure (p. 199)
•Supported Resource-Level Permissions for Amazon ECS API Actions (p. 203)
•Creating Amazon ECS IAM Policies (p. 205)
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Policy Structure
•Managed Policies (p. 205)
•Amazon ECS Container Instance IAM Role (p. 210)
•Amazon ECS Service Scheduler IAM Role (p. 212)
•Amazon ECS Service Auto Scaling IAM Role (p. 214)
•Amazon EC2 Container Service Task Role (p. 215)
•IAM Roles for Tasks (p. 216)
•Amazon ECS IAM Policy Examples (p. 220)
Policy Structure
The following topics explain the structure of an IAM policy.
Topics
•Policy Syntax (p. 199)
•Actions for Amazon ECS (p. 200)
•Amazon Resource Names for Amazon ECS (p. 200)
•Condition Keys for Amazon ECS (p. 201)
•Checking that Users Have the Required Permissions (p. 202)
Policy Syntax
An IAM policy is a JSON document that consists of one or more statements. Each statement is structured
as follows:
{
"Statement":[{
"Effect":"effect",
"Action":"action",
"Resource":"arn",
"Condition":{
"condition":{
"key":"value"
}
}
}
]
}
There are various elements that make up a statement:
•Effect: The effect can be Allow or Deny. By default, IAM users don't have permission to use resources
and API actions, so all requests are denied. An explicit allow overrides the default. An explicit deny
overrides any allows.
•Action: The action is the specific API action for which you are granting or denying permission. To learn
about specifying action, see Actions for Amazon ECS (p. 200).
•Resource: The resource that's affected by the action. Some Amazon ECS API actions allow you to
include specific resources in your policy that can be created or modified by the action. To specify a
resource in the statement, you need to use its Amazon Resource Name (ARN). For more information
about specifying the arn value, see Amazon Resource Names for Amazon ECS (p. 200). For more
information about which API actions support which ARNs, see Supported Resource-Level Permissions
for Amazon ECS API Actions (p. 203). If the API action does not support ARNs, use the * wildcard to
specify that all resources can be affected by the action.
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Actions for Amazon ECS
•Condition: Conditions are optional. They can be used to control when your policy will be in effect.
For more information about specifying conditions for Amazon ECS, see Condition Keys for Amazon
ECS (p. 201).
For more information about example IAM policy statements for Amazon ECS, see Creating Amazon ECS
IAM Policies (p. 205).
Actions for Amazon ECS
In an IAM policy statement, you can specify any API action from any service that supports IAM. For
Amazon ECS, use the following prefix with the name of the API action: ecs:. For example: ecs:RunTask
and ecs:CreateCluster.
To specify multiple actions in a single statement, separate them with commas as follows:
"Action": ["ecs:action1", "ecs:action2"]
You can also specify multiple actions using wildcards. For example, you can specify all actions whose
name begins with the word "Describe" as follows:
"Action": "ecs:Describe*"
To specify all Amazon ECS API actions, use the * wildcard as follows:
"Action": "ecs:*"
For a list of Amazon ECS actions, see Actions in the Amazon EC2 Container Service API Reference.
Amazon Resource Names for Amazon ECS
Each IAM policy statement applies to the resources that you specify using their ARNs.
Important
Currently, not all API actions support individual ARNs; we'll add support for additional API
actions and ARNs for additional Amazon ECS resources later. For information about which ARNs
you can use with which Amazon ECS API actions, as well as supported condition keys for each
ARN, see Supported Resource-Level Permissions for Amazon ECS API Actions (p. 203).
An ARN has the following general syntax:
arn:aws:[service]:[region]:[account]:resourceType/resourcePath
service
The service (for example, ecs).
region
The region for the resource (for example, us-east-1).
account
The AWS account ID, with no hyphens (for example, 123456789012).
resourceType
The type of resource (for example, instance).
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Condition Keys for Amazon ECS
resourcePath
A path that identifies the resource. You can use the * wildcard in your paths.
For example, you can indicate a specific cluster (default) in your statement using its ARN as follows:
"Resource": "arn:aws:ecs:us-east-1:123456789012:cluster/default"
You can also specify all clusters that belong to a specific account by using the * wildcard as follows:
"Resource": "arn:aws:ecs:us-east-1:123456789012:cluster/*"
To specify all resources, or if a specific API action does not support ARNs, use the * wildcard in the
Resource element as follows:
"Resource": "*"
The following table describes the ARNs for each type of resource used by the Amazon ECS API actions.
Resource Type ARN
All Amazon ECS resources arn:aws:ecs:*
All Amazon ECS resources
owned by the specified account
in the specified region
arn:aws:ecs:region:account:*
Cluster arn:aws:ecs:region:account:cluster/cluster-name
Container instance arn:aws:ecs:region:account:container-instance/container-instance-id
Task definition arn:aws:ecs:region:account:task-definition/task-definition-family-
name:task-definition-revision-number
Service arn:aws:ecs:region:account:service/service-name
Task arn:aws:ecs:region:account:task/task-id
Container arn:aws:ecs:region:account:container/container-id
Many Amazon ECS API actions accept multiple resources. To specify multiple resources in a single
statement, separate their ARNs with commas, as follows:
"Resource": ["arn1", "arn2"]
For more general information about ARNs, see Amazon Resource Names (ARN) and AWS Service
Namespaces in the Amazon Web Services General Reference.
Condition Keys for Amazon ECS
In a policy statement, you can optionally specify conditions that control when it is in effect. Each
condition contains one or more key-value pairs. Condition keys are not case-sensitive. We've defined
AWS-wide condition keys, plus additional service-specific condition keys.
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Testing Permissions
If you specify multiple conditions, or multiple keys in a single condition, we evaluate them using a
logical AND operation. If you specify a single condition with multiple values for one key, we evaluate the
condition using a logical OR operation. For permission to be granted, all conditions must be met.
You can also use placeholders when you specify conditions. For more information, see Policy Variables in
the IAM User Guide.
Amazon ECS implements the AWS-wide condition keys (see Available Keys), plus the following service-
specific condition keys. (We'll add support for additional service-specific condition keys for Amazon ECS
later.)
Condition Key Key/Value Pair Evaluation Types
ecs:cluster "ecs:cluster":"cluster-arn"
Where cluster-arn is the ARN for the Amazon ECS cluster
ARN, Null
ecs:container-
instances
"ecs:container-instances":"container-instance-arns"
Where container-instance-arns is one or more container
instance ARNs.
ARN, Null
For information about which condition keys you can use with which Amazon ECS resources, on an action-
by-action basis, see Supported Resource-Level Permissions for Amazon ECS API Actions (p. 203). For
example policy statements for Amazon ECS, see Creating Amazon ECS IAM Policies (p. 205).
Checking that Users Have the Required Permissions
After you've created an IAM policy, we recommend that you check whether it grants users the
permissions to use the particular API actions and resources they need before you put the policy into
production.
First, create an IAM user for testing purposes, and then attach the IAM policy that you created to the test
user. Then, make a request as the test user. You can make test requests in the console or with the AWS
CLI.
Note
You can also test your policies with the IAM Policy Simulator. For more information on the policy
simulator, see Working with the IAM Policy Simulator in the IAM User Guide.
If the action that you are testing creates or modifies a resource, you should make the request using
the DryRun parameter (or run the AWS CLI command with the --dry-run option). In this case, the
call completes the authorization check, but does not complete the operation. For example, you can
check whether the user can terminate a particular instance without actually terminating it. If the
test user has the required permissions, the request returns DryRunOperation; otherwise, it returns
UnauthorizedOperation.
If the policy doesn't grant the user the permissions that you expected, or is overly permissive, you can
adjust the policy as needed and retest until you get the desired results.
Important
It can take several minutes for policy changes to propagate before they take effect. Therefore,
we recommend that you allow five minutes to pass before you test your policy updates.
If an authorization check fails, the request returns an encoded message with diagnostic information.
You can decode the message using the DecodeAuthorizationMessage action. For more information, see
DecodeAuthorizationMessage in the AWS Security Token Service API Reference, and decode-authorization-
message in the AWS Command Line Interface Reference.
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Supported Resource-Level Permissions
Supported Resource-Level Permissions for Amazon
ECS API Actions
Resource-level permissions refers to the ability to specify which resources users are allowed to perform
actions on. Amazon ECS has partial support for resource-level permissions. This means that for certain
Amazon ECS actions, you can control when users are allowed to use those actions based on conditions
that have to be fulfilled, or specific resources that users are allowed to use. For example, you can grant
users permission to launch instances, but only of a specific type, and only using a specific AMI.
The following table describes the Amazon ECS API actions that currently support resource-level
permissions, as well as the supported resources, resource ARNs, and condition keys for each action.
Important
If an Amazon ECS API action is not listed in this table, then it does not support resource-level
permissions. If an Amazon ECS API action does not support resource-level permissions, you can
grant users permission to use the action, but you have to specify a * for the resource element of
your policy statement.
API action Resource Condition keys
DeleteAttributes Container instance
arn:aws:ecs:region:account:container-
instance/container-instance-id
ecs:cluster
DeleteCluster Cluster
arn:aws:ecs:region:account:cluster/my-
cluster
N/A
DeregisterContainerInstanceCluster
arn:aws:ecs:region:account:cluster/my-
cluster
N/A
DescribeClusters Cluster
arn:aws:ecs:region:account:cluster/my-
cluster1,
arn:aws:ecs:region:account:cluster/my-
cluster2
N/A
DescribeContainerInstancesContainer instance
arn:aws:ecs:region:account:container-
instance/container-instance-id1,
arn:aws:ecs:region:account:container-
instance/container-instance-id2
ecs:cluster
DescribeTasks Task
arn:aws:ecs:region:account:task/
1abf0f6d-a411-4033-
b8eb-a4eed3ad252a,
arn:aws:ecs:region:account:task/
1abf0f6d-a411-4033-b8eb-
a4eed3ad252b
ecs:cluster
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API action Resource Condition keys
ListAttributes Cluster
arn:aws:ecs:region:account:cluster/my-
cluster
N/A
ListContainerInstances Cluster
arn:aws:ecs:region:account:cluster/my-
cluster
N/A
ListTasks Container instance
arn:aws:ecs:region:account:container-
instance/container-instance-id
ecs:cluster
Poll Container instance
arn:aws:ecs:region:account:container-
instance/container-instance-id
ecs:cluster
PutAttributes Container instance
arn:aws:ecs:region:account:container-
instance/container-instance-id
ecs:cluster
RegisterContainerInstance Cluster
arn:aws:ecs:region:account:cluster/my-
cluster
N/A
RunTask Task definition
arn:aws:ecs:region:account:task-
definition/hello_world:8
ecs:cluster
StartTask Task definition
arn:aws:ecs:region:account:task-
definition/hello_world:8
ecs:cluster
ecs:container-instances
StartTelemetrySession Container instance
arn:aws:ecs:region:account:container-
instance/container-instance-id
ecs:cluster
StopTask Task
arn:aws:ecs:region:account:task/
1abf0f6d-a411-4033-b8eb-
a4eed3ad252a
ecs:cluster
SubmitContainerStateChangeCluster
arn:aws:ecs:region:account:cluster/my-
cluster
N/A
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API action Resource Condition keys
SubmitTaskStateChange Cluster
arn:aws:ecs:region:account:cluster/my-
cluster
N/A
UpdateContainerAgent Container instance
arn:aws:ecs:region:account:container-
instance/container-instance-id
ecs:cluster
UpdateContainerInstancesStateContainer instance
arn:aws:ecs:region:account:container-
instance/container-instance-id
ecs:cluster
Creating Amazon ECS IAM Policies
You can create specific IAM policies to restrict the calls and resources that users in your account have
access to, and then attach those policies to IAM users.
When you attach a policy to a user or group of users, it allows or denies the users permission to perform
the specified tasks on the specified resources. For more general information about IAM policies, see
Permissions and Policies in the IAM User Guide. For more information about managing and creating
custom IAM policies, see Managing IAM Policies.
To create an IAM policy for a user
1. Open the IAM console at https://console.aws.amazon.com/iam/.
2. In the navigation pane, choose Policies and then choose Create Policy.
3. In the Create Policy section, choose Select next to Create Your Own Policy.
4. In the Policy Name field, type your own unique name, such as AmazonECSUserPolicy.
5. In the Policy Document field, paste the policy to apply to the user. For example policies, see Amazon
ECS IAM Policy Examples (p. 220).
6. Choose Create Policy to finish.
To attach an IAM policy to a user
1. Open the IAM console at https://console.aws.amazon.com/iam/.
2. In the navigation pane, choose Users and then choose the user you would like to attach the policy
to.
3. In the Permissions tab, choose Attach Policy.
4. In the Attach Policy section, select the custom policy you created in the previous procedure and
then choose Attach Policy.
Managed Policies
Amazon ECS and Amazon ECR provide several managed policies that you can attach to IAM users or EC2
instances that allow differing levels of control over resources and API operations. You can apply these
policies directly, or you can use them as starting points for creating your own polices.
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Topics
•Amazon ECS Managed Policies (p. 206)
•Amazon ECR Managed Policies (p. 208)
Amazon ECS Managed Policies
Amazon ECS provides several managed policies that you can attach to IAM users or EC2 instances
that allow differing levels of control over Amazon ECS resources and API operations. You can apply
these policies directly, or you can use them as starting points for creating your own polices. For more
information about each API operation mentioned in these policies, see Actions in the Amazon EC2
Container Service API Reference.
Topics
•AmazonEC2ContainerServiceFullAccess (p. 206)
•AmazonEC2ContainerServiceforEC2Role (p. 206)
•AmazonEC2ContainerServiceRole (p. 207)
•AmazonEC2ContainerServiceAutoscaleRole (p. 207)
•AmazonEC2ContainerServiceTaskRole (p. 208)
AmazonEC2ContainerServiceFullAccess
This policy allows full administrator access to Amazon ECS.
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Action": [
"autoscaling:Describe*",
"autoscaling:UpdateAutoScalingGroup",
"cloudformation:CreateStack",
"cloudformation:DeleteStack",
"cloudformation:DescribeStack*",
"cloudformation:UpdateStack",
"cloudwatch:GetMetricStatistics",
"ec2:Describe*",
"elasticloadbalancing:*",
"ecs:*",
"iam:ListInstanceProfiles",
"iam:ListRoles",
"iam:PassRole"
],
"Resource": "*"
}
]
}
AmazonEC2ContainerServiceforEC2Role
This policy allows Amazon ECS container instances to make calls to AWS on your behalf. For more
information, see Amazon ECS Container Instance IAM Role (p. 210).
{
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"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Action": [
"ecs:CreateCluster",
"ecs:DeregisterContainerInstance",
"ecs:DiscoverPollEndpoint",
"ecs:Poll",
"ecs:RegisterContainerInstance",
"ecs:StartTelemetrySession",
"ecs:Submit*",
"ecr:GetAuthorizationToken",
"ecr:BatchCheckLayerAvailability",
"ecr:GetDownloadUrlForLayer",
"ecr:BatchGetImage",
"logs:CreateLogStream",
"logs:PutLogEvents"
],
"Resource": "*"
}
]
}
AmazonEC2ContainerServiceRole
This policy allows Elastic Load Balancing load balancers to register and deregister Amazon ECS container
instances on your behalf. For more information, see Amazon ECS Service Scheduler IAM Role (p. 212).
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Action": [
"ec2:AuthorizeSecurityGroupIngress",
"ec2:Describe*",
"elasticloadbalancing:DeregisterInstancesFromLoadBalancer",
"elasticloadbalancing:DeregisterTargets",
"elasticloadbalancing:Describe*",
"elasticloadbalancing:RegisterInstancesWithLoadBalancer",
"elasticloadbalancing:RegisterTargets"
],
"Resource": "*"
}
]
}
AmazonEC2ContainerServiceAutoscaleRole
This policy allows Application Auto Scaling to scale your Amazon ECS service's desired count up and
down in response to CloudWatch alarms on your behalf. For more information, see Amazon ECS Service
Auto Scaling IAM Role (p. 214).
{
"Version": "2012-10-17",
"Statement": [
{
"Sid": "Stmt1456535218000",
"Effect": "Allow",
"Action": [
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"ecs:DescribeServices",
"ecs:UpdateService"
],
"Resource": [
"*"
]
},
{
"Sid": "Stmt1456535243000",
"Effect": "Allow",
"Action": [
"cloudwatch:DescribeAlarms"
],
"Resource": [
"*"
]
}
]
}
AmazonEC2ContainerServiceTaskRole
This policy allows containers in your Amazon ECS tasks to make calls to the AWS APIs on your behalf. For
more information, see Amazon EC2 Container Service Task Role (p. 215).
{
"Version": "2012-10-17",
"Statement": [
{
"Sid": "",
"Effect": "Allow",
"Principal": {
"Service": "ecs-tasks.amazonaws.com"
},
"Action": "sts:AssumeRole"
}
]
}
Amazon ECR Managed Policies
Amazon ECR provides several managed policies that you can attach to IAM users or EC2 instances
that allow differing levels of control over Amazon ECR resources and API operations. You can apply
these policies directly, or you can use them as starting points for creating your own policies. For more
information about each API operation mentioned in these policies, see Actions in the Amazon EC2
Container Registry API Reference.
Topics
•AmazonEC2ContainerRegistryFullAccess (p. 208)
•AmazonEC2ContainerRegistryPowerUser (p. 209)
•AmazonEC2ContainerRegistryReadOnly (p. 209)
AmazonEC2ContainerRegistryFullAccess
This policy allows full administrator access to Amazon ECR.
{
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"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Action": [
"ecr:*"
],
"Resource": "*"
}
]
}
AmazonEC2ContainerRegistryPowerUser
This policy allows power user access to Amazon ECR, which allows read and write access to repositories,
but does not allow users to delete repositories or change the policy documents applied to them.
{
"Version": "2012-10-17",
"Statement": [{
"Effect": "Allow",
"Action": [
"ecr:GetAuthorizationToken",
"ecr:BatchCheckLayerAvailability",
"ecr:GetDownloadUrlForLayer",
"ecr:GetRepositoryPolicy",
"ecr:DescribeRepositories",
"ecr:ListImages",
"ecr:DescribeImages",
"ecr:BatchGetImage",
"ecr:InitiateLayerUpload",
"ecr:UploadLayerPart",
"ecr:CompleteLayerUpload",
"ecr:PutImage"
],
"Resource": "*"
}]
}
AmazonEC2ContainerRegistryReadOnly
This policy allows read-only access to Amazon ECR, such as the ability to list repositories and the images
within the repositories, and also to pull images from Amazon ECR with the Docker CLI.
{
"Version": "2012-10-17",
"Statement": [{
"Effect": "Allow",
"Action": [
"ecr:GetAuthorizationToken",
"ecr:BatchCheckLayerAvailability",
"ecr:GetDownloadUrlForLayer",
"ecr:GetRepositoryPolicy",
"ecr:DescribeRepositories",
"ecr:ListImages",
"ecr:DescribeImages",
"ecr:BatchGetImage"
],
"Resource": "*"
}]
}
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Amazon ECS Container Instance IAM Role
The Amazon ECS container agent makes calls to the Amazon ECS API actions on your behalf, so container
instances that run the agent require an IAM policy and role for the service to know that the agent
belongs to you. Before you can launch container instances and register them into a cluster, you must
create an IAM role for those container instances to use when they are launched. This requirement applies
to container instances launched with the Amazon ECS-optimized AMI provided by Amazon, or with any
other instances that you intend to run the agent on.
Important
Containers that are running on your container instances have access to all of the permissions
that are supplied to the container instance role through instance metadata. We recommend
that you limit the permissions in your container instance role to the minimal list of permissions
provided in the managed AmazonEC2ContainerServiceforEC2Role policy shown below. If
the containers in your tasks need extra permissions that are not listed here, we recommend
providing those tasks with their own IAM roles. For more information, see IAM Roles for
Tasks (p. 216).
You can prevent containers on the docker0 bridge from accessing the permissions supplied to
the container instance role (while still allowing the permissions that are provided by IAM Roles
for Tasks (p. 216)) by running the following iptables command on your container instances;
however, containers will not be able to query instance metadata with this rule in effect. Note
that this command assumes the default Docker bridge configuration and it will not work for
containers that use the host network mode. For more information, see Network Mode (p. 99).
$ iptables --insert FORWARD 1 --in-interface docker+ --destination
169.254.169.254/32 --jump DROP
The AmazonEC2ContainerServiceforEC2Role policy is shown below.
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Action": [
"ecs:CreateCluster",
"ecs:DeregisterContainerInstance",
"ecs:DiscoverPollEndpoint",
"ecs:Poll",
"ecs:RegisterContainerInstance",
"ecs:StartTelemetrySession",
"ecs:Submit*",
"ecr:GetAuthorizationToken",
"ecr:BatchCheckLayerAvailability",
"ecr:GetDownloadUrlForLayer",
"ecr:BatchGetImage",
"logs:CreateLogStream",
"logs:PutLogEvents"
],
"Resource": "*"
}
]
}
Note
The ecs:CreateCluster line in the above policy is optional, provided that the cluster you intend
to register your container instance into already exists. If the cluster does not already exist, the
agent must have permission to create it, or you can create the cluster with the create-cluster
command prior to launching your container instance.
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If you omit the ecs:CreateCluster line, the Amazon ECS container agent will not be able to
create clusters, including the default cluster.
The ecs:Poll line in the above policy is used to grant the agent permission to connect with the Amazon
ECS service to report status and get commands.
The Amazon ECS instance role is automatically created for you in the console first-run experience;
however, you should manually attach the managed IAM policy for container instances to allow Amazon
ECS to add permissions for future features and enhancements as they are introduced. You can use the
following procedure to check and see if your account already has the Amazon ECS instance role and to
attach the managed IAM policy if needed.
To check for the ecsInstanceRole in the IAM console
1. Open the IAM console at https://console.aws.amazon.com/iam/.
2. In the navigation pane, choose Roles.
3. Search the list of roles for ecsInstanceRole. If the role does not exist, use the procedure below to
create the role. If the role does exist, select the role to view the attached policies.
4. Choose the Permissions tab.
5. In the Managed Policies section, ensure that the AmazonEC2ContainerServiceforEC2Role managed
policy is attached to the role. If the policy is attached, your Amazon ECS instance role is properly
configured. If not, follow the substeps below to attach the policy.
a. Choose Attach Policy.
b. In the Filter box, type AmazonEC2ContainerServiceforEC2Role to narrow the available policies
to attach.
c. Check the box to the left of the AmazonEC2ContainerServiceforEC2Role policy and choose
Attach Policy.
6. Choose the Trust Relationships tab, and Edit Trust Relationship.
7. Verify that the trust relationship contains the following policy. If the trust relationship matches the
policy below, choose Cancel. If the trust relationship does not match, copy the policy into the Policy
Document window and choose Update Trust Policy.
{
"Version": "2008-10-17",
"Statement": [
{
"Sid": "",
"Effect": "Allow",
"Principal": {
"Service": "ec2.amazonaws.com"
},
"Action": "sts:AssumeRole"
}
]
}
To create the ecsInstanceRole IAM role for your container instances
1. Open the IAM console at https://console.aws.amazon.com/iam/.
2. In the navigation pane, choose Roles and then choose Create New Role.
3. In the Role Name field, type ecsInstanceRole to name the role, and then choose Next Step.
4. In the Select Role Type section, choose Select next to the Amazon EC2 Role for EC2 Container
Service role.
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to your Container Instance Role
5. In the Attach Policy section, select the AmazonEC2ContainerServiceforEC2Role policy and then
choose Next Step.
6. Review your role information and then choose Create Role to finish.
Adding Amazon S3 Read-only Access to your
Container Instance Role
Storing configuration information in a private bucket in Amazon S3 and granting read-only access to
your container instance IAM role is a secure and convenient way to allow container instance configuration
at launch time. You can store a copy of your ecs.config file in a private bucket, use Amazon EC2 user
data to install the AWS CLI and then copy your configuration information to /etc/ecs/ecs.config when
the instance launches.
For more information about creating an ecs.config file, storing it in Amazon S3, and launching instances
with this configuration, see Storing Container Instance Configuration in Amazon S3 (p. 84).
To allow Amazon S3 read-only access for your container instance role
1. Open the IAM console at https://console.aws.amazon.com/iam/.
2. In the navigation pane, choose Roles.
3. Choose the IAM role you use for your container instances (this role is likely titled ecsInstanceRole).
For more information, see Amazon ECS Container Instance IAM Role (p. 210).
4. Choose the Permissions tab.
5. Under Managed Policies, choose Attach Policy.
6. On the Attach Policy page, type S3 into the Filter field to narrow the policy results.
7. Check the box to the left of the AmazonS3ReadOnlyAccess policy and click Attach Policy.
Note
This policy allows read-only access to all Amazon S3 resources. For more restrictive bucket
policy examples, see Bucket Policy Examples in the Amazon Simple Storage Service
Developer Guide.
Amazon ECS Service Scheduler IAM Role
The Amazon ECS service scheduler makes calls to the Amazon EC2 and Elastic Load Balancing APIs on
your behalf to register and deregister container instances with your load balancers. Before you can
attach a load balancer to an Amazon ECS service, you must create an IAM role for your services to use
before you start them. This requirement applies to any Amazon ECS service that you plan to use with a
load balancer.
In most cases, the Amazon ECS service role is created for you automatically in the console first-run
experience. You can use the following procedure to check if your account already has the Amazon ECS
service role.
The AmazonEC2ContainerServiceRole policy is shown below.
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
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"Action": [
"ec2:AuthorizeSecurityGroupIngress",
"ec2:Describe*",
"elasticloadbalancing:DeregisterInstancesFromLoadBalancer",
"elasticloadbalancing:DeregisterTargets",
"elasticloadbalancing:Describe*",
"elasticloadbalancing:RegisterInstancesWithLoadBalancer",
"elasticloadbalancing:RegisterTargets"
],
"Resource": "*"
}
]
}
Note
The ec2:AuthorizeSecurityGroupIngress rule is reserved for future use. Amazon ECS does not
automatically update the security groups associated with Elastic Load Balancing load balancers
or Amazon ECS container instances.
To check for the ecsServiceRole in the IAM console
1. Open the IAM console at https://console.aws.amazon.com/iam/.
2. In the navigation pane, choose Roles.
3. Search the list of roles for ecsServiceRole. If the role does not exist, use the procedure below to
create the role. If the role does exist, select the role to view the attached policies.
4. Choose the Permissions tab.
5. In the Managed Policies section, ensure that the AmazonEC2ContainerServiceRole managed policy
is attached to the role. If the policy is attached, your Amazon ECS service role is properly configured.
If not, follow the substeps below to attach the policy.
a. Choose Attach Policy.
b. In the Filter box, type AmazonEC2ContainerServiceRole to narrow the available policies to
attach.
c. Check the box to the left of the AmazonEC2ContainerServiceRole policy and choose Attach
Policy.
6. Choose the Trust Relationships tab, and Edit Trust Relationship.
7. Verify that the trust relationship contains the following policy. If the trust relationship matches the
policy below, choose Cancel. If the trust relationship does not match, copy the policy into the Policy
Document window and choose Update Trust Policy.
{
"Version": "2008-10-17",
"Statement": [
{
"Sid": "",
"Effect": "Allow",
"Principal": {
"Service": "ecs.amazonaws.com"
},
"Action": "sts:AssumeRole"
}
]
}
To create an IAM role for your service scheduler load balancers
1. Open the IAM console at https://console.aws.amazon.com/iam/.
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2. In the navigation pane, choose Roles and then choose Create New Role.
3. In the Role Name field, type ecsServiceRole to name the role, and then choose Next Step.
4. In the Select Role Type section, scroll down and choose Select next to the Amazon EC2 Container
Service Role service role.
5. In the Attach Policy section, select the AmazonEC2ContainerServiceRole policy and then choose
Next Step.
6. Review your role information and then choose Create Role to finish.
Amazon ECS Service Auto Scaling IAM Role
Before you can use Service Auto Scaling with Amazon ECS, the Application Auto Scaling service needs
permission to describe your CloudWatch alarms and registered services, as well as permission to update
your Amazon ECS service's desired count on your behalf. These permissions are provided by the Service
Auto Scaling IAM role (ecsAutoscaleRole).
Note
IAM users also require permissions to use Service Auto Scaling; these permissions are described
in Service Auto Scaling Required IAM Permissions (p. 153). If an IAM user has the required
permissions to use Service Auto Scaling in the Amazon ECS console, create IAM roles, and
attach IAM role policies to them, then that user can create this role automatically as part of the
Amazon ECS console create service (p. ) or update service (p. 165) workflows, and then use
the role for any other service later (in the console or with the CLI/SDKs).
You can use the following procedure to check and see if your account already has Service Auto Scaling.
The AmazonEC2ContainerServiceAutoscaleRole policy is shown below.
{
"Version": "2012-10-17",
"Statement": [
{
"Sid": "Stmt1456535218000",
"Effect": "Allow",
"Action": [
"ecs:DescribeServices",
"ecs:UpdateService"
],
"Resource": [
"*"
]
},
{
"Sid": "Stmt1456535243000",
"Effect": "Allow",
"Action": [
"cloudwatch:DescribeAlarms"
],
"Resource": [
"*"
]
}
]
}
To check for the Service Auto Scaling role in the IAM console
1. Open the IAM console at https://console.aws.amazon.com/iam/.
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2. In the navigation pane, choose Roles.
3. Search the list of roles for ecsAutoscaleRole. If the role does not exist, use the procedure below to
create the role. If the role does exist, select the role to view the attached policies.
4. Choose the Permissions tab.
5. In the Managed Policies section, ensure that the AmazonEC2ContainerServiceAutoscaleRole
managed policy is attached to the role. If the policy is attached, your Amazon ECS service role is
properly configured. If not, follow the substeps below to attach the policy.
a. Choose Attach Policy.
b. For Filter, type AmazonEC2ContainerServiceAutoscaleRole to narrow the available policies to
attach.
c. Select the box to the left of the AmazonEC2ContainerAutoscaleRole policy and choose Attach
Policy.
6. Choose Trust Relationships, Edit Trust Relationship.
7. Verify that the trust relationship contains the following policy. If the trust relationship matches the
policy below, choose Cancel. If the trust relationship does not match, copy the policy into the Policy
Document window and choose Update Trust Policy.
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Principal": {
"Service": "application-autoscaling.amazonaws.com"
},
"Action": "sts:AssumeRole"
}
]
}
To create an IAM role for Service Auto Scaling
1. Open the IAM console at https://console.aws.amazon.com/iam/.
2. In the navigation pane, choose Roles and then choose Create New Role.
3. In the Role Name field, type ecsAutoscaleRole to name the role, and then choose Next Step.
4. In the Select Role Type section, scroll down and choose Select next to the Amazon EC2 Container
Service Autoscale Role service role.
5. In the Attach Policy section, select the AmazonEC2ContainerServiceAutoscaleRole policy and then
choose Next Step.
6. Review your role information and then choose Create Role to finish.
Amazon EC2 Container Service Task Role
Before you can use IAM roles for tasks , Amazon ECS needs permission to make calls to the AWS APIs on
your behalf. These permissions are provided by the Amazon EC2 Container Service Task Role.
You can create a task IAM role for each task definition that needs permission to call AWS APIs. You
simply create an IAM policy that defines which permissions your task should have, and then attach
that policy to a role that uses the Amazon EC2 Container Service Task Role managed policy. For more
information, see Creating an IAM Role and Policy for your Tasks (p. 218).
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The Amazon EC2 Container Service Task Role trust relationship is shown below.
{
"Version": "2012-10-17",
"Statement": [
{
"Sid": "",
"Effect": "Allow",
"Principal": {
"Service": "ecs-tasks.amazonaws.com"
},
"Action": "sts:AssumeRole"
}
]
}
IAM Roles for Tasks
With IAM roles for Amazon ECS tasks, you can specify an IAM role that can be used by the containers in
a task. Applications must sign their AWS API requests with AWS credentials, and this feature provides
a strategy for managing credentials for your applications to use, similar to the way that Amazon EC2
instance profiles provide credentials to EC2 instances. Instead of creating and distributing your AWS
credentials to the containers or using the EC2 instance’s role, you can associate an IAM role with an ECS
task definition or RunTask API operation. The applications in the task’s containers can then use the AWS
SDK or CLI to make API requests to authorized AWS services.
Important
Containers that are running on your container instances have access to all of the permissions
that are supplied to the container instance role. We recommend that you limit the permissions
in your container instance role to the minimal list of permissions shown in Amazon ECS
Container Instance IAM Role (p. 210).
You can prevent containers on the docker0 bridge from accessing the permissions supplied to
the container instance role (while still allowing the permissions that are provided by IAM roles
for tasks) by running the following iptables command on your container instances; however,
containers will not be able to query instance metadata with this rule in effect. Note that this
command assumes the default Docker bridge configuration and it will not work for containers
that use the host network mode. For more information, see Network Mode (p. 99).
$ iptables --insert FORWARD 1 --in-interface docker+ --destination
169.254.169.254/32 --jump DROP
You define the IAM role to use in your task definitions, or you can use a taskRoleArn override when
running a task manually with the RunTask API operation. The Amazon ECS agent receives a payload
message for starting the task with additional fields that contain the role credentials. The Amazon ECS
agent sets the task’s UUID as an identification token and updates its internal credential cache so that
the identification token for the task points to the role credentials that are received in the payload. The
Amazon ECS agent populates the AWS_CONTAINER_CREDENTIALS_RELATIVE_URI environment variable in
the Env object (available with the docker inspect container_id command) for all containers that belong
to this task with the following relative URI: /credential_provider_version/credentials?id=task_UUID.
From inside the container, you can query the credentials with the following command:
[ec2-user ~]$ curl 169.254.170.2$AWS_CONTAINER_CREDENTIALS_RELATIVE_URI
Output:
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{
"AccessKeyId": "ACCESS_KEY_ID",
"Expiration": "EXPIRATION_DATE",
"RoleArn": "TASK_ROLE_ARN",
"SecretAccessKey": "SECRET_ACCESS_KEY",
"Token": "SECURITY_TOKEN_STRING"
}
If your container instance is using at least version 1.11.0 of the container agent and a supported version
of the AWS CLI or SDKs, then the SDK client will see that the AWS_CONTAINER_CREDENTIALS_RELATIVE_URI
variable is available, and it will use the provided credentials to make calls to the AWS APIs. For more
information, see Enabling Task IAM Roles on your Container Instances (p. 217) and Using a Supported
AWS SDK (p. 219).
Each time the credential provider is used, the request is logged locally on the host container instance at /
var/log/ecs/audit.log.YYYY-MM-DD-HH. For more information, see IAM Roles for Tasks Credential Audit
Log (p. 281).
Topics
•Benefits of Using IAM Roles for Tasks (p. 217)
•Enabling Task IAM Roles on your Container Instances (p. 217)
•Creating an IAM Role and Policy for your Tasks (p. 218)
•Using a Supported AWS SDK (p. 219)
•Specifying an IAM Role for your Tasks (p. 219)
Benefits of Using IAM Roles for Tasks
•Credential Isolation: A container can only retrieve credentials for the IAM role that is defined in the
task definition to which it belongs; a container never has access to credentials that are intended for
another container that belongs to another task.
•Authorization: Unauthorized containers cannot access IAM role credentials defined for other tasks.
•Auditability: Access and event logging is available through CloudTrail to ensure retrospective auditing.
Task credentials have a context of taskArn that is attached to the session, so CloudTrail logs show
which task is using which role.
Enabling Task IAM Roles on your Container Instances
Your Amazon ECS container instances require at least version 1.11.0 of the container agent to enable
task IAM roles; however, we recommend using the latest container agent version. For information about
checking your agent version and updating to the latest version, see Updating the Amazon ECS Container
Agent (p. 73). If you are using the Amazon ECS-optimized AMI, your instance needs at least 1.11.0-1 of
the ecs-init package. If your container instances are launched from version 2016.03.e or later, then
they contain the required versions of the container agent and ecs-init. For more information, see
Amazon ECS-Optimized AMI (p. 34).
If you are not using the Amazon ECS-optimized AMI for your container instances, be sure to add the
--net=host option to your docker run command that starts the agent and the appropriate agent
configuration variables for your desired configuration (for more information, see Amazon ECS Container
Agent Configuration (p. 79)):
ECS_ENABLE_TASK_IAM_ROLE=true
Enables IAM roles for tasks for containers with the bridge and default network modes.
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Creating an IAM Role and Policy for your Tasks
ECS_ENABLE_TASK_IAM_ROLE_NETWORK_HOST=true
Enables IAM roles for tasks for containers with the host network mode. This variable is only
supported on agent versions 1.12.0 and later.
For an example run command, see Manually Updating the Amazon ECS Container Agent (for Non-
Amazon ECS-optimized AMIs) (p. 77). You will also need to set the following networking commands on
your container instance so that the containers in your tasks can retrieve their AWS credentials:
[ec2-user ~]$ sysctl -w net.ipv4.conf.all.route_localnet=1
[ec2-user ~]$ iptables -t nat -A PREROUTING -p tcp -d 169.254.170.2 --dport 80 -j DNAT --
to-destination 127.0.0.1:51679
[ec2-user ~]$ iptables -t nat -A OUTPUT -d 169.254.170.2 -p tcp -m tcp --dport 80 -j
REDIRECT --to-ports 51679
Creating an IAM Role and Policy for your Tasks
You must create an IAM policy for your tasks to use that specifies the permissions that you would like
the containers in your tasks to have. You have several ways to create a new IAM permission policy. You
can copy a complete AWS managed policy that already does some of what you're looking for and then
customize it to your specific requirements. For more information, see Creating a New Policy in the IAM
User Guide.
You must also create a role for your tasks to use before you can specify it in your task definitions. You
can create the role using the Amazon EC2 Container Service Task Role service role in the IAM console.
Then you can attach your specific IAM policy to the role that gives the containers in your task the
permissions you desire. The procedures below describe how to do this.
If you have multiple task definitions or services that require IAM permissions, you should consider
creating a role for each specific task definition or service with the minimum required permissions for the
tasks to operate so that you can minimize the access that you provide for each task.
To create an IAM policy for your tasks
In this example, we create a policy to allow read-only access to an Amazon S3 bucket. You could
store database credentials or other secrets in this bucket, and the containers in your task can read the
credentials from the bucket and load them into your application.
1. Open the IAM console at https://console.aws.amazon.com/iam/.
2. In the navigation pane, choose Policies and then choose Create Policy.
3. In the Create Policy section, choose Select next to Create Your Own Policy.
4. In the Policy Name field, type your own unique name, such as AmazonECSTaskS3BucketPolicy.
5. In the Policy Document field, paste the policy to apply to your tasks. The example below allows
permission to the my-task-secrets-bucket Amazon S3 bucket. You can modify the policy document
to suit your specific needs.
{
"Version": "2012-10-17",
"Statement": [
{
"Sid": "Stmt1465589882000",
"Effect": "Allow",
"Action": [
"s3:GetObject"
],
"Resource": [
"arn:aws:s3:::my-task-secrets-bucket/*"
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Using a Supported AWS SDK
]
}
]
}
6. Choose Create Policy to finish.
To create an IAM role for your tasks
1. Open the IAM console at https://console.aws.amazon.com/iam/.
2. In the navigation pane, choose Roles and then choose Create New Role.
3. In the Role Name field, enter a name for your role. For this example, type
AmazonECSTaskS3BucketRole to name the role, and then choose Next Step.
4. In the Select Role Type section, choose Select next to the Amazon EC2 Container Service Task Role
service role.
5. In the Attach Policy section, select the policy you want to use for your tasks (in this example
AmazonECSTaskS3BucketPolicy, and then choose Next Step.
6. Review your role information and then choose Create Role to finish.
Using a Supported AWS SDK
Support for IAM roles for tasks was added to the AWS SDKs on July 13th, 2016, so the containers in your
tasks must use an AWS SDK version that was created on or after that date. AWS SDKs that are included in
Linux distribution package managers may not be new enough to support this feature.
To ensure that you are using a supported SDK, follow the installation instructions for your preferred SDK
at Tools for Amazon Web Services when you are building your containers.
The following AWS SDK versions and above support IAM roles for tasks:
• AWS CLI: 1.10.47
• C++: 0.12.19
• CoreCLR: 3.2.6-beta
• Go: 1.2.5
• Java: 1.11.16
• .NET: 3.1.6
• Node.js: 2.4.7
• PHP: 3.18.28
• Python (botocore): 1.4.37
• Python (Boto3): 1.4.0
Note
The botocore module provides the low-level core functionality for Boto3, and each version
of Boto3 supports a range of botocore module versions. For Boto3 support of IAM roles for
tasks, you must ensure that your underlying botocore module is at least the minimum version
shown above.
• Ruby: 2.3.22
Specifying an IAM Role for your Tasks
After you have created a role and attached a policy to that role, you can run tasks that assume the role.
You have several options to do this:
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Amazon ECS IAM Policy Examples
• Specify an IAM role for your tasks in the task definition. You can create a new task definition or a new
revision of an existing task definition and specify the role you created previously. If you use the console
to create your task definition, choose your IAM role in the Task Role field. If you use the AWS CLI or
SDKs, specify your task role ARN using the taskRoleArn parameter. For more information, see Creating
a Task Definition (p. 95).
Note
This option is required if you want to use IAM task roles in an Amazon ECS service.
• Specify an IAM task role override when running a task. You can specify an IAM task role override
when running a task. If you use the console to run your task, choose Advanced Options and then
choose your IAM role in the Task Role field. If you use the AWS CLI or SDKs, specify your task role ARN
using the taskRoleArn parameter in the overrides JSON object. For more information, see Running
Tasks (p. 127).
Note
In addition to the standard Amazon ECS permissions required to run tasks and services, IAM
users also require iam:PassRole permissions to use IAM roles for tasks.
Amazon ECS IAM Policy Examples
The following examples show policy statements that you could use to control the permissions that IAM
users have to Amazon ECS.
Topics
•Amazon ECS First Run Wizard (p. 220)
•Clusters (p. 222)
•Container Instances (p. 223)
•Task Definitions (p. 224)
•Run Tasks (p. 225)
•Start Tasks (p. 225)
•List and Describe Tasks (p. 226)
•Create Services (p. 226)
•Update Services (p. 227)
Amazon ECS First Run Wizard
The Amazon ECS first run wizard simplifies the process of creating a cluster and running your tasks and
services. However, users require permissions to many API operations from multiple AWS services to
complete the wizard. The policy below shows the required permissions to complete the Amazon ECS first
run wizard.
Note
If you want to create an Amazon ECR repository in the first run wizard, tag and push an image
to that repository, and use that image in an Amazon ECS task definition, then your user also
needs the permissions listed in the AmazonEC2ContainerRegistryFullAccess managed policy.
For more information, see Amazon ECR Managed Policies (p. 208).
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
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"Action": [
"autoscaling:CreateAutoScalingGroup",
"autoscaling:CreateLaunchConfiguration",
"autoscaling:CreateOrUpdateTags",
"autoscaling:DeleteAutoScalingGroup",
"autoscaling:DeleteLaunchConfiguration",
"autoscaling:DescribeAutoScalingGroups",
"autoscaling:DescribeAutoScalingInstances",
"autoscaling:DescribeAutoScalingNotificationTypes",
"autoscaling:DescribeLaunchConfigurations",
"autoscaling:DescribeScalingActivities",
"autoscaling:DescribeTags",
"autoscaling:DescribeTriggers",
"autoscaling:UpdateAutoScalingGroup",
"cloudformation:CreateStack",
"cloudformation:DescribeStack*",
"cloudformation:DeleteStack",
"cloudformation:UpdateStack",
"cloudwatch:GetMetricStatistics",
"cloudwatch:ListMetrics",
"ec2:AssociateRouteTable",
"ec2:AttachInternetGateway",
"ec2:AuthorizeSecurityGroupIngress",
"ec2:CreateInternetGateway",
"ec2:CreateKeyPair",
"ec2:CreateNetworkInterface",
"ec2:CreateRoute",
"ec2:CreateRouteTable",
"ec2:CreateSecurityGroup",
"ec2:CreateSubnet",
"ec2:CreateTags",
"ec2:CreateVpc",
"ec2:DeleteInternetGateway",
"ec2:DeleteRoute",
"ec2:DeleteRouteTable",
"ec2:DeleteSecurityGroup",
"ec2:DeleteSubnet",
"ec2:DeleteTags",
"ec2:DeleteVpc",
"ec2:DescribeAccountAttributes",
"ec2:DescribeAvailabilityZones",
"ec2:DescribeInstances",
"ec2:DescribeInternetGateways",
"ec2:DescribeKeyPairs",
"ec2:DescribeNetworkInterface",
"ec2:DescribeRouteTables",
"ec2:DescribeSecurityGroups",
"ec2:DescribeSubnets",
"ec2:DescribeTags",
"ec2:DescribeVpcAttribute",
"ec2:DescribeVpcs",
"ec2:DetachInternetGateway",
"ec2:DisassociateRouteTable",
"ec2:ModifyVpcAttribute",
"ec2:RunInstances",
"ec2:TerminateInstances",
"ecr:*",
"ecs:*",
"elasticloadbalancing:ApplySecurityGroupsToLoadBalancer",
"elasticloadbalancing:AttachLoadBalancerToSubnets",
"elasticloadbalancing:ConfigureHealthCheck",
"elasticloadbalancing:CreateLoadBalancer",
"elasticloadbalancing:DeleteLoadBalancer",
"elasticloadbalancing:DeleteLoadBalancerListeners",
"elasticloadbalancing:DeleteLoadBalancerPolicy",
"elasticloadbalancing:DeregisterInstancesFromLoadBalancer",
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"elasticloadbalancing:DescribeInstanceHealth",
"elasticloadbalancing:DescribeLoadBalancerAttributes",
"elasticloadbalancing:DescribeLoadBalancerPolicies",
"elasticloadbalancing:DescribeLoadBalancerPolicyTypes",
"elasticloadbalancing:DescribeLoadBalancers",
"elasticloadbalancing:ModifyLoadBalancerAttributes",
"elasticloadbalancing:SetLoadBalancerPoliciesOfListener",
"iam:AttachRolePolicy",
"iam:CreateRole",
"iam:GetPolicy",
"iam:GetPolicyVersion",
"iam:GetRole",
"iam:ListAttachedRolePolicies",
"iam:ListInstanceProfiles",
"iam:ListRoles",
"iam:ListGroups",
"iam:ListUsers",
"iam:CreateInstanceProfile",
"iam:AddRoleToInstanceProfile",
"iam:ListInstanceProfilesForRole"
],
"Resource": "*"
}
]
}
Clusters
The following IAM policy allows permission to create and list clusters. The CreateCluster and
ListClusters actions do not accept any resources, so the resource definition is set to * for all resources.
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Action": [
"ecs:CreateCluster",
"ecs:ListClusters"
],
"Resource": [
"*"
]
}
]
}
The following IAM policy allows permission to describe and delete a specific cluster. The
DescribeCluster and DeleteCluster actions accept cluster ARNs as resources.
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Action": [
"ecs:DescribeCluster",
"ecs:DeleteCluster"
],
"Resource": [
"arn:aws:ecs:us-east-1:<aws_account_id>:cluster/<cluster_name>"
]
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Container Instances
}
]
}
The following IAM policy can be attached to a user or group that would only allow that user or group to
perform operations on a specific cluster.
{
"Version": "2012-10-17",
"Statement": [
{
"Action": [
"ecs:Describe*",
"ecs:List*"
],
"Effect": "Allow",
"Resource": "*"
},
{
"Action": [
"ecs:DeleteCluster",
"ecs:DeregisterContainerInstance",
"ecs:ListContainerInstances",
"ecs:RegisterContainerInstance",
"ecs:SubmitContainerStateChange",
"ecs:SubmitTaskStateChange"
],
"Effect": "Allow",
"Resource": "arn:aws:ecs:us-east-1:<aws_account_id>:cluster/default"
},
{
"Action": [
"ecs:DescribeContainerInstances",
"ecs:DescribeTasks",
"ecs:ListTasks",
"ecs:UpdateContainerAgent",
"ecs:StartTask",
"ecs:StopTask",
"ecs:RunTask"
],
"Effect": "Allow",
"Resource": "*",
"Condition": {
"ArnEquals": {
"ecs:cluster": "arn:aws:ecs:us-east-1:<aws_account_id>:cluster/default"
}
}
}
]
}
Container Instances
Container instance registration is handled by the Amazon ECS agent, but there may be times where you
want to allow a user to deregister an instance manually from a cluster. Perhaps the container instance
was accidentally registered to the wrong cluster, or the instance was terminated with tasks still running
on it.
The following IAM policy allows a user to list and deregister container instances in a specified cluster:
{
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Task Definitions
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Action": [
"ecs:DeregisterContainerInstance",
"ecs:ListContainerInstances"
],
"Resource": [
"arn:aws:ecs:<region>:<aws_account_id>:cluster/<cluster_name>"
]
}
]
}
The following IAM policy allows a user to describe a specified container instance in a specified cluster.
To open this permission up to all container instances in a cluster, you can replace the container instance
UUID with *.
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Action": [
"ecs:DescribeContainerInstance"
],
"Condition": {
"ArnEquals": {
"ecs:cluster": "arn:aws:ecs:<region>:<aws_account_id>:cluster/<cluster_name>"
}
},
"Resource": [
"arn:aws:ecs:<region>:<aws_account_id>:container-instance/
<container_instance_UUID>"
]
}
]
}
Task Definitions
Task definition IAM policies do not support resource-level permissions, but the following IAM policy
allows a user to register, list, and describe task definitions:
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Action": [
"ecs:RegisterTaskDefinition",
"ecs:ListTaskDefinitions",
"ecs:DescribeTaskDefinition"
],
"Resource": [
"*"
]
}
]
}
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Run Tasks
Run Tasks
The resources for RunTask are task definitions. To limit which clusters a user can run task definitions
on, you can specify them in the Condition block. The advantage is that you don't have to list both task
definitions and clusters in your resources to allow appropriate access. You can apply one, the other, or
both.
The following IAM policy allows permission to run any revision of a specific task definition on a specific
cluster:
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Action": [
"ecs:RunTask"
],
"Condition": {
"ArnEquals": {
"ecs:cluster": "arn:aws:ecs:<region>:<aws_account_id>:cluster/<cluster_name>"
}
},
"Resource": [
"arn:aws:ecs:<region>:<aws_account_id>:task-definition/<task_family>:*"
]
}
]
}
Start Tasks
The resources for StartTask are task definitions. To limit which clusters and container instances a user
can start task definitions on, you can specify them in the Condition block. The advantage is that you
don't have to list both task definitions and clusters in your resources to allow appropriate access. You can
apply one, the other, or both.
The following IAM policy allows permission to start any revision of a specific task definition on a specific
cluster and specific container instance:
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Action": [
"ecs:StartTask"
],
"Condition": {
"ArnEquals": {
"ecs:cluster": "arn:aws:ecs:<region>:<aws_account_id>:cluster/<cluster_name>",
"ecs:container-instances" : [
"arn:aws:ecs:<region>:<aws_account_id>:container-instance/
<container_instance_UUID>"
]
}
},
"Resource": [
"arn:aws:ecs:<region>:<aws_account_id>:task-definition/<task_family>:*"
]
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List and Describe Tasks
}
]
}
List and Describe Tasks
The following IAM policy allows a user to list tasks for a specified cluster:
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Action": [
"ecs:ListTasks"
],
"Condition": {
"ArnEquals": {
"ecs:cluster": "arn:aws:ecs:<region>:<aws_account_id>:cluster/<cluster_name>"
}
},
"Resource": [
"*"
]
}
]
}
The following IAM policy allows a user to describe a specified task in a specified cluster:
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Action": [
"ecs:DescribeTask"
],
"Condition": {
"ArnEquals": {
"ecs:cluster": "arn:aws:ecs:<region>:<aws_account_id>:cluster/<cluster_name>"
}
},
"Resource": [
"arn:aws:ecs:<region>:<aws_account_id>:task/<task_UUID>"
]
}
]
}
Create Services
The following IAM policy allows a user to create Amazon ECS services in the AWS Management Console:
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Action": [
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Update Services
"application-autoscaling:Describe*",
"application-autoscaling:PutScalingPolicy",
"application-autoscaling:RegisterScalableTarget",
"cloudwatch:DescribeAlarms",
"cloudwatch:PutMetricAlarm",
"ecs:List*",
"ecs:Describe*",
"ecs:CreateService",
"elasticloadbalancing:Describe*",
"iam:AttachRolePolicy",
"iam:CreateRole",
"iam:GetPolicy",
"iam:GetPolicyVersion",
"iam:GetRole",
"iam:ListAttachedRolePolicies",
"iam:ListRoles",
"iam:ListGroups",
"iam:ListUsers"
],
"Resource": [
"*"
]
}
]
}
Update Services
The following IAM policy allows a user to update Amazon ECS services in the AWS Management Console:
{
"Version": "2012-10-17",
"Statement": [
{
"Effect": "Allow",
"Action": [
"application-autoscaling:Describe*",
"application-autoscaling:PutScalingPolicy",
"application-autoscaling:DeleteScalingPolicy",
"application-autoscaling:RegisterScalableTarget",
"cloudwatch:DescribeAlarms",
"cloudwatch:PutMetricAlarm",
"ecs:List*",
"ecs:Describe*",
"ecs:UpdateService",
"iam:AttachRolePolicy",
"iam:CreateRole",
"iam:GetPolicy",
"iam:GetPolicyVersion",
"iam:GetRole",
"iam:ListAttachedRolePolicies",
"iam:ListRoles",
"iam:ListGroups",
"iam:ListUsers"
],
"Resource": [
"*"
]
}
]
}
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Installing the Amazon ECS CLI
Using the Amazon ECS Command
Line Interface
The Amazon EC2 Container Service (Amazon ECS) command line interface (CLI) provides high-level
commands to simplify creating, updating, and monitoring clusters and tasks from a local development
environment. The Amazon ECS CLI supports Docker Compose, a popular open-source tool for defining
and running multi-container applications. Use the CLI as part of your everyday development and testing
cycle as an alternative to the AWS Management Console.
Note
The source code for the Amazon ECS CLI is available on GitHub. We encourage you to submit
pull requests for changes that you would like to have included. However, Amazon Web Services
does not currently provide support for running modified copies of this software.
Topics
•Installing the Amazon ECS CLI (p. 228)
•Configuring the Amazon ECS CLI (p. 229)
•Amazon ECS CLI Tutorial (p. 230)
•Amazon ECS Command Line Reference (p. 235)
Installing the Amazon ECS CLI
Follow these instructions to install the Amazon ECS CLI on your Mac OSX or Linux system.
Note
The Amazon ECS CLI is not available for Windows systems at this time.
To install the Amazon ECS CLI
1. Download the binary.
• For Mac OSX:
$ sudo curl -o /usr/local/bin/ecs-cli https://s3.amazonaws.com/amazon-ecs-cli/ecs-
cli-darwin-amd64-latest
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Configuring the Amazon ECS CLI
• For Linux systems:
$ sudo curl -o /usr/local/bin/ecs-cli https://s3.amazonaws.com/amazon-ecs-cli/ecs-
cli-linux-amd64-latest
2. (Optional) Verify the downloaded binary with the MD5 sum provided.
• For Mac OSX: https://s3.amazonaws.com/amazon-ecs-cli/ecs-cli-darwin-amd64-latest.md5
• For Linux systems: https://s3.amazonaws.com/amazon-ecs-cli/ecs-cli-linux-amd64-latest.md5
3. Apply execute permissions to the binary.
$ sudo chmod +x /usr/local/bin/ecs-cli
4. Verify that the CLI is working properly.
ecs-cli --version
Output:
ecs-cli version 0.4.1 (e27df48)
After you have installed the CLI, proceed to Configuring the Amazon ECS CLI (p. 229).
Configuring the Amazon ECS CLI
The Amazon ECS CLI requires some basic configuration information before you can use it, such as your
AWS credentials, the AWS region in which to create your cluster, and the name of the Amazon ECS
cluster to use with the ecs-cli configure command. These settings are stored in the ~/.ecs/config file.
AWS Credentials
The Amazon ECS CLI requires your AWS credentials to make calls to AWS APIs on your behalf (for more
information, see Managing Access Keys for your AWS Account in the Amazon Web Services General
Reference). You can configure your AWS credentials in several ways:
• You can set the AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY environment variables. When you run
ecs-cli configure, the values of those variables are stored in the Amazon ECS CLI configuration file.
• You can use a named profile from the ~/.aws/credentials file on your system, if you have previously
configured your AWS credentials there for another tool, such as the AWS CLI. You can follow the Quick
Configuration instructions in the AWS Command Line Interface User Guide to set up a default profile if
you have not already done so. You can then pass this named profile as --profile default when you
run the ecs-cli configure command.
• You can pass credentials directly on the command line with the --access-key and --secret-key
options.
To configure the Amazon ECS CLI
• Configure the CLI with the following command, substituting us-west-2 with your desired AWS
region, ecs-cli-demo with the name of an existing Amazon ECS cluster or a new cluster to use,
and the $AWS_ACCESS_KEY_ID and $AWS_SECRET_ACCESS_KEY environment variables with your AWS
credentials.
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ecs-cli configure --region us-west-2 --access-key $AWS_ACCESS_KEY_ID --secret-
key $AWS_SECRET_ACCESS_KEY --cluster ecs-cli-demo
Output:
INFO[0000] Saved ECS CLI configuration for cluster (ecs-cli-demo)
After you have installed and configured the CLI, you can try the Amazon ECS CLI Tutorial (p. 230). For
more information, see the Amazon ECS Command Line Reference (p. 235).
Amazon ECS CLI Tutorial
This simple tutorial shows a few of the different commands and capabilities of the Amazon ECS
CLI. Before you can start this tutorial, you must install and configure the Amazon ECS CLI. For more
information, see Installing the Amazon ECS CLI (p. 228).
Topics
•Step 1: Create your Cluster (p. 230)
•Step 2: Create a Compose File (p. 231)
•Step 3: Deploy the Compose File to a Cluster (p. 232)
•Step 4: View the Running Containers on a Cluster (p. 232)
•Step 5: Scale the Tasks on a Cluster (p. 233)
•Step 6: Create an ECS Service from a Compose File (p. 233)
•Step 7: Clean Up (p. 234)
Step 1: Create your Cluster
The first action you should take is to create a cluster of Amazon ECS container instances that you can
launch your containers on with the ecs-cli up command. There are many options that you can choose
to configure your cluster with this command, but most of them are optional. In this example, you create
a simple cluster of two t2.medium container instances that use the id_rsa key pair for SSH access
(substitute your own key pair here).
By default, the security group created for your container instances opens port 80 for inbound traffic. You
can use the --port option to specify a different port to open, or if you have more complicated security
group requirements, you can specify an existing security group to use with the --security-group option.
ecs-cli up --keypair id_rsa --capability-iam --size 2 --instance-type t2.medium
Output:
INFO[0000] Created cluster cluster=ecs-cli-demo
INFO[0000] Waiting for your cluster resources to be created
INFO[0001] Cloudformation stack status stackStatus=CREATE_IN_PROGRESS
INFO[0061] Cloudformation stack status stackStatus=CREATE_IN_PROGRESS
INFO[0121] Cloudformation stack status stackStatus=CREATE_IN_PROGRESS
INFO[0182] Cloudformation stack status stackStatus=CREATE_IN_PROGRESS
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Step 2: Create a Compose File
This command may take a few minutes to complete as your resources are created. Now that you have a
cluster, you can create a Docker compose file and deploy it.
Step 2: Create a Compose File
For this step, create a simple Docker compose file that creates a WordPress application consisting of
a web server and a MySQL database. At this time, the Amazon ECS CLI supports Docker compose file
syntax versions 1 and 2.
The following parameters are supported in compose files for the Amazon ECS CLI:
•command
•cpu_shares
•dns
•dns_search
•entrypoint
•environment: If an environment variable value is not specified in the compose file, but it exists in the
shell environment, the shell environment variable value is passed to the task definition that is created
for any associated tasks or services.
Important
We do not recommend using plaintext environment variables for sensitive information, such
as credential data.
•env_file
Important
We do not recommend using plaintext environment variables for sensitive information, such
as credential data.
•extra_hosts
•hostname
•image
•labels
•links
•log_driver
•log_opt
•mem_limit (in bytes)
•ports
•privileged
•read_only
•security_opt
•ulimits
•user
•volumes
•volumes_from
•working_dir
Important
The build directive is not supported at this time.
For more information about Docker compose file syntax, see the Compose file reference in the Docker
documentation.
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Step 3: Deploy the Compose File to a Cluster
Here is the compose file, which you can call hello-world.yml. Each container has 100 CPU units and 500
MiB of memory. The wordpress container exposes port 80 to the container instance for inbound traffic to
the web server.
version: '2'
services:
wordpress:
image: wordpress
cpu_shares: 100
mem_limit: 524288000
ports:
- "80:80"
links:
- mysql
mysql:
image: mysql
cpu_shares: 100
mem_limit: 524288000
environment:
MYSQL_ROOT_PASSWORD: password
Step 3: Deploy the Compose File to a Cluster
After you create the compose file, you can deploy it to your cluster with the ecs-cli compose up
command. By default, the command looks for a file called docker-compose.yml in the current directory,
but you can specify a different file with the --file option. By default, the resources created by this
command have the current directory in the title, but you can override that with the --project-name
project_name option.
ecs-cli compose --file hello-world.yml up
Output:
INFO[0000] Using ECS task definition TaskDefinition=ecscompose-docker-
compose:2
INFO[0000] Starting container... container=340488e0-a307-4322-
b41c-99f1b70e97f9/wordpress
INFO[0000] Starting container... container=340488e0-a307-4322-
b41c-99f1b70e97f9/mysql
INFO[0000] Describe ECS container status container=340488e0-
a307-4322-b41c-99f1b70e97f9/wordpress desiredStatus=RUNNING lastStatus=PENDING
taskDefinition=ecscompose-docker-compose:2
INFO[0000] Describe ECS container status container=340488e0-a307-4322-
b41c-99f1b70e97f9/mysql desiredStatus=RUNNING lastStatus=PENDING taskDefinition=ecscompose-
docker-compose:2
INFO[0054] Started container... container=340488e0-
a307-4322-b41c-99f1b70e97f9/wordpress desiredStatus=RUNNING lastStatus=RUNNING
taskDefinition=ecscompose-docker-compose:2
INFO[0054] Started container... container=340488e0-a307-4322-
b41c-99f1b70e97f9/mysql desiredStatus=RUNNING lastStatus=RUNNING taskDefinition=ecscompose-
docker-compose:2
Step 4: View the Running Containers on a Cluster
After you deploy the compose file, you can view the containers that are running on your cluster with the
ecs-cli ps command.
ecs-cli ps
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Output:
Name State Ports
TaskDefinition
340488e0-a307-4322-b41c-99f1b70e97f9/wordpress RUNNING 52.89.204.137:80->80/tcp
ecscompose-docker-compose:2
340488e0-a307-4322-b41c-99f1b70e97f9/mysql RUNNING
ecscompose-docker-compose:2
In the above example, you can see the wordpress and mysql containers from your compose file, and also
the IP address and port of the web server. If you point a web browser to that address, you should see the
WordPress installation wizard.
Step 5: Scale the Tasks on a Cluster
You can scale your task count up so you could have more instances of your application with the ecs-cli
compose scale command. In this example, you can increase the count of your application to two.
ecs-cli compose --file hello-world.yml scale 2
Now you should see two more containers in your cluster.
ecs-cli ps
Output:
Name State Ports
TaskDefinition
340488e0-a307-4322-b41c-99f1b70e97f9/wordpress RUNNING 52.89.204.137:80->80/tcp
ecscompose-docker-compose:2
340488e0-a307-4322-b41c-99f1b70e97f9/mysql RUNNING
ecscompose-docker-compose:2
f80d82d5-3724-4f2f-86b1-5ee5891ce995/mysql RUNNING
ecscompose-docker-compose:2
f80d82d5-3724-4f2f-86b1-5ee5891ce995/wordpress RUNNING 52.89.205.89:80->80/tcp
ecscompose-docker-compose:2
Step 6: Create an ECS Service from a Compose File
Now that you know that your containers work properly, you can make sure that they are replaced if
they fail or stop. You can do this by creating a service from your compose file with the ecs-cli compose
service up command. This command creates a task definition from the latest compose file (if it does not
already exist) and creates an ECS service with it, with a desired count of 1.
Before starting your service, stop the containers from your compose file with the ecs-cli compose down
command so that you have an empty cluster to work with.
ecs-cli compose --file hello-world.yml down
Output:
INFO[0000] Stopping container... container=340488e0-a307-4322-
b41c-99f1b70e97f9/wordpress
INFO[0000] Stopping container... container=340488e0-a307-4322-
b41c-99f1b70e97f9/mysql
INFO[0000] Stopping container...
container=f80d82d5-3724-4f2f-86b1-5ee5891ce995/mysql
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INFO[0000] Stopping container...
container=f80d82d5-3724-4f2f-86b1-5ee5891ce995/wordpress
INFO[0000] Describe ECS container status
container=f80d82d5-3724-4f2f-86b1-5ee5891ce995/mysql desiredStatus=STOPPED
lastStatus=RUNNING taskDefinition=ecscompose-docker-compose:2
INFO[0000] Describe ECS container status
container=f80d82d5-3724-4f2f-86b1-5ee5891ce995/wordpress desiredStatus=STOPPED
lastStatus=RUNNING taskDefinition=ecscompose-docker-compose:2
INFO[0000] Describe ECS container status container=340488e0-
a307-4322-b41c-99f1b70e97f9/wordpress desiredStatus=STOPPED lastStatus=RUNNING
taskDefinition=ecscompose-docker-compose:2
INFO[0000] Describe ECS container status container=340488e0-a307-4322-
b41c-99f1b70e97f9/mysql desiredStatus=STOPPED lastStatus=RUNNING taskDefinition=ecscompose-
docker-compose:2
INFO[0006] Stopped container... container=340488e0-
a307-4322-b41c-99f1b70e97f9/wordpress desiredStatus=STOPPED lastStatus=STOPPED
taskDefinition=ecscompose-docker-compose:2
INFO[0006] Stopped container... container=340488e0-a307-4322-
b41c-99f1b70e97f9/mysql desiredStatus=STOPPED lastStatus=STOPPED taskDefinition=ecscompose-
docker-compose:2
INFO[0006] Stopped container...
container=f80d82d5-3724-4f2f-86b1-5ee5891ce995/mysql desiredStatus=STOPPED
lastStatus=STOPPED taskDefinition=ecscompose-docker-compose:2
INFO[0006] Stopped container...
container=f80d82d5-3724-4f2f-86b1-5ee5891ce995/wordpress desiredStatus=STOPPED
lastStatus=STOPPED taskDefinition=ecscompose-docker-compose:2
Now you can create your service.
ecs-cli compose --file hello-world.yml service up
Output:
INFO[0000] Using ECS task definition TaskDefinition=ecscompose-docker-
compose:2
INFO[0000] Created an ECS Service serviceName=ecscompose-service-
docker-compose taskDefinition=ecscompose-docker-compose:2
INFO[0000] Updated ECS service successfully desiredCount=1
serviceName=ecscompose-service-docker-compose
INFO[0000] Describe ECS Service status desiredCount=1 runningCount=0
serviceName=ecscompose-service-docker-compose
INFO[0015] ECS Service has reached a stable state desiredCount=1 runningCount=1
serviceName=ecscompose-service-docker-compose
Step 7: Clean Up
When you are done with this tutorial, you should clean up your resources so they do not incur any more
charges. First, delete the service so that it stops the existing containers and does not try to run any more
tasks.
ecs-cli compose --file hello-world.yml service rm
Output:
INFO[0000] Updated ECS service successfully desiredCount=0
serviceName=ecscompose-service-docker-compose
INFO[0000] Describe ECS Service status desiredCount=0 runningCount=1
serviceName=ecscompose-service-docker-compose
INFO[0015] ECS Service has reached a stable state desiredCount=0 runningCount=0
serviceName=ecscompose-service-docker-compose
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INFO[0015] Deleted ECS service service=ecscompose-service-docker-
compose
INFO[0015] ECS Service has reached a stable state desiredCount=0 runningCount=0
serviceName=ecscompose-service-docker-compose
Now, take down your cluster, which cleans up the resources that you created earlier with ecs-cli up.
ecs-cli down --force
Output:
INFO[0000] Waiting for your cluster resources to be deleted
INFO[0000] Cloudformation stack status stackStatus=DELETE_IN_PROGRESS
INFO[0061] Cloudformation stack status stackStatus=DELETE_IN_PROGRESS
INFO[0121] Deleted cluster cluster=ecs-cli-demo
Amazon ECS Command Line Reference
The following commands are available in the Amazon ECS CLI. Help text for each command is available
by appending the --help option to the final command argument; for example, help text for ecs-cli
compose service up is displayed with the following command:
ecs-cli compose service up --help
Available Commands
•ecs-cli (p. 235)
•ecs-cli configure (p. 237)
•ecs-cli up (p. 240)
•ecs-cli down (p. 243)
•ecs-cli scale (p. 244)
•ecs-cli ps (p. 244)
•ecs-cli push (p. 245)
•ecs-cli pull (p. 246)
•ecs-cli images (p. 247)
•ecs-cli license (p. 249)
•ecs-cli compose (p. 250)
•ecs-cli compose service (p. 252)
ecs-cli
Description
The Amazon ECS command line interface (CLI) provides high-level commands to simplify creating,
updating, and monitoring clusters and tasks from a local development environment. The Amazon ECS
CLI supports Docker Compose, a popular open-source tool for defining and running multi-container
applications.
For a quick walkthrough of the Amazon ECS CLI, see the Amazon ECS CLI Tutorial (p. 230).
Help text is available for each individual subcommand with ecs-cli subcommand --help.
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ecs-cli
Syntax
ecs-cli [--version] [subcommand] [--help]
Options
Name Description
--version, -v Prints the version information for the Amazon ECS CLI.
Required: No
--help, -h Show the help text for the specified command.
Required: No
Available Subcommands
The ecs-cli command supports the following subcommands:
configure
Configures your AWS credentials, the region to use, and the ECS cluster name to use with the
Amazon ECS CLI. For more information, see ecs-cli configure (p. 237).
up
Creates the ECS cluster (if it does not already exist) and the AWS resources required to set up the
cluster. For more information, see ecs-cli up (p. 240).
down
Deletes the AWS CloudFormation stack that was created by ecs-cli up and the associated resources.
For more information, see ecs-cli down (p. 243).
scale
Modifies the number of container instances in an ECS cluster. For more information, see ecs-cli
scale (p. 244).
ps
Lists all of the running containers in an ECS cluster. For more information, see ecs-cli ps (p. 244).
push
Pushes an image to an Amazon ECR repository. For more information, see ecs-cli push (p. 245).
pull
Pulls an image from an ECR repository. For more information, see ecs-cli pull (p. 246).
images
Lists all of the running containers in an ECS cluster. For more information, see ecs-cli
images (p. 247).
license
Prints the LICENSE files for the Amazon ECS CLI and its dependencies. For more information, see ecs-
cli license (p. 249).
compose
Executes docker-compose–style commands on an ECS cluster. For more information, see ecs-cli
compose (p. 250).
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ecs-cli configure
help
Shows the help text for the specified command.
ecs-cli configure
Description
Configures your AWS credentials, the AWS region to use, resource creation prefixes, and the ECS cluster
name to use with the Amazon ECS CLI. The resulting configuration is stored in the ~/.ecs/config file.
Each time you run the ecs-cli configure command, the configuration values in ~/.ecs/config are
replaced with the values from the latest command (and if existing configuration parameters are not
specified with their associated option flags or environment variables, they are removed or replaced with
the default values).
Syntax
ecs-cli configure [--region region] [--access-key aws_access_key_id] [--secret-key
aws_secret_access_key] [--profile profile_name] --cluster cluster_name [--compose-project-
name-prefix prefix] [--compose-service-name-prefix prefix] [--cfn-stack-name-prefix prefix]
[--help]
Options
Name Description
--region, -r region Specifies the region to use. If the AWS_REGION environment
variable is set when ecs-cli configure is run, then the region
is set to the value of that environment variable.
Type: String
Required: No
--access-key aws_access_key_id Specifies the AWS access key to use. If the
AWS_ACCESS_KEY_ID environment variable is set when ecs-
cli configure is run, then the AWS access key ID is set to the
value of that environment variable.
Type: String
Required: No
--secret-key aws_secret_access_key Specifies the AWS secret key to use. If the
AWS_SECRET_ACCESS_KEY environment variable is set when
ecs-cli configure is run, then the AWS secret access key is set
to the value of that environment variable.
Type: String
Required: No
--profile, -p profile_name Specifies your AWS credentials with an existing named
profile from ~/.aws/credentials. If the AWS_PROFILE
environment variable is set when ecs-cli configure is run,
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ecs-cli configure
Name Description
then the AWS named profile is set to the value of that
environment variable.
Type: String
Required: No
--cluster, -c cluster_name Specifies the ECS cluster name to use. If the cluster does not
exist, it is created when you try to add resources to it with
the ecs-cli up command.
Type: String
Required: Yes
--compose-project-name-prefix
prefix
Specifies the prefix to add to an ECS task definition that is
registered from a compose file. You can specify an empty
string (--compose-project-name-prefix "") with this option
to omit the default prefix.
Important
This prefix is used to name and later manage
resources created by the Amazon ECS CLI. Resources
that are created with a prefix are only addressable
from the Amazon ECS CLI if the configured prefix
matches the prefix that was used when the resource
was created. Before you change the prefix value,
you should consider the effects on any active
resources.
Type: String
Default: ecscompose-
Required: No
--compose-service-name-prefix
prefix
Specifies the prefix to add to an ECS service that is created
from a compose file. You can specify an empty string (--
compose-service-name-prefix "") with this option to omit
the default prefix.
Important
This prefix is used to name and later manage
resources created by the Amazon ECS CLI. Resources
that are created with a prefix are only addressable
from the Amazon ECS CLI if the configured prefix
matches the prefix that was used when the resource
was created. Before you change the prefix value,
you should consider the effects on any active
resources.
Type: String
Default: ecscompose-service-
Required: No
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ecs-cli configure
Name Description
--cfn-stack-name-prefix prefix Specifies the prefix to add to the AWS CloudFormation stack
that is created on ecs-cli up. You can specify an empty string
(--cfn-stack-name-prefix "") with this option to omit the
default prefix.
Important
This prefix is used to name and later manage
resources created by the Amazon ECS CLI. Resources
that are created with a prefix are only addressable
from the Amazon ECS CLI if the configured prefix
matches the prefix that was used when the resource
was created. Before you change the prefix value,
you should consider the effects on any active
resources.
Type: String
Default: amazon-ecs-cli-setup-
Required: No
--help, -h Shows the help text for the specified command.
Required: No
Examples
Example
This example configures the Amazon ECS CLI to create and use a cluster called ecs-cli in the us-west-2
region.
ecs-cli configure --region us-west-2 --access-key $AWS_ACCESS_KEY_ID --secret-
key $AWS_SECRET_ACCESS_KEY --cluster ecs-cli
Output:
INFO[0000] Saved ECS CLI configuration for cluster (ecs-cli)
Example
This example configures the Amazon ECS CLI to create and/or use a cluster called ecs-cli in the us-
west-2 region and omit the default Amazon ECS CLI prefixes on future resource creation.
Note
Any existing resources, such as task definitions, services, or AWS CloudFormation stacks, that
were created with the default prefixes will not be addressable from the Amazon ECS CLI until
the configured prefix matches the prefix that was used when the resource was created.
ecs-cli configure --region us-west-2 --access-key $AWS_ACCESS_KEY_ID --secret-
key $AWS_SECRET_ACCESS_KEY --cluster ecs-cli --compose-project-name-prefix "" --compose-
service-name-prefix "" --cfn-stack-name-prefix ""
Output:
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ecs-cli up
INFO[0000] Saved ECS CLI configuration for cluster (ecs-cli)
ecs-cli up
Description
Create the ECS cluster (if it does not already exist) and the AWS resources required to set up the cluster.
This command creates a new AWS CloudFormation stack called amazon-ecs-cli-setup-cluster_name.
You can view the progress of the stack creation in the AWS Management Console.
Syntax
ecs-cli up --keypair keypair_name --capability-iam [--size n] [--azs
availability_zone_1,availability_zone_2] [--security-group security_group_id] [--cidr
ip_range] [--port port_number] [--subnets subnet_1,subnet_2] [--vpc vpc_id] [--instance-
type instance_type] [--image-id ami_id] [--help]
Options
Name Description
--verbose, --debug Provides more verbose output for debugging purposes.
Required: No
--keypair keypair_name Specifies the name of an existing Amazon EC2 key pair to
enable SSH access to the EC2 instances in your cluster.
For more information about creating a key pair, see Setting
Up with Amazon EC2 in the Amazon EC2 User Guide for Linux
Instances.
Type: String
Required: Yes
--capability-iam Acknowledges that this command may create IAM resources.
Required: Yes
--size nSpecifies the number of instances to launch and register to
the cluster.
Type: Integer
Default: 1
Required: No
--azs
availability_zone_1,availability_zone_2
Specifies a comma-separated list of two VPC Availability
Zones in which to create subnets (these zones must have the
available status). We recommend this option if you do not
specify a VPC ID with the --vpc option.
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ecs-cli up
Name Description
Warning
Leaving this option blank can result in failure to
launch container instances if an unavailable zone is
chosen at random.
Type: String
Required: No
--security-group security_group_id Specifies an existing security group to associate with your
container instances. If you do not specify a security group
here, then a new one is created.
For more information, see Security Groups in the Amazon
EC2 User Guide for Linux Instances.
Required: No
--cidr ip_range Specifies a CIDR/IP range for the security group to use for
container instances in your cluster.
Note
This parameter is ignored if an existing security
group is specified with the --security-group
option.
Type: CIDR/IP range
Default: 0.0.0.0/0
Required: No
--port port_number Specifies a port to open on the security group to use for
container instances in your cluster.
Note
This parameter is ignored if an existing security
group is specified with the --security-group
option.
Type: Integer
Default: 80
Required: No
--subnets subnet_1,subnet_2 Specifies a comma-separated list of existing VPC subnet IDs
in which to launch your container instances.
Type: String
Required: This option is required if you specify a VPC with
the --vpc option.
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ecs-cli up
Name Description
--vpc vpc_id Specifies the ID of an existing VPC in which to launch your
container instances. If you specify a VPC ID, you must specify
a list of existing subnets in that VPC with the --subnets
option. If you do not specify a VPC ID, a new VPC is created
with two subnets.
Type: String
Required: No
--instance-type instance_type Specifies the EC2 instance type for your container instances.
For more information on EC2 instance types, see Amazon
EC2 Instances.
Type: String
Default: t2.micro
Required: No
--image-id ami_id Specifies the Amazon EC2 AMI ID to use for your container
instances.
Type: String
Default: The latest Amazon ECS–optimized AMI for the
specified region.
Required: No
--help, -h Shows the help text for the specified command.
Required: No
Examples
Example
This example brings up a cluster of 4 c4.large instances and configures them to use the EC2 key pair
called id_rsa.
ecs-cli up --keypair id_rsa --capability-iam --size 4 --instance-type c4.large
Output:
INFO[0000] Created cluster cluster=ecs-cli
INFO[0000] Waiting for your cluster resources to be created
INFO[0001] Cloudformation stack status stackStatus=CREATE_IN_PROGRESS
INFO[0061] Cloudformation stack status stackStatus=CREATE_IN_PROGRESS
INFO[0121] Cloudformation stack status stackStatus=CREATE_IN_PROGRESS
INFO[0181] Cloudformation stack status stackStatus=CREATE_IN_PROGRESS
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ecs-cli down
ecs-cli down
Description
Deletes the AWS CloudFormation stack that was created by ecs-cli up and the associated resources. The
--force option is required.
Note
The Amazon ECS CLI can only manage tasks, services, and container instances that were created
with the CLI. To manage tasks, services, and container instances that were not created by the
Amazon ECS CLI, use the AWS Command Line Interface or the AWS Management Console.
The ecs-cli down command attempts to delete the cluster specified in ~/.ecs/config. However, if
there are any active services (even with a desired count of 0) or registered container instances in your
cluster that were not created by ecs-cli up, the cluster is not deleted and the services and pre-existing
container instances remain active. This might happen, for example, if you used an existing ECS cluster
with registered container instances, such as the default cluster.
If you have remaining services or container instances in your cluster that you would like to remove, you
can follow the procedures in Cleaning Up your Amazon ECS Resources (p. 24) to remove them and then
delete your cluster.
Syntax
ecs-cli down --force [--help]
Options
Name Description
--force, -f Acknowledges that this command permanently deletes
resources.
Required: Yes
--help, -h Shows the help text for the specified command.
Required: No
Examples
Example
This example deletes a cluster.
ecs-cli down --force
Output:
INFO[0001] Waiting for your cluster resources to be deleted
INFO[0001] Cloudformation stack status stackStatus=DELETE_IN_PROGRESS
INFO[0062] Cloudformation stack status stackStatus=DELETE_IN_PROGRESS
INFO[0123] Cloudformation stack status stackStatus=DELETE_IN_PROGRESS
INFO[0154] Deleted cluster
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ecs-cli scale
ecs-cli scale
Description
Modifies the number of container instances in your cluster. This command changes the desired and
maximum instance count in the Auto Scaling group created by the ecs-cli up command. You can use this
command to scale out (increase the number of instances) or scale in (decrease the number of instances)
your cluster.
Note
The Amazon ECS CLI can only manage tasks, services, and container instances that were created
with the CLI. To manage tasks, services, and container instances that were not created by the
Amazon ECS CLI, use the AWS Command Line Interface or the AWS Management Console.
Syntax
ecs-cli scale --capability-iam --size n [--help]
Options
Name Description
--capability-iam Acknowledges that this command may create IAM resources.
Required: Yes
--size nSpecifies the number of instances to maintain in your cluster.
Type: Integer
Required: Yes
--help, -h Shows the help text for the specified command.
Required: No
Examples
Example
This example scales the current cluster to two container instances.
ecs-cli scale --capability-iam --size 2
Output:
INFO[0001] Waiting for your cluster resources to be updated
INFO[0001] Cloudformation stack status stackStatus=UPDATE_IN_PROGRESS
ecs-cli ps
Description
Lists all running containers in your ECS cluster.
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ecs-cli push
Syntax
ecs-cli ps [--help]
Options
Name Description
--help, -h Shows the help text for the specified command.
Required: No
Examples
Example
This example shows the containers that are running in the cluster.
ecs-cli ps
Output:
Name State Ports
TaskDefinition
595deba7-16a1-4aaf-9b27-e152eba03ccc/wordpress RUNNING 52.33.62.24:80->80/tcp
ecscompose-hello-world:3
595deba7-16a1-4aaf-9b27-e152eba03ccc/mysql RUNNING
ecscompose-hello-world:3
7fc0a2a4-9202-47d2-8b06-4463286b63de/mysql RUNNING
ecscompose-hello-world:3
7fc0a2a4-9202-47d2-8b06-4463286b63de/wordpress RUNNING 52.32.232.166:80->80/tcp
ecscompose-hello-world:3
ecs-cli push
Description
Pushes an image to an Amazon ECR repository.
Syntax
ecs-cli push [--registry-id registry_id] ECR_REPOSITORY[:TAG] [--help]
Options
Name Description
--registry-id registry_id Specifies the ECR registry ID to which to push the image. By
default, images are pushed to the current AWS account.
Required: No
--help, -h Shows the help text for the specified command.
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Name Description
Required: No
Examples
Example 1
This example pushes a local image called ubuntu to an ECR repository with the same name.
ecs-cli push ubuntu
Output:
INFO[0000] Getting AWS account ID...
INFO[0000] Tagging image
repository="aws_account_id.dkr.ecr.us-east-1.amazonaws.com/ubuntu" source-image=ubuntu
tag=
INFO[0000] Image tagged
INFO[0001] Creating repository repository=ubuntu
INFO[0001] Repository created
INFO[0001] Pushing image
repository="aws_account_id.dkr.ecr.us-east-1.amazonaws.com/ubuntu" tag=
INFO[0079] Image pushed
ecs-cli pull
Description
Pull an image from an Amazon ECR repository.
Syntax
ecs-cli pull [--registry-id registry_id] ECR_REPOSITORY[:TAG|@DIGEST] [--help]
Options
Name Description
--registry-id registry_id Specifies the ECR registry ID from which to pull the image.
By default, images are pulled from the current AWS account.
Required: No
--help, -h Shows the help text for the specified command.
Required: No
Examples
Example 1
This example pulls a local image called amazonlinux from an ECR repository with the same name.
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ecs-cli pull amazonlinux
Output:
INFO[0000] Getting AWS account ID...
INFO[0000] Pulling image
repository="aws_account_id.dkr.ecr.us-east-1.amazonaws.com/amazonlinux" tag=
INFO[0129] Image pulled
ecs-cli images
Description
List images in an Amazon ECR registry or repository.
Syntax
ecs-cli images [--registry-id registry_id] [--tagged|--untagged] [ECR_REPOSITORY] [--help]
Options
Name Description
--registry-id registry_id Specifies the ECR registry with which to list images. By
default, images are listed for the current AWS account.
Required: No
--tagged Filters the result to show only tagged images.
Required: No
--untagged Filters the result to show only untagged images.
Required: No
--help, -h Shows the help text for the specified command.
Required: No
Examples
Example 1
This example lists all of the images in an ECR registry.
ecs-cli images
Output:
REPOSITORY NAME TAG IMAGE DIGEST
PUSHED AT SIZE
rkt latest
sha256:404758ad8af94347fc8582fc8e30b6284f2b0751de29b2e755da212f80232fac 3 months ago
203 MB
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foobuntu latest
sha256:6b079ae764a6affcb632231349d4a5e1b084bece8c46883c099863ee2aeb5cf8 4 days ago
51.7 MB
ubuntu xenial
sha256:6b079ae764a6affcb632231349d4a5e1b084bece8c46883c099863ee2aeb5cf8 4 days ago
51.7 MB
ubuntu latest
sha256:6b079ae764a6affcb632231349d4a5e1b084bece8c46883c099863ee2aeb5cf8 4 days ago
51.7 MB
ubuntu <none>
sha256:512e30a26d9fa3648dbccb9e78e9bab636e6022e2d80bd73c99177b21a0d3982 19 minutes ago
268 MB
ubuntu trusty
sha256:bd6d24e8fa3f5822146b2c94247976b87e6564195c3c180b67833e6ea699f7c2 18 minutes ago
67.2 MB
ubuntu precise
sha256:b38267a51fb4460699bc2bcdbb53d42fec697bb4e4f9a819df3e762cec393b2a 17 minutes ago
40.1 MB
amazon-ecs-sample latest
sha256:bf04071a8edecc309f4d109ae36f24a5c272a115b6f7e636f77940059024d71c 2 weeks ago
105 MB
golang latest
sha256:137b22efee2df470b0cd28ebfc1ae583be0baf09334a5a882096193577d983ab 4 days ago
266 MB
amazonlinux latest
sha256:a59d563b5139deee8cb108bfb97bf3e9021b8ccea6dec8ff49733230cb2f0eca 4 days ago
98.8 MB
awsbatch/fetch_and_run latest
sha256:543800007416d0ccff4f63643bb18eeff4b874ea772128efcdc231ff456a37fc 6 weeks ago
116 MB
Example 2
This example lists all of the images in a specific ECR repository.
ecs-cli images ubuntu
Output:
REPOSITORY NAME TAG IMAGE DIGEST
PUSHED AT SIZE
ubuntu xenial
sha256:6b079ae764a6affcb632231349d4a5e1b084bece8c46883c099863ee2aeb5cf8 4 days ago
51.7 MB
ubuntu latest
sha256:6b079ae764a6affcb632231349d4a5e1b084bece8c46883c099863ee2aeb5cf8 4 days ago
51.7 MB
ubuntu <none>
sha256:512e30a26d9fa3648dbccb9e78e9bab636e6022e2d80bd73c99177b21a0d3982 20 minutes ago
268 MB
ubuntu trusty
sha256:bd6d24e8fa3f5822146b2c94247976b87e6564195c3c180b67833e6ea699f7c2 19 minutes ago
67.2 MB
ubuntu precise
sha256:b38267a51fb4460699bc2bcdbb53d42fec697bb4e4f9a819df3e762cec393b2a 18 minutes ago
40.1 MB
Example 3
This example lists all of the untagged images in an ECR registry.
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ecs-cli images --untagged
Output:
REPOSITORY NAME TAG IMAGE DIGEST
PUSHED AT SIZE
ubuntu <none>
sha256:512e30a26d9fa3648dbccb9e78e9bab636e6022e2d80bd73c99177b21a0d3982 24 minutes ago
268 MB
ecs-cli license
Description
Prints the LICENSE files for the Amazon ECS CLI and its dependencies.
Syntax
ecs-cli license [--help]
Options
Name Description
--help, -h Shows the help text for the specified command.
Required: No
Examples
Example
This example prints the license files.
ecs-cli license
Output:
Copyright 2015 Amazon.com, Inc. or its affiliates. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License"). You may not use this file
except in compliance with the
License. A copy of the License is located at
http://aws.amazon.com/apache2.0/
or in the "license" file accompanying this file. This file is distributed on an "AS IS"
BASIS, WITHOUT WARRANTIES OR
CONDITIONS OF ANY KIND, either express or implied. See the License for the specific
language governing permissions
and limitations under the License.
...
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ecs-cli compose
Description
Manage Amazon ECS tasks with docker-compose-style commands on an ECS cluster.
Note
To create Amazon ECS services with the Amazon ECS CLI, see ecs-cli compose service (p. 252).
The ecs-cli compose command works with a Docker compose file to create task definitions and manage
tasks. At this time, the latest version of the Amazon ECS CLI supports Docker compose file syntax
versions 1 and 2. By default, the command looks for a compose file in the current directory, called
docker-compose.yml. However, you can also specify a different file name or path to a compose file with
the --file option. This is especially useful for managing tasks and services from multiple compose files
at a time with the Amazon ECS CLI.
The ecs-cli compose command uses a project name with the task definitions and services it
creates. When the CLI creates a task definition from a compose file, the task definition is called
ecscompose-project-name. When the CLI creates a service from a compose file, the service is called
ecscompose-service-project-name. By default, the project name is the name of the current working
directory. However, you can also specify your own project name with the --project-name option.
Note
The Amazon ECS CLI can only manage tasks, services, and container instances that were created
with the CLI. To manage tasks, services, and container instances that were not created by the
Amazon ECS CLI, use the AWS Command Line Interface or the AWS Management Console.
The following parameters are supported in compose files for the Amazon ECS CLI:
•command
•cpu_shares
•dns
•dns_search
•entrypoint
•environment: If an environment variable value is not specified in the compose file, but it exists in the
shell environment, the shell environment variable value is passed to the task definition that is created
for any associated tasks or services.
Important
We do not recommend using plaintext environment variables for sensitive information, such
as credential data.
•env_file
Important
We do not recommend using plaintext environment variables for sensitive information, such
as credential data.
•extra_hosts
•hostname
•image
•labels
•links
•log_driver
•log_opt
•mem_limit (in bytes)
•ports
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•privileged
•read_only
•security_opt
•ulimits
•user
•volumes
•volumes_from
•working_dir
Important
The build directive is not supported at this time.
For more information about Docker compose file syntax, see the Compose file reference in the Docker
documentation.
Syntax
ecs-cli compose [--verbose] [--file compose-file] [--project-name project-name]
[subcommand] [arguments] [--help]
Options
Name Description
--verbose, --debug Increases the verbosity of command output to aid in
diagnostics.
Required: No
--file, -f compose-file Specifies the Docker compose file to use. At this time, the
latest version of the Amazon ECS CLI supports Docker
compose file syntax versions 1 and 2. If the COMPOSE_FILE
environment variable is set when ecs-cli compose is run,
then the Docker compose file is set to the value of that
environment variable.
Type: String
Default: ./docker-compose.yml
Required: No
--project-name, -p project-name Specifies the project name to use. If the
COMPOSE_PROJECT_NAME environment variable is set when
ecs-cli compose is run, then the project name is set to the
value of that environment variable.
Type: String
Default: The current directory name.
Required: No
--help, -h Shows the help text for the specified command.
Required: No
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Available Subcommands
The ecs-cli compose command supports the following subcommands:
create
Creates an ECS task definition from your compose file.
start
Starts a single task from the task definition created from your compose file.
up
Creates an ECS task definition from your compose file (if it does not already exist) and runs one
instance of that task on your cluster (a combination of create and start)
ps
Lists all the containers in your cluster that were started by the compose project.
scale n
Scales the number of running tasks to the specified count.
run [containerName] [command] ...
Starts all containers overriding commands with the supplied one-off commands for the containers.
stop
Stops all the running tasks created by the compose project.
service [subcommand]
Creates an ECS service from your compose file. For more information, see ecs-cli compose
service (p. 252).
help
Shows the help text for the specified command.
Examples
Example 1
This example creates a task definition with the project name hello-world from the hello-world.yml
compose file.
ecs-cli compose --project-name hello-world --file hello-world.yml create
Output:
INFO[0000] Using ECS task definition TaskDefinition=ecscompose-hello-
world:5
ecs-cli compose service
Description
Manage Amazon ECS services with docker-compose-style commands on an ECS cluster.
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Note
To run tasks with the Amazon ECS CLI instead of creating services, see ecs-cli
compose (p. 250).
The ecs-cli compose service command works with a Docker compose file to create task definitions and
manage services. At this time, the Amazon ECS CLI supports Docker compose file syntax versions 1 and
2. By default, the command looks for a compose file in the current directory, called docker-compose.yml.
However, you can also specify a different file name or path to a compose file with the --file option.
This is especially useful for managing tasks and services from multiple compose files at a time with the
Amazon ECS CLI.
The ecs-cli compose service command uses a project name with the task definitions and services
that it creates. When the CLI creates a task definition from a compose file, the task definition is called
ecscompose-project-name. When the CLI creates a service from a compose file, the service is called
ecscompose-service-project-name. By default, the project name is the name of the current working
directory. However, you can also specify your own project name with the --project-name option.
Note
The Amazon ECS CLI can only manage tasks, services, and container instances that were created
with the CLI. To manage tasks, services, and container instances that were not created by the
Amazon ECS CLI, use the AWS Command Line Interface or the AWS Management Console.
The following parameters are supported in compose files for the Amazon ECS CLI:
•command
•cpu_shares
•dns
•dns_search
•entrypoint
•environment: If an environment variable value is not specified in the compose file, but it exists in the
shell environment, the shell environment variable value is passed to the task definition that is created
for any associated tasks or services.
Important
We do not recommend using plaintext environment variables for sensitive information, such
as credential data.
•env_file
Important
We do not recommend using plaintext environment variables for sensitive information, such
as credential data.
•extra_hosts
•hostname
•image
•labels
•links
•log_driver
•log_opt
•mem_limit (in bytes)
•ports
•privileged
•read_only
•security_opt
•ulimits
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•user
•volumes
•volumes_from
•working_dir
Important
The build directive is not supported at this time.
For more information about Docker compose file syntax, see the Compose file reference in the Docker
documentation.
Syntax
ecs-cli compose [--verbose] [--file compose-file] [--project-name project-name] service
[subcommand] [arguments] [--help]
Options
Name Description
--verbose, --debug Increases the verbosity of command output to aid in
diagnostics.
Required: No
--file, -f compose-file Specifies the Docker compose file to use. At this time, the
latest version of the Amazon ECS CLI supports Docker
compose file syntax versions 1 and 2. If the COMPOSE_FILE
environment variable is set when ecs-cli compose is run,
then the Docker compose file is set to the value of that
environment variable.
Type: String
Default: ./docker-compose.yml
Required: No
--project-name, -p project-name Specifies the project name to use. If the
COMPOSE_PROJECT_NAME environment variable is set when
ecs-cli compose is run, then the project name is set to the
value of that environment variable.
Type: String
Default: The current directory name.
Required: No
--help, -h Shows the help text for the specified command.
Required: No
Available Subcommands
The ecs-cli compose service command supports the following subcommands and arguments:
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create [--deployment-max-percent n] [--deployment-min-healthy-percent n] [--load-balancer-name
value|--target-group-arn value] [--container-name value] [--container-port value] [--role value]
Creates an ECS service from your compose file. The service is created with a desired count of 0, so no
containers are started by this command.
The --deployment-max-percent option specifies the upper limit (as a percentage of the service's
desiredCount) of the number of running tasks that can be running in a service during a deployment
(the default value is 200). The --deployment-min-healthy-percent option specifies the lower
limit (as a percentage of the service's desiredCount) of the number of running tasks that must
remain running and healthy in a service during a deployment (the default value is 100). For more
information, see maximumPercent (p. 141) and minimumHealthyPercent (p. 141).
You can optionally run your service behind a load balancer. The load balancer distributes traffic
across the tasks that are associated with the service. For more information, see Service Load
Balancing (p. 141). After you create a service, the load balancer name or target group ARN, container
name, and container port specified in the service definition are immutable.
Note
You must create your load balancer resources in the before you can configure a service to
use them. Your load balancer resources should reside in the same VPC as your container
instances and they should be configured to use the same subnets. You must also add a
security group rule to your container instance security group that allows inbound traffic
from your load balancer. For more information, see Creating a Load Balancer (p. 145).
• To configure your service to use an existing Elastic Load Balancing Classic Load Balancer, you must
specify the load balancer name, the container name (as it appears in a container definition), and
the container port to access from the load balancer. When a task from this service is placed on a
container instance, the container instance is registered with the load balancer specified here.
• To configure your service to use an existing Elastic Load Balancing Application Load Balancer, you
must specify the load balancer target group ARN, the container name (as it appears in a container
definition), and the container port to access from the load balancer. When a task from this service
is placed on a container instance, the container instance and port combination is registered as a
target in the target group specified here.
start
Starts one copy of each of the containers on the created ECS service. This command updates the
desired count of the service to 1.
up [--deployment-max-percent n] [--deployment-min-healthy-percent n] [--load-balancer-name
value|--target-group-arn value] [--container-name value] [--container-port value] [--role value]
Creates an ECS service from your compose file (if it does not already exist) and runs one instance
of that task on your cluster (a combination of create and start). This command updates the desired
count of the service to 1.
The --deployment-max-percent option specifies the upper limit (as a percentage of the service's
desiredCount) of the number of running tasks that can be running in a service during a deployment
(the default value is 200). The --deployment-min-healthy-percent option specifies the lower
limit (as a percentage of the service's desiredCount) of the number of running tasks that must
remain running and healthy in a service during a deployment (the default value is 100). For more
information, see maximumPercent (p. 141) and minimumHealthyPercent (p. 141).
You can optionally run your service behind a load balancer. The load balancer distributes traffic
across the tasks that are associated with the service. For more information, see Service Load
Balancing (p. 141). After you create a service, the load balancer name or target group ARN, container
name, and container port specified in the service definition are immutable.
Note
You must create your load balancer resources in the before you can configure a service to
use them. Your load balancer resources should reside in the same VPC as your container
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instances and they should be configured to use the same subnets. You must also add a
security group rule to your container instance security group that allows inbound traffic
from your load balancer. For more information, see Creating a Load Balancer (p. 145).
• To configure your service to use an existing Elastic Load Balancing Classic Load Balancer, you must
specify the load balancer name, the container name (as it appears in a container definition), and
the container port to access from the load balancer. When a task from this service is placed on a
container instance, the container instance is registered with the load balancer specified here.
• To configure your service to use an existing Elastic Load Balancing Application Load Balancer, you
must specify the load balancer target group ARN, the container name (as it appears in a container
definition), and the container port to access from the load balancer. When a task from this service
is placed on a container instance, the container instance and port combination is registered as a
target in the target group specified here.
ps
Lists all the containers in your cluster that belong to the service created with the compose project.
scale [--deployment-max-percent n] [--deployment-min-healthy-percent n] n
Scales the desired count of the service to the specified count.
The --deployment-max-percent option specifies the upper limit (as a percentage of the service's
desiredCount) of the number of running tasks that can be running in a service during a deployment
(the default value is 200). The --deployment-min-healthy-percent option specifies the lower
limit (as a percentage of the service's desiredCount) of the number of running tasks that must
remain running and healthy in a service during a deployment (the default value is 100). For more
information, see maximumPercent (p. 141) and minimumHealthyPercent (p. 141).
stop
Stops the running tasks that belong to the service created with the compose project. This command
updates the desired count of the service to 0.
rm
Updates the desired count of the service to 0 and then deletes the service.
help
Shows the help text for the specified command.
Examples
Example 1
This example brings up an ECS service with the project name hello-world from the hello-world.yml
compose file.
ecs-cli compose --project-name hello-world --file hello-world.yml service up
Output:
INFO[0001] Using ECS task definition TaskDefinition=ecscompose-hello-
world:3
INFO[0001] Created an ECS Service serviceName=ecscompose-service-
hello-world taskDefinition=ecscompose-hello-world:3
INFO[0002] Updated ECS service successfully desiredCount=1
serviceName=ecscompose-service-hello-world
INFO[0002] Describe ECS Service status desiredCount=1 runningCount=0
serviceName=ecscompose-service-hello-world
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INFO[0033] Describe ECS Service status desiredCount=1 runningCount=0
serviceName=ecscompose-service-hello-world
INFO[0063] Describe ECS Service status desiredCount=1 runningCount=0
serviceName=ecscompose-service-hello-world
INFO[0093] Describe ECS Service status desiredCount=1 runningCount=0
serviceName=ecscompose-service-hello-world
INFO[0108] ECS Service has reached a stable state desiredCount=1 runningCount=1
serviceName=ecscompose-service-hello-world
Example 2
This example scales the service created by the hello-world project to a desired count of 2.
ecs-cli compose --project-name hello-world --file hello-world.yml service scale 2
Output:
INFO[0001] Updated ECS service successfully desiredCount=2
serviceName=ecscompose-service-hello-world
INFO[0001] Describe ECS Service status desiredCount=2 runningCount=1
serviceName=ecscompose-service-hello-world
INFO[0032] Describe ECS Service status desiredCount=2 runningCount=1
serviceName=ecscompose-service-hello-world
INFO[0063] ECS Service has reached a stable state desiredCount=2 runningCount=2
serviceName=ecscompose-service-hello-world
Example 3
This example scales the service created by the hello-world project to a desired count of 0 and then
deletes the service.
ecs-cli compose --project-name hello-world --file hello-world.yml service rm
Output:
INFO[0000] Updated ECS service successfully desiredCount=0
serviceName=ecscompose-service-hello-world
INFO[0000] Describe ECS Service status desiredCount=0 runningCount=2
serviceName=ecscompose-service-hello-world
INFO[0016] ECS Service has reached a stable state desiredCount=0 runningCount=0
serviceName=ecscompose-service-hello-world
INFO[0016] Deleted ECS service service=ecscompose-service-hello-
world
INFO[0016] ECS Service has reached a stable state desiredCount=0 runningCount=0
serviceName=ecscompose-service-hello-world
Example 4
This example creates a service from the nginx-compose.yml compose file and configures it to use an
existing Application Load Balancer.
ecs-cli compose -f nginx-compose.yml service up --target-group-arn
arn:aws:elasticloadbalancing:us-east-1:aws_account_id:targetgroup/ecs-cli-
alb/9856106fcc5d4be8 --container-name nginx --container-port 80 --role ecsServiceRole
Output:
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INFO[0000] Using ECS task definition TaskDefinition="ecscompose-ecs-
cli:3"
INFO[0001] Created an ECS service service=ecscompose-service-ecs-cli
taskDefinition="ecscompose-ecs-cli:3"
INFO[0001] Updated ECS service successfully desiredCount=1
serviceName=ecscompose-service-ecs-cli
INFO[0001] Describe ECS Service status desiredCount=1 runningCount=0
serviceName=ecscompose-service-ecs-cli
INFO[0016] ECS Service has reached a stable state desiredCount=1 runningCount=1
serviceName=ecscompose-service-ecs-cli
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Step 1: (Optional) Create a Cluster
Using the AWS CLI with Amazon ECS
The following steps will help you set up a cluster, register a task definition, run a task, and perform other
common scenarios in Amazon ECS with the AWS CLI.
Important
Before you begin, be sure that you've completed the steps in Setting Up with Amazon ECS (p. 8)
and that your AWS user has the required permissions specified in the Amazon ECS First Run
Wizard (p. 220) IAM policy example.
The AWS Command Line Interface (CLI) is a unified tool to manage your AWS services. With just one tool
to download and configure, you can control multiple AWS services from the command line and automate
them through scripts. For more information on the AWS CLI, see http://aws.amazon.com/cli/.
For more information on the other tools available for managing your AWS resources, including the
different AWS SDKs, IDE toolkits, and the Windows PowerShell command line tools, see http://
aws.amazon.com/tools/.
1. Step 1: (Optional) Create a Cluster (p. 259)
2. Step 2: Launch an Instance with the Amazon ECS AMI (p. 260)
3. Step 3: List Container Instances (p. 261)
4. Step 4: Describe your Container Instance (p. 261)
5. Step 5: Register a Task Definition (p. 263)
6. Step 6: List Task Definitions (p. 264)
7. Step 7: Run a Task (p. 265)
8. Step 8: List Tasks (p. 265)
9. Step 9: Describe the Running Task (p. 266)
Step 1: (Optional) Create a Cluster
By default, your account receives a default cluster when you launch your first container instance.
Note
The benefit of using the default cluster that is provided for you is that you don't have to specify
the --cluster cluster_name option in the subsequent commands. If you do create your own,
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non-default, cluster you need to specify --cluster cluster_name for each command that you
intend to use with that cluster.
Create your own cluster with a unique name with the following command:
aws ecs create-cluster --cluster-name MyCluster
Output:
{
"cluster": {
"clusterName": "MyCluster",
"status": "ACTIVE",
"clusterArn": "arn:aws:ecs:region:aws_account_id:cluster/MyCluster"
}
}
Step 2: Launch an Instance with the Amazon ECS
AMI
You must have an Amazon ECS container instance in your cluster before you can run tasks on it. If you do
not have any container instances in your cluster, see Launching an Amazon ECS Container Instance (p. 42)
for more information. The current Amazon ECS–optimized AMI IDs by region are listed below for
reference.
Region AMI Name AMI ID EC2 console link
us-east-1 amzn-ami-2016.09.g-
amazon-ecs-optimized
ami-275ffe31 Launch instance
us-east-2 amzn-ami-2016.09.g-
amazon-ecs-optimized
ami-62745007 Launch instance
us-west-1 amzn-ami-2016.09.g-
amazon-ecs-optimized
ami-689bc208 Launch instance
us-west-2 amzn-ami-2016.09.g-
amazon-ecs-optimized
ami-62d35c02 Launch instance
eu-west-1 amzn-ami-2016.09.g-
amazon-ecs-optimized
ami-95f8d2f3 Launch instance
eu-west-2 amzn-ami-2016.09.g-
amazon-ecs-optimized
ami-bf9481db Launch instance
eu-central-1 amzn-ami-2016.09.g-
amazon-ecs-optimized
ami-085e8a67 Launch instance
ap-northeast-1 amzn-ami-2016.09.g-
amazon-ecs-optimized
ami-f63f6f91 Launch instance
ap-southeast-1 amzn-ami-2016.09.g-
amazon-ecs-optimized
ami-b4ae1dd7 Launch instance
ap-southeast-2 amzn-ami-2016.09.g-
amazon-ecs-optimized
ami-fbe9eb98 Launch instance
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Region AMI Name AMI ID EC2 console link
ca-central-1 amzn-ami-2016.09.g-
amazon-ecs-optimized
ami-ee58e58a Launch instance
Step 3: List Container Instances
Within a few minutes of launching your container instance, the Amazon ECS agent registers the instance
with your default cluster. You can list the container instances in a cluster by running the following
command:
aws ecs list-container-instances --cluster default
Output:
{
"containerInstanceArns": [
"arn:aws:ecs:us-east-1:aws_account_id:container-instance/container_instance_ID"
]
}
Step 4: Describe your Container Instance
After you have the ARN or ID of a container instance, you can use the describe-container-instances
command to get valuable information on the instance, such as remaining and registered CPU and
memory resources.
aws ecs describe-container-instances --cluster default --container-
instances container_instance_ID
Output:
{
"failures": [],
"containerInstances": [
{
"status": "ACTIVE",
"registeredResources": [
{
"integerValue": 1024,
"longValue": 0,
"type": "INTEGER",
"name": "CPU",
"doubleValue": 0.0
},
{
"integerValue": 995,
"longValue": 0,
"type": "INTEGER",
"name": "MEMORY",
"doubleValue": 0.0
},
{
"name": "PORTS",
"longValue": 0,
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"doubleValue": 0.0,
"stringSetValue": [
"22",
"2376",
"2375",
"51678"
],
"type": "STRINGSET",
"integerValue": 0
},
{
"name": "PORTS_UDP",
"longValue": 0,
"doubleValue": 0.0,
"stringSetValue": [],
"type": "STRINGSET",
"integerValue": 0
}
],
"ec2InstanceId": "instance_id",
"agentConnected": true,
"containerInstanceArn": "arn:aws:ecs:us-west-2:aws_account_id:container-
instance/container_instance_ID",
"pendingTasksCount": 0,
"remainingResources": [
{
"integerValue": 1024,
"longValue": 0,
"type": "INTEGER",
"name": "CPU",
"doubleValue": 0.0
},
{
"integerValue": 995,
"longValue": 0,
"type": "INTEGER",
"name": "MEMORY",
"doubleValue": 0.0
},
{
"name": "PORTS",
"longValue": 0,
"doubleValue": 0.0,
"stringSetValue": [
"22",
"2376",
"2375",
"51678"
],
"type": "STRINGSET",
"integerValue": 0
},
{
"name": "PORTS_UDP",
"longValue": 0,
"doubleValue": 0.0,
"stringSetValue": [],
"type": "STRINGSET",
"integerValue": 0
}
],
"runningTasksCount": 0,
"attributes": [
{
"name": "com.amazonaws.ecs.capability.privileged-container"
},
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{
"name": "com.amazonaws.ecs.capability.docker-remote-api.1.17"
},
{
"name": "com.amazonaws.ecs.capability.docker-remote-api.1.18"
},
{
"name": "com.amazonaws.ecs.capability.docker-remote-api.1.19"
},
{
"name": "com.amazonaws.ecs.capability.logging-driver.json-file"
},
{
"name": "com.amazonaws.ecs.capability.logging-driver.syslog"
}
],
"versionInfo": {
"agentVersion": "1.5.0",
"agentHash": "b197edd",
"dockerVersion": "DockerVersion: 1.7.1"
}
}
]
}
You can also find the Amazon EC2 instance ID that you can use to monitor the instance in the Amazon
EC2 console or with the aws ec2 describe-instances --instance-id instance_id command.
Step 5: Register a Task Definition
Before you can run a task on your ECS cluster, you must register a task definition. Task definitions
are lists of containers grouped together. The following example is a simple task definition that uses a
busybox image from Docker Hub and simply sleeps for 360 seconds. For more information about the
available task definition parameters, see Amazon ECS Task Definitions (p. 93).
{
"containerDefinitions": [
{
"name": "sleep",
"image": "busybox",
"cpu": 10,
"command": [
"sleep",
"360"
],
"memory": 10,
"essential": true
}
],
"family": "sleep360"
}
The above example JSON can be passed to the AWS CLI in two ways: you can save the task definition
JSON as a file and pass it with the --cli-input-json file://path_to_file.json option, or you can
escape the quotation marks in the JSON and pass the JSON container definitions on the command line
as in the below example. If you choose to pass the container definitions on the command line, your
command additionally requires a --family parameter that is used to keep multiple versions of your task
definition associated with each other.
To use a JSON file for container definitions:
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aws ecs register-task-definition --cli-input-json file://$HOME/tasks/sleep360.json
To use a JSON string for container definitions:
aws ecs register-task-definition --family sleep360 --container-definitions "[{\"name\":
\"sleep\",\"image\":\"busybox\",\"cpu\":10,\"command\":[\"sleep\",\"360\"],\"memory\":10,
\"essential\":true}]"
The register-task-definition returns a description of the task definition after it completes its
registration.
{
"taskDefinition": {
"volumes": [],
"taskDefinitionArn": "arn:aws:ec2:us-east-1:aws_account_id:task-definition/
sleep360:1",
"containerDefinitions": [
{
"environment": [],
"name": "sleep",
"mountPoints": [],
"image": "busybox",
"cpu": 10,
"portMappings": [],
"command": [
"sleep",
"360"
],
"memory": 10,
"essential": true,
"volumesFrom": []
}
],
"family": "sleep360",
"revision": 1
}
}
Step 6: List Task Definitions
You can list the task definitions for your account at any time with the list-task-definitions command.
The output of this command shows the family and revision values that you can use together when
calling run-task or start-task.
aws ecs list-task-definitions
Output:
{
"taskDefinitionArns": [
"arn:aws:ec2:us-east-1:aws_account_id:task-definition/sleep300:1",
"arn:aws:ec2:us-east-1:aws_account_id:task-definition/sleep300:2",
"arn:aws:ec2:us-east-1:aws_account_id:task-definition/sleep360:1",
"arn:aws:ec2:us-east-1:aws_account_id:task-definition/wordpress:3",
"arn:aws:ec2:us-east-1:aws_account_id:task-definition/wordpress:4",
"arn:aws:ec2:us-east-1:aws_account_id:task-definition/wordpress:5",
"arn:aws:ec2:us-east-1:aws_account_id:task-definition/wordpress:6"
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]
}
Step 7: Run a Task
After you have registered a task for your account and have launched a container instance that is
registered to your cluster, you can run the registered task in your cluster. For this example, you place a
single instance of the sleep360:1 task definition in your default cluster.
aws ecs run-task --cluster default --task-definition sleep360:1 --count 1
Output:
{
"tasks": [
{
"taskArn": "arn:aws:ecs:us-east-1:aws_account_id:task/task_ID",
"overrides": {
"containerOverrides": [
{
"name": "sleep"
}
]
},
"lastStatus": "PENDING",
"containerInstanceArn": "arn:aws:ecs:us-east-1:aws_account_id:container-
instance/container_instance_ID",
"clusterArn": "arn:aws:ecs:us-east-1:aws_account_id:cluster/default",
"desiredStatus": "RUNNING",
"taskDefinitionArn": "arn:aws:ecs:us-east-1:aws_account_id:task-definition/
sleep360:1",
"containers": [
{
"containerArn": "arn:aws:ecs:us-
east-1:aws_account_id:container/container_ID",
"taskArn": "arn:aws:ecs:us-east-1:aws_account_id:task/task_ID",
"lastStatus": "PENDING",
"name": "sleep"
}
]
}
]
}
Step 8: List Tasks
List the tasks for your cluster. You should see the task that you ran in the previous section. You can take
the task ID or the full ARN that is returned from this command and use it to describe the task later.
aws ecs list-tasks --cluster default
Output:
{
"taskArns": [
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"arn:aws:ecs:us-east-1:aws_account_id:task/task_ID"
]
}
Step 9: Describe the Running Task
Describe the task using the task ID retrieved earlier to get more information about the task.
aws ecs describe-tasks --cluster default --task task_ID
Output:
{
"failures": [],
"tasks": [
{
"taskArn": "arn:aws:ecs:us-east-1:aws_account_id:task/task_ID",
"overrides": {
"containerOverrides": [
{
"name": "sleep"
}
]
},
"lastStatus": "RUNNING",
"containerInstanceArn": "arn:aws:ecs:us-east-1:aws_account_id:container-
instance/container_instance_ID",
"clusterArn": "arn:aws:ecs:us-east-1:aws_account_id:cluster/default",
"desiredStatus": "RUNNING",
"taskDefinitionArn": "arn:aws:ecs:us-east-1:aws_account_id:task-definition/
sleep360:1",
"containers": [
{
"containerArn": "arn:aws:ecs:us-
east-1:aws_account_id:container/container_ID",
"taskArn": "arn:aws:ecs:us-east-1:aws_account_id:task/task_ID",
"lastStatus": "RUNNING",
"name": "sleep",
"networkBindings": []
}
]
}
]
}
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Microservices
Common Use Cases in Amazon ECS
This topic provides guidance for two common use cases in Amazon ECS: microservices and batch jobs.
Here you can find considerations and external resources that may be useful for getting your application
running on Amazon ECS, and the common aspects of each solution.
Topics
•Microservices (p. 267)
•Batch Jobs (p. 269)
Microservices
Microservices are built with a software architectural method that decomposes complex applications into
smaller, independent services. Containers are optimal for running small, decoupled services, and they
offer the following advantages:
• Containers make services easy to model in an immutable image with all of your dependencies.
• Containers can use any application and any programming language.
• The container image is a versioned artifact, so you can track your container images to the source they
came from.
• You can test your containers locally, and deploy the same artifact to scale.
The following sections cover some of the aspects and challenges that you must consider when designing
a microservices architecture to run on Amazon ECS. You can also view the microservices reference
architecture on GitHub. For more information, see Deploying Microservices with Amazon ECS, AWS
CloudFormation, and an Application Load Balancer.
Topics
•Auto Scaling (p. 268)
•Service Discovery (p. 268)
•Authorization and Secrets Management (p. 268)
•Logging (p. 268)
•Continuous Integration and Continuous Deployment (p. 269)
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Auto Scaling
Auto Scaling
The application load for your microservice architecture can change over time. A responsive application
can scale out or in, depending on actual or anticipated load. Amazon ECS provides you with several tools
to scale not only your services that are running in your clusters, but the actual clusters themselves.
For example, Amazon ECS provides CloudWatch metrics for your clusters and services. For more
information, see Amazon ECS CloudWatch Metrics (p. 172). You can monitor the memory and CPU
utilization for your clusters and services. Then, use those metrics to trigger CloudWatch alarms that can
automatically scale out your cluster when its resources are running low, and scale them back in when
you don't need as many resources. For more information, see Tutorial: Scaling Container Instances with
CloudWatch Alarms (p. 182).
In addition to scaling your cluster size, your Amazon ECS service can optionally be configured to use
Service Auto Scaling to adjust its desired count up or down in response to CloudWatch alarms. Service
Auto Scaling is available in all regions that support Amazon ECS. For more information, see Service Auto
Scaling (p. 152).
Service Discovery
Service discovery is a key component of most distributed systems and service-oriented architectures.
With service discovery, your microservice components are automatically discovered as they get created
and terminated on a given infrastructure. There are several approaches that you can use to make your
services discoverable. The following resources describe a few examples:
•Run Containerized Microservices with Amazon EC2 Container Service and Application Load Balancer:
This post describes how to use the dynamic port mapping and path-based routing features of Elastic
Load Balancing Application Load Balancers to provide service discovery for a microservice architecture.
•Amazon EC2 Container Service - Reference Architecture: Service Discovery: This Amazon ECS reference
architecture provides service discovery to containers using CloudWatch Events, Lambda, and Amazon
Route53 private hosted zones.
•Service Discovery via Consul with Amazon ECS: This post shows how a third party tool called Consul
by HashiCorp can augment the capabilities of Amazon ECS by providing service discovery for an ECS
cluster (complete with an example application).
Authorization and Secrets Management
Managing secrets, such as database credentials for an application, has always been a challenging issue.
The Managing Secrets for Amazon ECS Applications Using Parameter Store and IAM Roles for Tasks
post focuses on how to integrate the IAM roles for tasks (p. 216) functionality of Amazon ECS with the
Amazon EC2 Systems Manager parameter store. Parameter store provides a centralized store to manage
your configuration data, whether it's plaintext data such as database strings or secrets such as passwords,
encrypted through AWS Key Management Service.
Logging
You can configure your container instances to send log information to CloudWatch Logs. This
enables you to view different logs from your container instances in one convenient location. For
more information about getting started using CloudWatch Logs on your container instances that
were launched with the Amazon ECS-optimized AMI, see Using CloudWatch Logs with Container
Instances (p. 52).
You can configure the containers in your tasks to send log information to CloudWatch Logs. This enables
you to view different logs from your containers in one convenient location, and it prevents your container
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logs from taking up disk space on your container instances. For more information about getting started
using the awslogs log driver in your task definitions, see Using the awslogs Log Driver (p. 117).
Continuous Integration and Continuous Deployment
Continuous integration and continuous deployment (CICD) is a common process for microservice
architectures that are based on Docker containers. You can create a pipeline that takes the following
actions:
• Monitors changes to a source code repository
• Builds a new Docker image from that source
• Pushes the image to an image repository such as Amazon ECR or Docker Hub
• Updates your Amazon ECS services to use the new image in your application
The following resources outline how to do this in different ways:
•ECS Reference Architecture: Continuous Deployment: This reference architecture demonstrates how
to achieve continuous deployment of an application to Amazon ECS using AWS CodePipeline, AWS
CodeBuild, and AWS CloudFormation.
•Continuous Delivery Pipeline for Amazon ECS Using Jenkins, GitHub, and Amazon ECR: This AWS
labs repository helps you set up and configure a continuous delivery pipeline for Amazon ECS using
Jenkins, GitHub, and Amazon ECR.
Batch Jobs
Docker containers are particularly suited for batch job workloads. Batch jobs are often short-lived and
embarrassingly parallel. You can package your batch processing application into a Docker image so that
you can deploy it anywhere, such as in an Amazon ECS task. If you are interested in running batch job
workloads, consider the following resources:
•AWS Batch: For fully managed batch processing at any scale, you should consider using AWS Batch.
AWS Batch enables developers, scientists, and engineers to easily and efficiently run hundreds of
thousands of batch computing jobs on AWS. AWS Batch dynamically provisions the optimal quantity
and type of compute resources (for example, CPU or memory optimized instances) based on the
volume and specific resource requirements of the batch jobs submitted. For more information, see the
AWS Batch product detail pages.
•Amazon ECS Reference Architecture: Batch Processing: This reference architecture illustrates how
to use AWS CloudFormation, Amazon S3, Amazon SQS, and CloudWatch alarms to handle batch
processing on Amazon ECS.
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Amazon ECS Service Limits
The following table provides the default limits for Amazon ECS for an AWS account which can be
changed. For more information on the service limits for other AWS services that you can use with
Amazon ECS, such as Elastic Load Balancing and Auto Scaling, see AWS Service Limits in the Amazon Web
Services General Reference.
Resource Default Limit
Number of clusters per region, per account 1000
Number of container instances per cluster 1000
Number of services per cluster 500
The following table provides other limitations for Amazon ECS that cannot be changed.
Resource Default Limit
Number of load balancers per service 1
Number of tasks per service (the desired count) 1000
Number of tasks launched (count) per run-task 10
Number of container instances per start-task 10
Throttle on container instance registration rate 1 per second / 60 max per minute
Task definition size limit 32 KiB
Task definition max containers 10
Throttle on task definition registration rate 1 per second / 60 max per minute
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Amazon ECS Information in CloudTrail
Logging Amazon ECS API Calls By
Using AWS CloudTrail
Amazon ECS is integrated with AWS CloudTrail, a service that captures API calls made by or on behalf
of Amazon ECS in your AWS account and delivers the log files to an Amazon S3 bucket that you specify.
CloudTrail captures API calls from the Amazon ECS console or from the Amazon ECS API. Using the
information collected by CloudTrail, you can determine what request was made to Amazon ECS, the
source IP address from which the request was made, who made the request, when it was made, and so
on. To learn more about CloudTrail, including how to configure and enable it, see the AWS CloudTrail
User Guide.
Amazon ECS Information in CloudTrail
When CloudTrail logging is enabled in your AWS account, API calls made to Amazon ECS actions are
tracked in log files. Amazon ECS records are written together with other AWS service records in a log file.
CloudTrail determines when to create and write to a new file based on a time period and file size.
All of the Amazon ECS actions are logged and are documented in the Amazon EC2 Container Service API
Reference. For example, calls to the CreateService, RunTask, and RegisterContainerInstance actions
generate entries in the CloudTrail log files.
Every log entry contains information about who generated the request. The user identity information
in the log helps you determine whether the request was made with root or IAM user credentials,
with temporary security credentials for a role or federated user, or by another AWS service. For more
information, see the userIdentity field in the CloudTrail Event Reference.
You can store your log files in your bucket for as long as you want, but you can also define Amazon S3
life cycle rules to archive or delete log files automatically. By default, your log files are encrypted by
using Amazon S3 server-side encryption (SSE).
You can choose to have CloudTrail publish Amazon SNS notifications when new log files are delivered if
you want to take quick action upon log file delivery. For more information, see Configuring Amazon SNS
Notifications.
You can also aggregate Amazon ECS log files from multiple AWS regions and multiple AWS accounts into
a single S3 bucket. For more information, see Aggregating CloudTrail Log Files to a Single Amazon S3
Bucket.
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Understanding Amazon ECS Log File Entries
Understanding Amazon ECS Log File Entries
CloudTrail log files can contain one or more log entries where each entry is made up of multiple JSON-
formatted events. A log entry represents a single request from any source and includes information
about the requested action, any parameters, the date and time of the action, and so on. The log entries
are not guaranteed to be in any particular order. That is, they are not an ordered stack trace of the public
API calls.
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Checking Stopped Tasks for Errors
Amazon ECS Troubleshooting
You may need to troubleshoot issues with your load balancers, tasks, services, or container instances.
This chapter helps you find diagnostic information from the Amazon ECS container agent, the Docker
daemon on the container instance, and the service event log in the Amazon ECS console.
Topics
•Checking Stopped Tasks for Errors (p. 273)
•Service Event Messages (p. 275)
•CannotCreateContainerError: API error (500): devmapper (p. 277)
•Troubleshooting Service Load Balancers (p. 278)
•Enabling Docker Debug Output (p. 280)
•Amazon ECS Log File Locations (p. 281)
•Amazon ECS Logs Collector (p. 282)
•Agent Introspection Diagnostics (p. 283)
•Docker Diagnostics (p. 284)
•API failures Error Messages (p. 286)
Checking Stopped Tasks for Errors
If you have trouble starting a task (for example, you run the task and the task displays a PENDING status
and then disappears) your task might be stopping because of an error. You can view errors like this in the
Amazon ECS console by displaying the stopped task and inspecting it for error messages.
To check stopped tasks for errors
1. Open the Amazon ECS console at https://console.aws.amazon.com/ecs/.
2. On the Clusters page, choose the cluster in which your stopped task resides.
3. On the Cluster : clustername page, choose the Tasks tab to view your tasks.
4. In the Desired task status table header, choose Stopped to view stopped tasks, and then choose the
stopped task you want to inspect. The most recent stopped tasks are listed first.
5. In the Details section, inspect the Stopped reason field to see the reason the task was stopped.
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Checking Stopped Tasks for Errors
Some possible reasons and their explanations are listed below:
Task failed ELB health checks in (elb elb-name)
The current task failed the ELB health check for the load balancer that is associated with the
task's service. For more information, see Troubleshooting Service Load Balancers (p. 278).
Scaling activity initiated by (deployment deployment-id)
When you reduce the desired count of a stable service, some tasks need to be stopped in order
to reach the desired number. Tasks that are stopped by downscaling services have this stopped
reason.
Host EC2 (instance id) stopped/terminated
If you stop or terminate a container instance with running tasks, then the tasks are given this
stopped reason.
Container instance deregistration forced by user
If you force the deregistration of a container instance with running tasks, then the tasks are
given this stopped reason.
Essential container in task exited
Containers marked as essential in task definitions cause a task to stop if they exit or die. When
an essential container exiting is the cause of a stopped task, the Step 6 (p. 275) can provide
more diagnostic information as to why the container stopped.
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Service Event Messages
6. If you have a container that has stopped, expand the container and inspect the Status reason row to
see what caused the task state to change.
In the previous example, the container image name cannot be found. This can happen if you misspell
the image name.
If this inspection does not provide enough information, you can connect to the container instance
with SSH and inspect the Docker container locally. For more information, see Inspect Docker
Containers (p. 285).
Service Event Messages
If you are troubleshooting a problem with a service, the first place you should check for diagnostic
information is the service event log.
To check the service event log in the Amazon ECS console
1. Open the Amazon ECS console at https://console.aws.amazon.com/ecs/.
2. On the Clusters page, choose the cluster in which your service resides.
3. On the Cluster : clustername page, choose the service that you would like to inspect.
4. On the Service : servicename page, choose the Events tab.
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5. Examine the Message column for errors or other helpful information.
(service service-name) was unable to place a task because the resources could not be found.
In the above image, this service could not find the available resources to add another task. The possible
causes for this are:
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CannotCreateContainerError:
API error (500): devmapper
Not enough ports
If your task uses fixed host port mapping (for example, your task uses port 80 on the host for a web
server), you must have at least one container instance per task, because only one container can use a
single host port at a time. You should add container instances to your cluster or reduce your number
of desired tasks.
Not enough memory
If your task definition specifies 1000 MiB of memory, and the container instances in your cluster
each have 1024 MiB of memory, you can only run one copy of this task per container instance. You
can experiment with less memory in your task definition so that you could launch more than one
task per container instance, or launch more container instances into your cluster.
Not enough CPU
A container instance has 1,024 CPU units for every CPU core. If your task definition specifies 1,000
CPU units, and the container instances in your cluster each have 1,024 CPU units, you can only
run one copy of this task per container instance. You can experiment with less CPU units in your
task definition so that you could launch more than one task per container instance, or launch more
container instances into your cluster.
Container instance missing required attribute
Some task definition parameters require a specific Docker remote API version to be installed on the
container instance. Others, such as the logging driver options, require the container instances to
register those log drivers with the ECS_AVAILABLE_LOGGING_DRIVERS agent configuration variable.
If your task definition contains a parameter that requires a specific container instance attribute,
and you do not have any available container instances that can satisfy this requirement, the task
cannot be placed. For more information on which attributes are required for specific task definition
parameters and agent configuration variables, see Task Definition Parameters (p. 98) and Amazon
ECS Container Agent Configuration (p. 79).
(service service-name) was unable to place a task because no container instance met all of its
requirements. The closest matching container-instance container-instance-id encountered error
"AGENT".
The Amazon ECS container agent on the closest matching container instance for task placement is
disconnected. If you can connect to the container instance with SSH, you can examine the agent logs;
for more information, see Amazon ECS Container Agent Log (p. 281). You should also verify that the
agent is running on the instance. If you are using the Amazon ECS-optimized AMI, you can try stopping
and restarting the agent with the following commands:
[ec2-user ~]$ sudo stop ecs
ecs stop/waiting
[ec2-user ~]$ sudo start ecs
ecs start/running, process 26119
(service service-name) (instance instance-id) is unhealthy in (elb elb-name) due to (reason Instance
has failed at least the UnhealthyThreshold number of health checks consecutively.)
This service is registered with a load balancer and the load balancer health checks are failing. For more
information, see Troubleshooting Service Load Balancers (p. 278).
CannotCreateContainerError: API error (500): devmapper
The following Docker error indicates that the thin pool storage on your container instance is full, and
that the Docker daemon cannot create new containers:
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Troubleshooting Service Load Balancers
CannotCreateContainerError: API error (500): devmapper: Thin Pool has 4350 free data blocks
which is less than minimum required 4454 free data blocks. Create more free space in thin
pool or use dm.min_free_space option to change behavior
By default, Amazon ECS-optimized AMIs from version 2015.09.d and later launch with an 8-GiB volume
for the operating system that is attached at /dev/xvda and mounted as the root of the file system. There
is an additional 22-GiB volume that is attached at /dev/xvdcz that Docker uses for image and metadata
storage. If this storage space is filled up, the Docker deamon cannot create new containers.
The easiest way to add storage to your container instances is to terminate the existing instances and
launch new ones with larger data storage volumes. However, if you are unable to do this, you can add
storage to the volume group that Docker uses and extend its logical volume by following the procedures
in Storage Configuration (p. 36).
If your container instance storage is filling up too quickly, there are a few actions that you can take to
reduce this effect:
• (Amazon ECS container agent 1.8.0 and later) Reduce the amount of time that stopped or exited
containers remain on your container instances. The ECS_ENGINE_TASK_CLEANUP_WAIT_DURATION agent
configuration variable sets the time duration to wait from when a task is stopped until the Docker
container is removed (by default, this value is 3 hours). This removes the Docker container data. If this
value is set too low, you may not be able to inspect your stopped containers or view the logs before
they are removed. For more information, see Amazon ECS Container Agent Configuration (p. 79).
• Remove non-running containers and unused images from your container instances. You can use the
following example commands to manually remove stopped containers and unused images. Deleted
containers cannot be inspected later, and deleted images must be pulled again before starting new
containers from them.
To remove non-running containers, execute the following command on your container instance:
$ docker rm $(docker ps -aq)
To remove unused images, execute the following command on your container instance:
$ docker rmi $(docker images -q)
• Remove unused data blocks within containers. You can use the following command to run fstrim on
any running container and discard any data blocks that are unused by the container file system.
$ sudo sh -c "docker ps -q | xargs docker inspect --format='{{ .State.Pid }}' | xargs -IZ
fstrim /proc/Z/root/"
Troubleshooting Service Load Balancers
Amazon ECS services can register tasks with an Elastic Load Balancing load balancer. Load balancer
configuration errors are common causes for stopped tasks. If your stopped tasks were started by services
that use a load balancer, consider the following possible causes.
Improper IAM permissions for the ecsServiceRole IAM role
The ecsServiceRole allows Amazon ECS services to register container instances with Elastic
Load Balancing load balancers. You must have the proper permissions set for this role. For more
information, see Amazon ECS Service Scheduler IAM Role (p. 212).
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Container instance security group
If your container is mapped to port 80 on your container instance, your container instance security
group must allow inbound traffic on port 80 for the load balancer health checks to pass.
Elastic Load Balancing load balancer not configured for all Availability Zones
Your load balancer should be configured to use all of the Availability Zones in a region, or at least
all of the Availability Zones in which your container instances reside. If a service uses a load balancer
and starts a task on a container instance that resides in an Availability Zone that the load balancer is
not configured to use, the task never passes the health check and it is killed.
Elastic Load Balancing load balancer health check misconfigured
The load balancer health check parameters can be overly restrictive or point to resources that do not
exist. If a container instance is determined to be unhealthy, it is removed from the load balancer. Be
sure to verify that the following parameters are configured correctly for your service load balancer.
Ping Port
The Ping Port value for a load balancer health check is the port on the container instances
that the load balancer checks to determine if it is healthy. If this port is misconfigured, the load
balancer will likely deregister your container instance from itself. This port should be configured
to use the hostPort value for the container in your service's task definition that you are using
with the health check.
Ping Path
This value is often set to index.html, but if your service does not respond to that request, then
the health check fails. If your container does not have an index.html file, you can set this to / to
target the base URL for the container instance.
Response Timeout
This is the amount of time that your container has to return a response to the health check ping.
If this value is lower than the amount of time required for a response, the health check fails.
Health Check Interval
This is the amount of time between health check pings. The shorter your health check intervals
are, the faster your container instance can reach the Unhealthy Threshold.
Unhealthy Threshold
This is the number of times your health check can fail before your container instance is
considered unhealthy. If you have an unhealthy threshold of 2, and a health check interval of 30
seconds, then your task has 60 seconds to respond to the health check ping before it is assumed
unhealthy. You can raise the unhealthy threshold or the health check interval to give your tasks
more time to respond.
Unable to update the service servicename: Load balancer container name or port changed in task
definition
If your service uses a load balancer, the load balancer configuration defined for your service when
it was created cannot be changed. If you update the task definition for the service, the container
name and container port that were specified when the service was created must remain in the task
definition.
To change the load balancer name, the container name, or the container port associated with a
service load balancer configuration, you must create a new service.
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Enabling Docker Debug Output
Enabling Docker Debug Output
If you are having trouble with Docker containers or images, you can enable debug mode on your Docker
daemon. Enabling debugging provides more verbose output from the daemon and you can use this
information to find out more about why your containers or images are having issues.
Enabling Docker debug mode can be especially useful in retrieving error messages that are sent from
container registries, such as Amazon ECR, and, in many circumstances, enabling debug mode is the only
way to see these error messages.
Important
This procedure is written for the Amazon ECS-optimized AMI. For other operating systems,
see Enable debugging and Control and configure Docker with systemd in the Docker
documentation.
To enable Docker daemon debug mode on the Amazon ECS-optimized AMI
1. Connect to your container instance. For more information, see Connect to Your Container
Instance (p. 51).
2. Open the Docker options file with a text editor, such as vi. For the Amazon ECS-optimized AMI, the
Docker options file is at /etc/sysconfig/docker.
3. Find the Docker options statement and add the -D option to the string, inside the quotes.
Note
If the Docker options statement begins with a #, you need to remove that character to
uncomment the statement and enable the options.
For the Amazon ECS-optimized AMI, the Docker options statement is called OPTIONS. For example:
# Additional startup options for the Docker daemon, for example:
# OPTIONS="--ip-forward=true --iptables=true"
# By default we limit the number of open files per container
OPTIONS="-D --default-ulimit nofile=1024:4096"
4. Save the file and exit your text editor.
5. Restart the Docker daemon.
$ sudo service docker restart
Output:
Stopping docker: [ OK ]
Starting docker: . [ OK ]
6. Restart the Amazon ECS agent.
$ sudo start ecs
Your Docker logs should now show more verbose output. For example:
time="2015-12-30T21:48:21.907640838Z" level=debug msg="Unexpected response from
server: \"{\\\"errors\\\":[{\\\"code\\\":\\\"DENIED\\\",\\\"message\\\":\\\"User:
arn:aws:sts::1111:assumed-role/ecrReadOnly/i-abcdefg is not authorized to perform:
ecr:InitiateLayerUpload on resource: arn:aws:ecr:us-east-1:1111:repository/nginx_test
\\\"}]}\\n\" http.Header{\"Connection\":[]string{\"keep-alive\"}, \"Content-Type\":
[]string{\"application/json; charset=utf-8\"}, \"Date\":[]string{\"Wed, 30 Dec 2015
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21:48:21 GMT\"}, \"Docker-Distribution-Api-Version\":[]string{\"registry/2.0\"},
\"Content-Length\":[]string{\"235\"}}"
Amazon ECS Log File Locations
Amazon ECS stores logs in the /var/log/ecs folder of your container instances. There are logs available
from the Amazon ECS container agent and the ecs-init service that controls the state of the agent
(start/stop) on the container instance. You can view these log files by connecting to a container instance
using SSH. For more information, see Connect to Your Container Instance (p. 51).
Note
If you are unsure how to collect all of the various logs on your container instances, you can use
the Amazon ECS logs collector. For more information, see Amazon ECS Logs Collector (p. 282).
Amazon ECS Container Agent Log
The Amazon ECS container agent stores logs at /var/log/ecs/ecs-agent.log.timestamp.
Note
You can increase the verbosity of the container agent logs by setting ECS_LOGLEVEL=debug
and restarting the container agent. For more information, see Amazon ECS Container Agent
Configuration (p. 79).
[ec2-user ~]$ cat /var/log/ecs/ecs-agent.log.2016-08-15-15
2016-08-15T15:54:41Z [INFO] Starting Agent: Amazon ECS Agent - v1.12.0 (895f3c1)
2016-08-15T15:54:41Z [INFO] Loading configuration
2016-08-15T15:54:41Z [WARN] Invalid value for task cleanup duration, will be overridden to
3h0m0s, parsed value 0, minimum threshold 1m0s
2016-08-15T15:54:41Z [INFO] Checkpointing is enabled. Attempting to load state
2016-08-15T15:54:41Z [INFO] Loading state! module="statemanager"
2016-08-15T15:54:41Z [INFO] Detected Docker versions [1.17 1.18 1.19 1.20 1.21 1.22]
2016-08-15T15:54:41Z [INFO] Registering Instance with ECS
2016-08-15T15:54:41Z [INFO] Registered! module="api client"
Amazon ECS ecs-init Log
The ecs-init process stores logs at /var/log/ecs/ecs-init.log.timestamp.
[ec2-user ~]$ cat /var/log/ecs/ecs-init.log.2015-04-22-20
2015-04-22T20:51:45Z [INFO] pre-start
2015-04-22T20:51:45Z [INFO] Loading Amazon EC2 Container Service Agent into Docker
2015-04-22T20:51:46Z [INFO] start
2015-04-22T20:51:46Z [INFO] No existing agent container to remove.
2015-04-22T20:51:46Z [INFO] Starting Amazon EC2 Container Service Agent
IAM Roles for Tasks Credential Audit Log
When the IAM roles for tasks credential provider is used to provide credentials to tasks, these requests
are logged in /var/log/ecs/audit.log.YYYY-MM-DD-HH.
The log entry format is as follows:
• Timestamp
• HTTP response code
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• IP address and port number of request origin
• Relative URI of the credential provider
• The user agent that made the request
• The task ARN that the requesting container belongs to
• The GetCredentials API name and version number
• The Amazon ECS cluster name that the container instance is registered to
• The container instance ARN
An example log entry is shown below:
[ec2-user ~]$ cat /var/log/ecs/audit.log.2016-07-13-16
2016-07-13T16:11:53Z 200 172.17.0.5:52444 "/v1/credentials" "python-requests/2.7.0
CPython/2.7.6 Linux/4.4.14-24.50.amzn1.x86_64" TASK_ARN GetCredentials
1 CLUSTER_NAME CONTAINER_INSTANCE_ARN
Amazon ECS Logs Collector
If you are unsure how to collect all of the various logs on your container instances, you can use the
Amazon ECS logs collector, which is available on GitHub. The script collects general operating system
logs as well as Docker and Amazon ECS container agent logs, which can be helpful for troubleshooting
AWS Support cases, and then it compresses and archives the collected information into a single file
that can easily be shared for diagnostic purposes. It also supports enabling debug mode for the Docker
daemon and the Amazon ECS container agent on Amazon Linux variants, such as the Amazon ECS-
optimized AMI. Currently, the Amazon ECS logs collector supports the following operating systems:
• Amazon Linux
• Red Hat Enterprise Linux 7
• Debian 8
Note
The source code for the Amazon ECS logs collector is available on GitHub. We encourage you to
submit pull requests for changes that you would like to have included. However, Amazon Web
Services does not currently provide support for running modified copies of this software.
To download and run the Amazon ECS logs collector
1. Connect to your container instance. For more information, see Connect to Your Container
Instance (p. 51).
2. Download the Amazon ECS logs collector script.
[ec2-user ~]$ curl -O https://raw.githubusercontent.com/awslabs/ecs-logs-collector/
master/ecs-logs-collector.sh
3. Run the script to collect the logs and create the archive.
Note
To enable debug mode for the Docker daemon and the Amazon ECS container agent, add
the --mode=debug option to the command below.
[ec2-user ~]$ sudo bash ./ecs-logs-collector.sh
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Agent Introspection Diagnostics
After you have run the script, you can examine the collected logs in the collect folder that the script
created. The collect.tgz file is a compressed archive of all of the logs, which you can share with AWS
Support for diagnostic help.
Agent Introspection Diagnostics
The Amazon ECS agent introspection API can provide helpful diagnostic information. For example, you
can use the agent introspection API to get the Docker ID for a container in your task. You can use the
agent introspection API by connecting to a container instance using SSH. For more information, see
Connect to Your Container Instance (p. 51).
The below example shows two tasks, one that is currently running and one that was stopped.
Note
The command below is piped through the python -mjson.tool for greater readability.
[ec2-user ~]$ curl http://localhost:51678/v1/tasks | python -mjson.tool
Output:
% Total % Received % Xferd Average Speed Time Time Time Current
Dload Upload Total Spent Left Speed
100 1095 100 1095 0 0 117k 0 --:--:-- --:--:-- --:--:-- 133k
{
"Tasks": [
{
"Arn": "arn:aws:ecs:us-west-2:aws_account_id:task/090eff9b-1ce3-4db6-848a-
a8d14064fd24",
"Containers": [
{
"DockerId":
"189a8ff4b5f04affe40e5160a5ffadca395136eb5faf4950c57963c06f82c76d",
"DockerName": "ecs-console-sample-app-static-6-simple-
app-86caf9bcabe3e9c61600",
"Name": "simple-app"
},
{
"DockerId":
"f7f1f8a7a245c5da83aa92729bd28c6bcb004d1f6a35409e4207e1d34030e966",
"DockerName": "ecs-console-sample-app-static-6-busybox-
ce83ce978a87a890ab01",
"Name": "busybox"
}
],
"Family": "console-sample-app-static",
"KnownStatus": "STOPPED",
"Version": "6"
},
{
"Arn": "arn:aws:ecs:us-west-2:aws_account_id:task/1810e302-eaea-4da9-
a638-097bea534740",
"Containers": [
{
"DockerId":
"dc7240fe892ab233dbbcee5044d95e1456c120dba9a6b56ec513da45c38e3aeb",
"DockerName": "ecs-console-sample-app-static-6-simple-app-
f0e5859699a7aecfb101",
"Name": "simple-app"
},
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Docker Diagnostics
{
"DockerId":
"096d685fb85a1ff3e021c8254672ab8497e3c13986b9cf005cbae9460b7b901e",
"DockerName": "ecs-console-sample-app-static-6-
busybox-92e4b8d0ecd0cce69a01",
"Name": "busybox"
}
],
"DesiredStatus": "RUNNING",
"Family": "console-sample-app-static",
"KnownStatus": "RUNNING",
"Version": "6"
}
]
}
In the above example, the stopped task (090eff9b-1ce3-4db6-848a-a8d14064fd24) has two containers.
You can use docker inspect container-ID to view detailed information on each container. For more
information, see Amazon ECS Container Agent Introspection (p. 90).
Docker Diagnostics
Docker provides several diagnostic tools that can help you troubleshoot problems with your containers
and tasks. For more information about all of the available Docker command line utilities, go to the
Docker Command Line topic in the Docker documentation. You can access the Docker command line
utilities by connecting to a container instance using SSH. For more information, see Connect to Your
Container Instance (p. 51).
The exit codes that Docker containers report can also provide some diagnostic information (for example,
exit code 137 means that the container received a SIGKILL signal). For more information, see Exit Status
in the Docker documentation.
List Docker Containers
You can use the docker ps command on your container instance to list the running containers. In the
below example, only the Amazon ECS container agent is running. For more information, go to docker ps
in the Docker documentation.
[ec2-user ~]$ docker ps
Output:
CONTAINER ID IMAGE COMMAND CREATED
STATUS PORTS NAMES
cee0d6986de0 amazon/amazon-ecs-agent:latest "/agent" 22 hours ago
Up 22 hours 127.0.0.1:51678->51678/tcp ecs-agent
You can use the docker ps -a command to see all containers (even stopped or killed containers). This
is helpful for listing containers that are unexpectedly stopping. In the following example, container
f7f1f8a7a245 exited 9 seconds ago, so it would not show up in a docker ps output without the -a flag.
[ec2-user ~]$ docker ps -a
Output:
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View Docker Logs
CONTAINER ID IMAGE COMMAND
CREATED STATUS PORTS NAMES
db4d48e411b1 amazon/ecs-emptyvolume-base:autogenerated "not-applicable" 19
seconds ago ecs-console-
sample-app-static-6-internalecs-emptyvolume-source-c09288a6b0cba8a53700
f7f1f8a7a245 busybox:buildroot-2014.02 "\"sh -c '/bin/sh -c 22
hours ago Exited (137) 9 seconds ago ecs-console-
sample-app-static-6-busybox-ce83ce978a87a890ab01
189a8ff4b5f0 httpd:2 "httpd-foreground" 22
hours ago Exited (137) 40 seconds ago ecs-console-
sample-app-static-6-simple-app-86caf9bcabe3e9c61600
0c7dca9321e3 amazon/ecs-emptyvolume-base:autogenerated "not-applicable" 22
hours ago ecs-console-
sample-app-static-6-internalecs-emptyvolume-source-90fefaa68498a8a80700
cee0d6986de0 amazon/amazon-ecs-agent:latest "/agent" 22
hours ago Up 22 hours 127.0.0.1:51678->51678/tcp ecs-agent
View Docker Logs
You can view the STDOUT and STDERR streams for a container with the docker logs command. In this
example, the logs are displayed for the dc7240fe892a container and piped through the head command
for brevity. For more information, go to docker logs in the Docker documentation.
[ec2-user ~]$ docker logs dc7240fe892a | head
Output:
AH00558: httpd: Could not reliably determine the server's fully qualified domain name,
using 172.17.0.11. Set the 'ServerName' directive globally to suppress this message
AH00558: httpd: Could not reliably determine the server's fully qualified domain name,
using 172.17.0.11. Set the 'ServerName' directive globally to suppress this message
[Thu Apr 23 19:48:36.956682 2015] [mpm_event:notice] [pid 1:tid 140327115417472] AH00489:
Apache/2.4.12 (Unix) configured -- resuming normal operations
[Thu Apr 23 19:48:36.956827 2015] [core:notice] [pid 1:tid 140327115417472] AH00094:
Command line: 'httpd -D FOREGROUND'
10.0.1.86 - - [23/Apr/2015:19:48:59 +0000] "GET / HTTP/1.1" 200 348
10.0.0.154 - - [23/Apr/2015:19:48:59 +0000] "GET / HTTP/1.1" 200 348
10.0.1.86 - - [23/Apr/2015:19:49:28 +0000] "GET / HTTP/1.1" 200 348
10.0.0.154 - - [23/Apr/2015:19:49:29 +0000] "GET / HTTP/1.1" 200 348
10.0.1.86 - - [23/Apr/2015:19:49:50 +0000] "-" 408 -
10.0.0.154 - - [23/Apr/2015:19:49:50 +0000] "-" 408 -
10.0.1.86 - - [23/Apr/2015:19:49:58 +0000] "GET / HTTP/1.1" 200 348
10.0.0.154 - - [23/Apr/2015:19:49:59 +0000] "GET / HTTP/1.1" 200 348
10.0.1.86 - - [23/Apr/2015:19:50:28 +0000] "GET / HTTP/1.1" 200 348
10.0.0.154 - - [23/Apr/2015:19:50:29 +0000] "GET / HTTP/1.1" 200 348
time="2015-04-23T20:11:20Z" level="fatal" msg="write /dev/stdout: broken pipe"
Inspect Docker Containers
If you have the Docker ID of a container, you can inspect it with the docker inspect command. Inspecting
containers provides the most detailed view of the environment in which a container was launched. For
more information, go to docker inspect in the Docker documentation.
[ec2-user ~]$ docker inspect dc7240fe892a
Output:
[{
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"AppArmorProfile": "",
"Args": [],
"Config": {
"AttachStderr": false,
"AttachStdin": false,
"AttachStdout": false,
"Cmd": [
"httpd-foreground"
],
"CpuShares": 10,
"Cpuset": "",
"Domainname": "",
"Entrypoint": null,
"Env": [
"PATH=/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/local/
apache2/bin",
"HTTPD_PREFIX=/usr/local/apache2",
"HTTPD_VERSION=2.4.12",
"HTTPD_BZ2_URL=https://www.apache.org/dist/httpd/httpd-2.4.12.tar.bz2"
],
"ExposedPorts": {
"80/tcp": {}
},
"Hostname": "dc7240fe892a",
...
API failures Error Messages
In some cases, an API call that you have triggered through the Amazon ECS console or the AWS CLI
exits with a failures error message. The following possible API failures error messages are explained
below for each API call. The failures occur on a particular resource, and the resource in parentheses is the
resource associated with the failure.
Many resources are region-specific, so make sure the console is set to the correct region for your
resources, or that your AWS CLI commands are being sent to the correct region with the --region
region option.
•DescribeClusters
MISSING (cluster ID)
Your cluster was not found. The cluster name may not have been spelled correctly or the wrong
region may be specified.
•DescribeInstances
MISSING (container instance ID)
The container instance you are attempting to describe does not exist. Perhaps the wrong cluster or
region has been specified, or the container instance ARN or ID is misspelled.
•DescribeServices
MISSING (service ID)
The service you are attempting to describe does not exist. Perhaps the wrong cluster or region has
been specified, or the container instance ARN or ID is misspelled.
•DescribeTasks
MISSING (task ID)
The task you are trying to describe does not exist. Perhaps the wrong cluster or region has been
specified, or the task ARN or ID is misspelled.
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•RunTask or StartTask
RESOURCE:* (container instance ID)
The resource or resources requested by the task are unavailable on the given container instance. If
the resource is CPU or memory, you may need to add container instances to your cluster.
AGENT (container instance ID)
The container instance that you attempted to launch a task onto has an agent which is currently
disconnected. In order to prevent extended wait times for task placement, the request was
rejected.
ATTRIBUTE (container instance ID)
Your task definition contains a parameter that requires a specific container instance attribute that
is not available on your container instances. For more information on which attributes are required
for specific task definition parameters and agent configuration variables, see Task Definition
Parameters (p. 98) and Amazon ECS Container Agent Configuration (p. 79).
•StartTask
MISSING (container instance ID)
The container instance you attempted to launch the task onto does not exist. Perhaps the wrong
cluster or region has been specified, or the container instance ARN or ID is misspelled.
INACTIVE (container instance ID)
The container instance that you attempted to launch a task onto was previously deregistered with
Amazon ECS and cannot be used.
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Windows Container Caveats
Windows Containers (Beta)
Amazon ECS now supports Windows containers on container instances that are launched with the
Microsoft Windows Server 2016 Base with Containers AMI. This is considered a beta, and you should not
use this for a production environment at this time.
Windows container instances use their own version of the Amazon ECS container agent. On Windows
Server 2016, the Amazon ECS container agent runs as a process on the host. Unlike the Linux platform,
the agent does not run inside a container because it uses the host's registry and the named pipe at \\.
\pipe\docker_engine to communicate with the Docker daemon.
The source code for the Amazon ECS container agent is available on GitHub. We encourage you to submit
pull requests for changes that you would like to have included. However, Amazon Web Services does
not currently provide support for running modified copies of this software. You can view open issues for
Amazon ECS and Windows on our GitHub issues page.
Topics
•Windows Container Caveats (p. 288)
•Windows Containers AWS CloudFormation Template (p. 289)
•Getting Started with Windows Containers (p. 302)
•Windows Task Definitions (p. 308)
•Windows IAM Roles for Tasks (p. 311)
•Pushing Windows Images to Amazon ECR (p. 312)
Windows Container Caveats
Here are some things you should know about Windows containers and Amazon ECS.
• Windows containers cannot run on Linux container instances and vice versa. To ensure proper task
placement for Windows and Linux tasks, you should keep Windows and Linux container instances in
separate clusters, and only place Windows tasks on Windows clusters.
• Windows containers and container instances cannot support all the task definition parameters that are
available for Linux containers and container instances. For some parameters, they are not supported
at all, and others behave differently on Windows than they do on Linux. For more information, see
Windows Task Definitions (p. 308).
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• The IAM roles for tasks feature requires that you configure your Windows container instances to allow
the feature at launch, and your containers must run some provided PowerShell code when they use the
feature. For more information, see Windows IAM Roles for Tasks (p. 311).
• The IAM roles for tasks feature uses a credential proxy to provide credentials to the containers. This
credential proxy occupies port 80 on the container instance, so if you use IAM roles for tasks, port 80
is not available for tasks. For web service containers, you can use an Application Load Balancer and
dynamic port mapping to provide standard HTTP port 80 connections to your containers. For more
information, see Service Load Balancing (p. 141).
• The Windows server Docker images are large (9 GiB), so your container instances require more storage
space than Linux container instances, which typically have smaller image sizes.
• Container instances can take up to 15 minutes to download and extract the Windows server Docker
images the first time they use them. This time can be doubled if you enable IAM roles for tasks.
Windows Containers AWS CloudFormation
Template
Here is an AWS CloudFormation template that you can use to get started with Windows containers. For
more information about creating stacks with AWS CloudFormation templates, see Creating a Stack on
the AWS CloudFormation Console in the AWS CloudFormation User Guide.
This AWS CloudFormation template provides a reference implementation of an Amazon ECS cluster
running a sample application. This template requires an existing VPC with at least two public subnets.
The template creates an Amazon ECS cluster with a configurable number of container instances, an
Application Load Balancer, the necessary security group configuration, an Amazon ECS task definition,
an Amazon ECS service, and an Application Auto Scaling policy that allows the service to scale out in
response to metrics emitted by the Application Load Balancer.
The container instances that are launched into the cluster are configured with an Auto Scaling group
and an associated launch configuration. The launch configuration contains configuration data for the
container instances, such as volume type and size, instance type, IAM role, and Amazon EC2 user data.
The user data is run on every instance in the Auto Scaling group at boot to pull down the ECS Agent,
configure it, and run it, so that the instance can register into the ECS cluster.
An Amazon ECS task definition and service are also created by the template. The task definition
references the microsoft/iis container image and provides a command for it to execute at startup, as
well as additional parameters like CPU shares and which CloudWatch Logs log group to send logging
information to. The service is configured to run one or more copies of this task definition on the cluster
and associate the container with an Application Load Balancer. Application Auto Scaling is also enabled
on the service.
The template also creates three different IAM roles. The first is the ECSServiceRole, which allows
Amazon ECS to manage your service on your behalf; for example, to register new tasks into your
Application Load Balancer. The next role is the Ec2Role, which provides permissions to each EC2 instance
in the cluster and allows the container agent to perform its necessary actions, like polling the ECS APIs
on your behalf. Finally, we create a role for Application Auto Scaling to help your service scale in and out
in response to CloudWatch alarms on your behalf.
Note
The AMIID's included in this template are updated periodically so if you use this template you
should confirm they are current before deploying or updating your cluster.
{
"AWSTemplateFormatVersion": "2010-09-09",
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"Parameters": {
"KeyName": {
"Type": "AWS::EC2::KeyPair::KeyName",
"Description": "Name of an existing EC2 key pair to enable SSH access to the ECS
instances."
},
"VpcId": {
"Type": "AWS::EC2::VPC::Id",
"Description": "Select a default VPC ID."
},
"SubnetID": {
"Type": "List<AWS::EC2::Subnet::Id>",
"Description": "Select a default subnet ID in your selected VPC."
},
"DesiredCapacity": {
"Type": "Number",
"Default": "1",
"Description": "Number of instances to launch in your ECS cluster."
},
"MaxSize": {
"Type": "Number",
"Default": "1",
"Description": "Maximum number of instances that can be launched in your ECS
cluster."
},
"InstanceType": {
"Description": "EC2 instance type",
"Type": "String",
"Default": "t2.micro",
"AllowedValues": [
"t2.micro",
"t2.small",
"t2.medium",
"t2.large",
"m3.medium",
"m3.large",
"m3.xlarge",
"m3.2xlarge",
"m4.large",
"m4.xlarge",
"m4.2xlarge",
"m4.4xlarge",
"m4.10xlarge",
"c4.large",
"c4.xlarge",
"c4.2xlarge",
"c4.4xlarge",
"c4.8xlarge",
"c3.large",
"c3.xlarge",
"c3.2xlarge",
"c3.4xlarge",
"c3.8xlarge",
"r3.large",
"r3.xlarge",
"r3.2xlarge",
"r3.4xlarge",
"r3.8xlarge",
"i2.xlarge",
"i2.2xlarge",
"i2.4xlarge",
"i2.8xlarge"
],
"ConstraintDescription": "Please choose a valid instance type."
}
},
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"Mappings": {
"AWSRegionToAMI": {
"ap-south-1": {
"AMIID": "ami-d55e23ba"
},
"eu-west-2": {
"AMIID": "ami-44495e20"
},
"eu-west-1": {
"AMIID": "ami-a0fcf5c6"
},
"ap-northeast-2": {
"AMIID": "ami-f30fd29d"
},
"ap-northeast-1": {
"AMIID": "ami-26f7cb41"
},
"sa-east-1": {
"AMIID": "ami-1baac577"
},
"ca-central-1": {
"AMIID": "ami-0f7bc76b"
},
"ap-southeast-1": {
"AMIID": "ami-fbb23698"
},
"ap-southeast-2": {
"AMIID": "ami-d78288b4"
},
"eu-central-1": {
"AMIID": "ami-70ae771f"
},
"us-east-1": {
"AMIID": "ami-17106201"
},
"us-east-2": {
"AMIID": "ami-b1d2f5d4"
},
"us-west-1": {
"AMIID": "ami-1e70517e"
},
"us-west-2": {
"AMIID": "ami-f081e590"
}
}
},
"Resources": {
"EcsSecurityGroup": {
"Type": "AWS::EC2::SecurityGroup",
"Properties": {
"GroupDescription": "ECS Security Group",
"VpcId": {
"Ref": "VpcId"
}
}
},
"EcsSecurityGroupHTTPinbound": {
"Type": "AWS::EC2::SecurityGroupIngress",
"Properties": {
"GroupId": {
"Ref": "EcsSecurityGroup"
},
"IpProtocol": "tcp",
"FromPort": "80",
"ToPort": "80",
"CidrIp": "0.0.0.0/0"
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}
},
"EcsSecurityGroupRDPinbound": {
"Type": "AWS::EC2::SecurityGroupIngress",
"Properties": {
"GroupId": {
"Ref": "EcsSecurityGroup"
},
"IpProtocol": "tcp",
"FromPort": "3389",
"ToPort": "3389",
"CidrIp": "0.0.0.0/0"
}
},
"EcsSecurityGroupALBports": {
"Type": "AWS::EC2::SecurityGroupIngress",
"Properties": {
"GroupId": {
"Ref": "EcsSecurityGroup"
},
"IpProtocol": "tcp",
"FromPort": "31000",
"ToPort": "61000",
"SourceSecurityGroupId": {
"Ref": "EcsSecurityGroup"
}
}
},
"ECSCluster": {
"Type": "AWS::ECS::Cluster"
},
"CloudwatchLogsGroup": {
"Type": "AWS::Logs::LogGroup",
"Properties": {
"LogGroupName": {
"Fn::Join": [
"-",
[
"ECSLogGroup",
{
"Ref": "AWS::StackName"
}
]
]
},
"RetentionInDays": 14
}
},
"taskdefinition": {
"Type": "AWS::ECS::TaskDefinition",
"Properties": {
"ContainerDefinitions": [
{
"Name": "windows_sample_app",
"Cpu": "100",
"Essential": "true",
"Image": "microsoft/iis",
"Memory": "500",
"EntryPoint": [
"powershell",
"-Command"
],
"Command": [
"New-Item -Path C:\\inetpub\\wwwroot\\index.html -Type file -Value '<html>
<head> <title>Amazon ECS Sample App</title> <style>body {margin-top: 40px; background-
color: #333;} </style> </head><body> <div style=color:white;text-align:center> <h1>Amazon
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ECS Sample App</h1> <h2>Congratulations!</h2> <p>Your application is now running on a
container in Amazon ECS.</p>'; C:\\ServiceMonitor.exe w3svc"
],
"LogConfiguration": {
"LogDriver": "awslogs",
"Options": {
"awslogs-group": {
"Ref": "CloudwatchLogsGroup"
},
"awslogs-region": {
"Ref": "AWS::Region"
},
"awslogs-stream-prefix": "ecs-windows-sample-app"
}
},
"PortMappings": [
{
"ContainerPort": 80
}
]
}
]
}
},
"ECSALB": {
"Type": "AWS::ElasticLoadBalancingV2::LoadBalancer",
"Properties": {
"Name": "ECSALB",
"Scheme": "internet-facing",
"LoadBalancerAttributes": [
{
"Key": "idle_timeout.timeout_seconds",
"Value": "30"
}
],
"Subnets": {
"Ref": "SubnetID"
},
"SecurityGroups": [
{
"Ref": "EcsSecurityGroup"
}
]
}
},
"ALBListener": {
"Type": "AWS::ElasticLoadBalancingV2::Listener",
"DependsOn": "ECSServiceRole",
"Properties": {
"DefaultActions": [
{
"Type": "forward",
"TargetGroupArn": {
"Ref": "ECSTargetGroup"
}
}
],
"LoadBalancerArn": {
"Ref": "ECSALB"
},
"Port": "80",
"Protocol": "HTTP"
}
},
"ECSALBListenerRule": {
"Type": "AWS::ElasticLoadBalancingV2::ListenerRule",
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"DependsOn": "ALBListener",
"Properties": {
"Actions": [
{
"Type": "forward",
"TargetGroupArn": {
"Ref": "ECSTargetGroup"
}
}
],
"Conditions": [
{
"Field": "path-pattern",
"Values": [
"/"
]
}
],
"ListenerArn": {
"Ref": "ALBListener"
},
"Priority": 1
}
},
"ECSTargetGroup": {
"Type": "AWS::ElasticLoadBalancingV2::TargetGroup",
"DependsOn": "ECSALB",
"Properties": {
"HealthCheckIntervalSeconds": 10,
"HealthCheckPath": "/",
"HealthCheckProtocol": "HTTP",
"HealthCheckTimeoutSeconds": 5,
"HealthyThresholdCount": 2,
"Name": "ECSTargetGroup",
"Port": 80,
"Protocol": "HTTP",
"UnhealthyThresholdCount": 2,
"VpcId": {
"Ref": "VpcId"
}
}
},
"ECSAutoScalingGroup": {
"Type": "AWS::AutoScaling::AutoScalingGroup",
"Properties": {
"VPCZoneIdentifier": {
"Ref": "SubnetID"
},
"LaunchConfigurationName": {
"Ref": "ContainerInstances"
},
"MinSize": "1",
"MaxSize": {
"Ref": "MaxSize"
},
"DesiredCapacity": {
"Ref": "DesiredCapacity"
}
},
"CreationPolicy": {
"ResourceSignal": {
"Timeout": "PT15M"
}
},
"UpdatePolicy": {
"AutoScalingRollingUpdate": {
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"MinInstancesInService": "1",
"MaxBatchSize": "1",
"PauseTime": "PT15M",
"WaitOnResourceSignals": "true"
}
}
},
"ContainerInstances": {
"Type": "AWS::AutoScaling::LaunchConfiguration",
"Metadata": {
"AWS::CloudFormation::Init": {
"config": {
"files": {
"c:\\cfn\\cfn-hup.conf": {
"content": {
"Fn::Join": [
"",
[
"[main]\n",
"stack=",
{
"Ref": "AWS::StackId"
},
"\n",
"region=",
{
"Ref": "AWS::Region"
},
"\n"
]
]
}
},
"c:\\cfn\\hooks.d\\cfn-auto-reloader.conf": {
"content": {
"Fn::Join": [
"",
[
"[cfn-auto-reloader-hook]\n",
"triggers=post.update\n",
"path=Resources.ContainerInstances.Metadata.AWS::CloudFormation::Init
\n",
"action=cfn-init.exe -v -s ",
{
"Ref": "AWS::StackId"
},
" -r ContainerInstances",
" --region ",
{
"Ref": "AWS::Region"
},
"\n"
]
]
}
}
},
"services": {
"windows": {
"cfn-hup": {
"enabled": "true",
"ensureRunning": "true",
"files": [
"c:\\cfn\\cfn-hup.conf",
"c:\\cfn\\hooks.d\\cfn-auto-reloader.conf"
]
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}
}
}
}
}
},
"Properties": {
"ImageId": {
"Fn::FindInMap": [
"AWSRegionToAMI",
{
"Ref": "AWS::Region"
},
"AMIID"
]
},
"SecurityGroups": [
{
"Ref": "EcsSecurityGroup"
}
],
"InstanceType": {
"Ref": "InstanceType"
},
"IamInstanceProfile": {
"Ref": "EC2InstanceProfile"
},
"KeyName": {
"Ref": "KeyName"
},
"BlockDeviceMappings": [
{
"DeviceName": "/dev/sda1",
"Ebs": {
"VolumeSize": "100",
"VolumeType": "gp2"
}
}
],
"AssociatePublicIpAddress": "true",
"UserData": {
"Fn::Base64": {
"Fn::Join": [
"",
[
"<powershell> \n",
" # Set agent env variables for the Machine context (durable)\n",
" [Environment]::SetEnvironmentVariable(\"ECS_CLUSTER\", \"",
{
"Ref": "ECSCluster"
},
"\"",
", \"Machine\")",
"\n",
"$agentVersion = 'v1.14.0';",
"$agentZipUri = \"https://s3.amazonaws.com/amazon-ecs-agent/ecs-agent-
windows-$agentVersion.zip\";",
"$agentZipMD5Uri = \"$agentZipUri.md5\";",
"$ecsExeDir = \"$env:ProgramFiles\\Amazon\\ECS\";",
"$zipFile = \"$env:TEMP\\ecs-agent.zip\";",
"echo \"log\" >> c:\\windows\\temp\\log1.txt;",
"echo $zipFile >> c:\\windows\\temp\\log1.txt;",
"echo $ecsExeDir >> c:\\windows\\temp\\log1.txt;",
"$md5File = \"$env:TEMP\\ecs-agent.zip.md5\";",
"Invoke-RestMethod -OutFile $zipFile -Uri $agentZipUri;",
"Invoke-RestMethod -OutFile $md5File -Uri $agentZipMD5Uri;",
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"$expectedMD5 = (Get-Content $md5File);",
"$md5 = New-Object -TypeName
System.Security.Cryptography.MD5CryptoServiceProvider;",
"$actualMD5 =
[System.BitConverter]::ToString($md5.ComputeHash([System.IO.File]::ReadAllBytes($zipFile))).replace(\"-
\", \"\");",
"if($expectedMD5 -ne $actualMD5) {",
"echo \"Download does not match hash.\";",
"echo \"Expected: $expectedMD5 - Got: $actualMD5\";",
"exit 1;",
"};",
"Expand-Archive -Path $zipFile -DestinationPath $ecsExeDir -Force;",
"$jobname = \"ECS-Agent-Init\";",
"$script = \"cd '$ecsExeDir'; .\\amazon-ecs-agent.ps1\";",
"$repeat = (New-TimeSpan -Minutes 1);",
"try {",
"Unregister-ScheduledJob -Name $jobname | out-null",
"}",
"catch{};",
"Invoke-Expression(\"cd $ecsExeDir; .\\amazon-ecs-agent.ps1\");",
"$scriptblock = [scriptblock]::Create(\"$script\");",
"$trigger = New-JobTrigger -At (Get-Date).Date -RepeatIndefinitely -
RepetitionInterval $repeat -Once;",
"$options = New-ScheduledJobOption -RunElevated -ContinueIfGoingOnBattery -
StartIfOnBattery;",
"Register-ScheduledJob -Name $jobname -ScriptBlock $scriptblock -Trigger
$trigger -ScheduledJobOption $options -RunNow;",
"echo $scriptblock >> c:\\windows\\temp\\log1.txt;",
"echo $trigger >> c:\\windows\\temp\\log1.txt;",
"echo $options >> c:\\windows\\temp\\log1.txt;",
"# end of script\n",
" cfn-init.exe -v -s ",
{
"Ref": "AWS::StackId"
},
" -r ContainerInstances",
" --region ",
{
"Ref": "AWS::Region"
},
"\n",
" cfn-signal.exe -e $lastexitcode --stack ",
{
"Ref": "AWS::StackName"
},
" --resource ECSAutoScalingGroup ",
" --region ",
{
"Ref": "AWS::Region"
},
"; \n",
" </powershell>\n",
"<persist>true</persist>"
]
]
}
}
}
},
"service": {
"Type": "AWS::ECS::Service",
"DependsOn": "ALBListener",
"Properties": {
"Cluster": {
"Ref": "ECSCluster"
},
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"DesiredCount": "1",
"LoadBalancers": [
{
"ContainerName": "windows_sample_app",
"ContainerPort": "80",
"TargetGroupArn": {
"Ref": "ECSTargetGroup"
}
}
],
"Role": {
"Ref": "ECSServiceRole"
},
"TaskDefinition": {
"Ref": "taskdefinition"
}
}
},
"ECSServiceRole": {
"Type": "AWS::IAM::Role",
"Properties": {
"AssumeRolePolicyDocument": {
"Statement": [
{
"Effect": "Allow",
"Principal": {
"Service": [
"ecs.amazonaws.com"
]
},
"Action": [
"sts:AssumeRole"
]
}
]
},
"Path": "/",
"Policies": [
{
"PolicyName": "ecs-service",
"PolicyDocument": {
"Statement": [
{
"Effect": "Allow",
"Action": [
"elasticloadbalancing:DeregisterInstancesFromLoadBalancer",
"elasticloadbalancing:DeregisterTargets",
"elasticloadbalancing:Describe*",
"elasticloadbalancing:RegisterInstancesWithLoadBalancer",
"elasticloadbalancing:RegisterTargets",
"ec2:Describe*",
"ec2:AuthorizeSecurityGroupIngress"
],
"Resource": "*"
}
]
}
}
]
}
},
"ServiceScalingTarget": {
"Type": "AWS::ApplicationAutoScaling::ScalableTarget",
"DependsOn": "service",
"Properties": {
"MaxCapacity": 2,
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"MinCapacity": 1,
"ResourceId": {
"Fn::Join": [
"",
[
"service/",
{
"Ref": "ECSCluster"
},
"/",
{
"Fn::GetAtt": [
"service",
"Name"
]
}
]
]
},
"RoleARN": {
"Fn::GetAtt": [
"AutoscalingRole",
"Arn"
]
},
"ScalableDimension": "ecs:service:DesiredCount",
"ServiceNamespace": "ecs"
}
},
"ServiceScalingPolicy": {
"Type": "AWS::ApplicationAutoScaling::ScalingPolicy",
"Properties": {
"PolicyName": "AStepPolicy",
"PolicyType": "StepScaling",
"ScalingTargetId": {
"Ref": "ServiceScalingTarget"
},
"StepScalingPolicyConfiguration": {
"AdjustmentType": "PercentChangeInCapacity",
"Cooldown": 60,
"MetricAggregationType": "Average",
"StepAdjustments": [
{
"MetricIntervalLowerBound": 0,
"ScalingAdjustment": 200
}
]
}
}
},
"ALB500sAlarmScaleUp": {
"Type": "AWS::CloudWatch::Alarm",
"Properties": {
"EvaluationPeriods": "1",
"Statistic": "Average",
"Threshold": "10",
"AlarmDescription": "Alarm if our ALB generates too many HTTP 500s.",
"Period": "60",
"AlarmActions": [
{
"Ref": "ServiceScalingPolicy"
}
],
"Namespace": "AWS/ApplicationELB",
"Dimensions": [
{
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"Name": "ECSService",
"Value": {
"Ref": "service"
}
}
],
"ComparisonOperator": "GreaterThanThreshold",
"MetricName": "HTTPCode_ELB_5XX_Count"
}
},
"EC2Role": {
"Type": "AWS::IAM::Role",
"Properties": {
"AssumeRolePolicyDocument": {
"Statement": [
{
"Effect": "Allow",
"Principal": {
"Service": [
"ec2.amazonaws.com"
]
},
"Action": [
"sts:AssumeRole"
]
}
]
},
"Path": "/",
"Policies": [
{
"PolicyName": "ecs-service",
"PolicyDocument": {
"Statement": [
{
"Effect": "Allow",
"Action": [
"ecs:CreateCluster",
"ecs:DeregisterContainerInstance",
"ecs:DiscoverPollEndpoint",
"ecs:Poll",
"ecs:RegisterContainerInstance",
"ecs:StartTelemetrySession",
"ecs:Submit*",
"logs:CreateLogStream",
"logs:PutLogEvents"
],
"Resource": "*"
}
]
}
}
]
}
},
"AutoscalingRole": {
"Type": "AWS::IAM::Role",
"Properties": {
"AssumeRolePolicyDocument": {
"Statement": [
{
"Effect": "Allow",
"Principal": {
"Service": [
"application-autoscaling.amazonaws.com"
]
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},
"Action": [
"sts:AssumeRole"
]
}
]
},
"Path": "/",
"Policies": [
{
"PolicyName": "service-autoscaling",
"PolicyDocument": {
"Statement": [
{
"Effect": "Allow",
"Action": [
"application-autoscaling:*",
"cloudwatch:DescribeAlarms",
"cloudwatch:PutMetricAlarm",
"ecs:DescribeServices",
"ecs:UpdateService"
],
"Resource": "*"
}
]
}
}
]
}
},
"EC2InstanceProfile": {
"Type": "AWS::IAM::InstanceProfile",
"Properties": {
"Path": "/",
"Roles": [
{
"Ref": "EC2Role"
}
]
}
}
},
"Outputs": {
"ecsservice": {
"Value": {
"Ref": "service"
}
},
"ecscluster": {
"Value": {
"Ref": "ECSCluster"
}
},
"ECSALB": {
"Description": "Your ALB DNS URL",
"Value": {
"Fn::Join": [
"",
[
{
"Fn::GetAtt": [
"ECSALB",
"DNSName"
]
}
]
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]
}
},
"taskdef": {
"Value": {
"Ref": "taskdefinition"
}
}
}
}
Getting Started with Windows Containers
This tutorial walks you through manually getting Windows containers running on Amazon ECS. You
create a cluster for your Windows container instances, launch one or more container instances into your
cluster, register a task definition that uses a Windows container image, create a service that uses that
task definition, and then view the sample webpage that the container runs.
If you would rather have your cluster set up automatically with a provided AWS CloudFormation
template, see Windows Containers AWS CloudFormation Template (p. 289).
Topics
•Step 1: Create a Windows Cluster (p. 302)
•Step 2: Launching a Windows Container Instance into your Cluster (p. 302)
•Step 3: Register a Windows Task Definition (p. 305)
•Step 4: Create a Service with Your Task Definition (p. 307)
•Step 5: View Your Service (p. 307)
Step 1: Create a Windows Cluster
You should create a new cluster for your Windows containers. Linux container instances cannot run
Windows containers, and vice versa, so proper task placement is best accomplished by running Windows
and Linux container instances in separate clusters. In this tutorial, you create a cluster called windows for
your Windows containers.
You can create a cluster with the AWS Management Console. For more information, see Creating a
Cluster (p. 27).
You can also create a cluster using the AWS CLI with the following command:
$ aws ecs create-cluster --cluster-name windows
Step 2: Launching a Windows Container Instance into
your Cluster
You can launch Windows container instance using the AWS Management Console, as described in this
topic. Before you begin, be sure that you've completed the steps in Setting Up with Amazon ECS (p. 8).
After you've launched your instance, you can use it to run tasks.
To launch a Windows container instance
1. Open the Amazon EC2 console at https://console.aws.amazon.com/ec2/.
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Step 2: Launching a Windows
Container Instance into your Cluster
2. From the navigation bar, select the region to use.
Note
Amazon ECS is available in the following regions:
Region Name Region
US East (N. Virginia) us-east-1
US East (Ohio) us-east-2
US West (N.
California)
us-west-1
US West (Oregon) us-west-2
EU (Ireland) eu-west-1
EU (London) eu-west-2
EU (Frankfurt) eu-central-1
Asia Pacific (Tokyo) ap-northeast-1
Asia Pacific
(Singapore)
ap-southeast-1
Asia Pacific (Sydney) ap-southeast-2
Canada (Central) ca-central-1
3. From the console dashboard, choose Launch Instance.
4. On the Choose an Amazon Machine Image (AMI) page, choose Quick Start.
5. Choose the Microsoft Windows Server 2016 Base with Containers AMI for your container instance.
6. On the Choose an Instance Type page, you can select the hardware configuration of your instance.
The t2.micro instance type is selected by default. The instance type that you select determines the
resources available for your tasks to run on.
7. Choose Next: Configure Instance Details.
8. On the Configure Instance Details page, set the Auto-assign Public IP check box depending on
whether to make your instance accessible from the public Internet. If your instance should be
accessible from the Internet, verify that the Auto-assign Public IP field is set to Enable. If your
instance should not be accessible from the Internet, choose Disable.
Note
Container instances need external network access to communicate with the Amazon ECS
service endpoint, so if your container instances do not have public IP addresses, then they
must use network address translation (NAT) to provide this access. For more information,
see NAT Instances in the Amazon VPC User Guide.
9. On the Configure Instance Details page, select the ecsInstanceRole IAM role value that you
created for your container instances in Setting Up with Amazon ECS (p. 8).
Important
If you do not launch your container instance with the proper IAM permissions, your
Amazon ECS agent will not connect to your cluster. For more information, see Amazon ECS
Container Instance IAM Role (p. 210).
10. Configure your Windows container instance with the provided user data PowerShell script. By
default, this script registers your container instance into the windows cluster that you created
earlier. To launch into another cluster instead of windows, replace that value of the ECS_CLUSTER
environment variable in the script below with the name of your cluster.
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Container Instance into your Cluster
Note
To use the IAM roles for tasks feature with your Windows containers, replace the value of
the ECS_ENABLE_TASK_IAM_ROLE environment variable in the script below with true. For
more information, see Windows IAM Roles for Tasks (p. 311).
<powershell>
## The string 'windows' should be replaced with your cluster name
# Set agent env variables for the Machine context (durable)
[Environment]::SetEnvironmentVariable("ECS_CLUSTER", "windows", "Machine")
[Environment]::SetEnvironmentVariable("ECS_ENABLE_TASK_IAM_ROLE", "false", "Machine")
$agentVersion = 'v1.14.0-1.windows.1'
$agentZipUri = "https://s3.amazonaws.com/amazon-ecs-agent/ecs-agent-windows-
$agentVersion.zip"
$agentZipMD5Uri = "$agentZipUri.md5"
### --- Nothing user configurable after this point ---
$ecsExeDir = "$env:ProgramFiles\Amazon\ECS"
$zipFile = "$env:TEMP\ecs-agent.zip"
$md5File = "$env:TEMP\ecs-agent.zip.md5"
### Get the files from S3
Invoke-RestMethod -OutFile $zipFile -Uri $agentZipUri
Invoke-RestMethod -OutFile $md5File -Uri $agentZipMD5Uri
## MD5 Checksum
$expectedMD5 = (Get-Content $md5File)
$md5 = New-Object -TypeName System.Security.Cryptography.MD5CryptoServiceProvider
$actualMD5 =
[System.BitConverter]::ToString($md5.ComputeHash([System.IO.File]::ReadAllBytes($zipFile))).replace('-',
'')
if($expectedMD5 -ne $actualMD5) {
echo "Download doesn't match hash."
echo "Expected: $expectedMD5 - Got: $actualMD5"
exit 1
}
## Put the executables in the executable directory.
Expand-Archive -Path $zipFile -DestinationPath $ecsExeDir -Force
## Start the agent script in the background.
$jobname = "ECS-Agent-Init"
$script = "cd '$ecsExeDir'; .\amazon-ecs-agent.ps1"
$repeat = (New-TimeSpan -Minutes 1)
$jobpath = $env:LOCALAPPDATA + "\Microsoft\Windows\PowerShell\ScheduledJobs\$jobname
\ScheduledJobDefinition.xml"
if($(Test-Path -Path $jobpath)) {
echo "Job definition already present"
exit 0
}
$scriptblock = [scriptblock]::Create("$script")
$trigger = New-JobTrigger -At (Get-Date).Date -RepeatIndefinitely -RepetitionInterval
$repeat -Once
$options = New-ScheduledJobOption -RunElevated -ContinueIfGoingOnBattery -
StartIfOnBattery
Register-ScheduledJob -Name $jobname -ScriptBlock $scriptblock -Trigger $trigger -
ScheduledJobOption $options -RunNow
Add-JobTrigger -Name $jobname -Trigger (New-JobTrigger -AtStartup -RandomDelay 00:1:00)
</powershell>
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<persist>true</persist>
11. Choose Next: Add Storage.
12. On the Add Storage page, configure the storage for your container instance. The Windows OS and
container images are quite large (approximately 9 GiB for the Windows server core base layers),
and just a few images and containers quickly fill up the default 30 GiB volume size that the launch
wizard uses. A larger root volume size (for example, 200 GiB) allows for more containers and images
on your instance.
You can optionally increase or decrease the volume size for your instance to meet your application
needs.
13. Choose Review and Launch.
14. On the Review Instance Launch page, under Security Groups, you'll see that the wizard created and
selected a security group for you. By default, you should have port 3389 for RDP connectivity. If you
want your containers to receive inbound traffic from the Internet, you need to open those ports as
well.
a. Choose Edit security groups.
b. On the Configure Security Group page, ensure that the Create a new security group option is
selected.
c. Add rules for any other ports that your containers may need (the sample task definition later in
this walk through uses port 8000, so you should open that to Anywhere), and choose Review
and Launch.
15. On the Review Instance Launch page, choose Launch.
16. In the Select an existing key pair or create a new key pair dialog box, choose Choose an existing
key pair, then select the key pair that you created when getting set up.
When you are ready, select the acknowledgment field, and then choose Launch Instances.
17. A confirmation page lets you know that your instance is launching. Choose View Instances to close
the confirmation page and return to the console.
18. On the Instances screen, you can view the status of your instance. It takes a short time for an
instance to launch. When you launch an instance, its initial state is pending. After the instance starts,
its state changes to running, and it receives a public DNS name. (If the Public DNS column is hidden,
choose the Show/Hide icon and choose Public DNS.)
19. After your instance has launched, you can view your cluster in the Amazon ECS console to see that
your container instance has registered with it.
Note
It can take up to 15 minutes for your Windows instance to register with your cluster.
Step 3: Register a Windows Task Definition
Before you can run Windows containers in your Amazon ECS cluster, you must register a task definition.
The following task definition example displays a simple webpage on port 80 of a container instance with
the microsoft/iis container image.
{
"family": "windows-simple-iis",
"containerDefinitions": [
{
"name": "windows_sample_app",
"image": "microsoft/iis",
"cpu": 100,
"entryPoint":["powershell", "-Command"],
"command":["New-Item -Path C:\\inetpub\\wwwroot\\index.html -Type file -Value '<html>
<head> <title>Amazon ECS Sample App</title> <style>body {margin-top: 40px; background-
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color: #333;} </style> </head><body> <div style=color:white;text-align:center> <h1>Amazon
ECS Sample App</h1> <h2>Congratulations!</h2> <p>Your application is now running on a
container in Amazon ECS.</p>'; C:\\ServiceMonitor.exe w3svc"],
"portMappings": [
{
"protocol": "tcp",
"containerPort": 80,
"hostPort": 80
}
],
"memory": 500,
"essential": true
}
]
}
To register the sample task definition
1. Create a file called windows-simple-iis.json.
2. Open the file with your favorite text editor and add the sample JSON above to the file and save it.
3. Using the AWS CLI, run the following command to register the task definition with Amazon ECS.
Note
Make sure that your AWS CLI is configured to use the same region that your Windows
cluster exists in, or add the --region your_cluster_region option to your command.
$ aws ecs register-task-definition --cli-input-json file://windows-simple-iis.json
{
"taskDefinition": {
"status": "ACTIVE",
"family": "windows-simple-iis",
"volumes": [],
"taskDefinitionArn": "arn:aws:ecs:us-east-1:130757420319:task-definition/
windows-simple-iis:1",
"containerDefinitions": [
{
"environment": [],
"name": "windows_sample_app",
"mountPoints": [],
"image": "microsoft/iis",
"cpu": 100,
"portMappings": [
{
"protocol": "tcp",
"containerPort": 80,
"hostPort": 80
}
],
"entryPoint": [
"powershell",
"-Command"
],
"memory": 500,
"command": [
"New-Item -Path C:\\inetpub\\wwwroot\\index.html -Type file -
Value '<html> <head> <title>Amazon ECS Sample App</title> <style>body {margin-top:
40px; background-color: #333;} </style> </head><body> <div style=color:white;text-
align:center> <h1>Amazon ECS Sample App</h1> <h2>Congratulations!</h2> <p>Your
application is now running on a container in Amazon ECS.</p>'; C:\\ServiceMonitor.exe
w3svc"
],
"essential": true,
"volumesFrom": []
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}
],
"revision": 1
}
}
Step 4: Create a Service with Your Task Definition
After you have registered your task definition, you can place tasks in your cluster with it. The following
procedure creates a service with your task definition and places one task on your cluster.
To create a service with your task definition
• Using the AWS CLI, run the following command to create your service.
$ aws ecs create-service --cluster windows --task-definition windows-simple-iis --
desired-count 1 --service-name windows-simple-iis
{
"service": {
"status": "ACTIVE",
"taskDefinition": "arn:aws:ecs:us-east-1:130757420319:task-definition/windows-
simple-iis:1",
"pendingCount": 0,
"loadBalancers": [],
"createdAt": 1479849211.046,
"desiredCount": 1,
"serviceName": "windows-simple-iis",
"clusterArn": "arn:aws:ecs:us-east-1:130757420319:cluster/windows",
"serviceArn": "arn:aws:ecs:us-east-1:130757420319:service/windows-simple-iis",
"deploymentConfiguration": {
"maximumPercent": 200,
"minimumHealthyPercent": 100
},
"deployments": [
{
"status": "PRIMARY",
"pendingCount": 0,
"createdAt": 1479849211.046,
"desiredCount": 1,
"taskDefinition": "arn:aws:ecs:us-east-1:130757420319:task-definition/
windows-simple-iis:1",
"updatedAt": 1479849211.046,
"id": "ecs-svc/9223370557005564761",
"runningCount": 0
}
],
"events": [],
"runningCount": 0
}
}
Step 5: View Your Service
After your service has launched a task into your cluster, you can view the service and open the IIS test
page in a browser to verify that the container is running.
Note
It can take up to 15 minutes for your container instance to download and extract the Windows
container base layers.
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Windows Task Definitions
To view your service
1. Open the Amazon ECS console at https://console.aws.amazon.com/ecs/.
2. On the Clusters page, choose the windows cluster.
3. In the Services tab, choose the windows-simple-iis service.
4. On the Service: windows-simple-iis page, choose the task ID for the task in your service.
5. On the Task page, expand the iis container to view its information.
6. In the Network bindings of the container, you should see an External Link IP address and port
combination link. Choose that link to open the IIS test page in your browser.
Windows Task Definitions
Windows containers and container instances cannot support all the task definition parameters that are
available for Linux containers and container instances. For some parameters, they are not supported at
all, and others behave differently on Windows than they do on Linux.
Windows Task Definition Parameters
The following matrix explains which parameters are supported, not supported, or behave differently on
Windows containers. For more information about these parameters as they relate to Amazon ECS, see
Task Definition Parameters (p. 98).
family
Supported: Yes
taskRoleArn
Supported: Yes
Additional notes: IAM roles for tasks on Windows require that you set the
ECS_ENABLE_TASK_IAM_ROLE environment variable to true when you launch your container instances.
Your containers must also run some configuration code in order to take advantage of the feature.
For more information, see Windows IAM Roles for Tasks (p. 311).
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Windows Task Definition Parameters
networkMode
Supported: No
Additional notes: Docker for Windows uses different network modes than Docker for Linux. When
you register a task definition with Windows containers, you must not specify a network mode. If you
use the console to register a task definition with Windows containers, you must use the JSON input
form and remove the network mode object; otherwise, the network mode is registered as bridge,
which fails.
containerDefinitions
Supported: Yes
Additional notes: Not all container definition parameters are supported. Review the list below for
individual parameter support.
name
Supported: Yes
image
Supported: Yes
memory
Supported: Unknown behavior on Windows side
Additional notes: The memory parameter is a required in Amazon ECS task definitions; however,
there is no published documentation from Microsoft as to how this parameter behaves on the
container instance. Amazon ECS treats this parameter in the same manner that it does for Linux
container instances: if you provide 500 MiB to a container, that amount of memory is removed
from the available resources on the container instance when the task is placed).
memoryReservation
Supported: No
portMappings
Supported: Limited
Additional notes: Port mappings on Windows use the NetNAT gateway address rather than
localhost. There is no loopback for port mappings on Windows, so you cannot access a
container's mapped port from the host itself.
cpu
Supported: Unknown behavior on Windows side
Additional notes: There is no published documentation from Microsoft as to how this parameter
behaves on the container instance. Amazon ECS treats this parameter in the same manner that
it does for Linux container instances: if you provide 500 CPU shares to a container, that number
of CPU shares is removed from the available resources on the container instance when the task
is placed.
essential
Supported: Yes
entryPoint
Supported: Yes
command
Supported: Yes
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workingDirectory
Supported: Yes
environment
Supported: Yes
disableNetworking
Supported: No
links
Supported: No
hostname
Supported: Yes
dnsServers
Supported: No
dnsSearchDomains
Supported: No
extraHosts
Supported: No
readonlyRootFilesystem
Supported: No
mountPoints
Supported: Limited
Additional notes: Containers can mount whole directories on the same drive as
$env:ProgramData. Containers cannot mount directories on a different drive, and mount point
cannot be across drives.
volumesFrom
Supported: Yes
logConfiguration
Supported: Yes
Additional notes: The list of available log drivers for Docker can be found at Configure logging
drivers in the Docker documentation. Amazon ECS currently supports a subset of the logging
drivers available to the Docker daemon (shown in the valid values at logDriver (p. 108)); we
have tested the awslogs and json-file log drivers with Windows containers on Amazon ECS.
Additional log drivers may be available in future releases of the Amazon ECS container agent.
privileged
Supported: No
user
Supported: No
dockerLabels
Supported: Yes
volumes
Supported: Yes
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name
Supported: Yes
host
Supported: Limited
Additional notes: Containers can mount whole directories on the same drive as
$env:ProgramData. Containers cannot mount directories on a different drive, and mount point
cannot be across drives. For example, you can mount C:\my\path:C:\my\path and D:\:D:\, but
not D:\my\path:C:\my\path or D:\:C:\my\path.
Windows Sample Task Definitions
Below is a sample task definition that can help you get started with Windows containers on Amazon ECS.
Example Amazon ECS Console Sample Application for Windows
The following task definition is the Amazon ECS console sample application that is produced in the first-
run wizard for Amazon ECS; it has been ported to use the microsoft/iis Windows container image.
{
"family": "windows-simple-iis",
"containerDefinitions": [
{
"name": "windows_sample_app",
"image": "microsoft/iis",
"cpu": 100,
"entryPoint":["powershell", "-Command"],
"command":["New-Item -Path C:\\inetpub\\wwwroot\\index.html -Type file -Value '<html>
<head> <title>Amazon ECS Sample App</title> <style>body {margin-top: 40px; background-
color: #333;} </style> </head><body> <div style=color:white;text-align:center> <h1>Amazon
ECS Sample App</h1> <h2>Congratulations!</h2> <p>Your application is now running on a
container in Amazon ECS.</p>'; C:\\ServiceMonitor.exe w3svc"],
"portMappings": [
{
"protocol": "tcp",
"containerPort": 80,
"hostPort": 80
}
],
"memory": 500,
"essential": true
}
]
}
Windows IAM Roles for Tasks
IAM roles for tasks with Windows requires extra configuration, but much of this configuration is similar
to enabling IAM roles for tasks on Linux container instances. The following requirements must be met to
enable IAM roles for tasks for Windows containers.
• When you launch your container instances, you must enable the feature by setting the
ECS_ENABLE_TASK_IAM_ROLE environment variable in the container instances startup script.
• You must bootstrap your container with the networking commands that are provided in IAM Roles for
Task Container Bootstrap Script (p. 312).
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• You must create an IAM role and policy for your tasks. For more information, see Creating an IAM Role
and Policy for your Tasks (p. 218).
• Your container must use an AWS SDK that supports IAM roles for tasks. For more information, see
Using a Supported AWS SDK (p. 219).
• You must specify the IAM role you created for your tasks when you register the task definition, or
as an override when you run the task. For more information, see Specifying an IAM Role for your
Tasks (p. 219).
• The IAM roles for the task credential provider use port 80 on the container instance, so if you enable
IAM roles for tasks on your container instance, your containers cannot use port 80 for the host port
in any port mappings. To expose your containers on port 80, we recommend configuring a service
for them that uses load balancing. You can use port 80 on the load balancer, and the traffic can be
routed to another host port on your container instances. For more information, see Service Load
Balancing (p. 141).
IAM Roles for Task Container Bootstrap Script
Before containers can access the credential proxy on the container instance to get credentials, the
container must be bootstrapped with the required networking commands. The following code example
script should be run on your containers when they start.
# Copyright 2014-2016 Amazon.com, Inc. or its affiliates. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"). You may
# not use this file except in compliance with the License. A copy of the
# License is located at
#
# http://aws.amazon.com/apache2.0/
#
# or in the "license" file accompanying this file. This file is distributed
# on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either
# express or implied. See the License for the specific language governing
# permissions and limitations under the License.
$gateway = (Get-WMIObject -Class Win32_IP4RouteTable | Where { $_.Destination -eq '0.0.0.0'
-and $_.Mask -eq '0.0.0.0' } | Sort-Object Metric1 | Select NextHop).NextHop
$ifIndex = (Get-NetAdapter -InterfaceDescription "Hyper-V Virtual Ethernet*" | Sort-Object
| Select ifIndex).ifIndex
New-NetRoute -DestinationPrefix 169.254.170.2/32 -InterfaceIndex $ifIndex -NextHop $gateway
Pushing Windows Images to Amazon ECR
You can push Windows Docker container images to Amazon ECR. You must be using a version of
Docker that supports Windows containers. The following procedures show you how to pull a Windows
Docker image, create an Amazon ECR repository to store the image, tag the image to that repository,
authenticate the image to the Amazon ECR registry, and then push the image to that repository.
To pull and tag a Windows Docker image
1. Pull a Windows Docker image locally. This example uses the microsoft/iis image.
PS C:\> docker pull microsoft/iis
Using default tag: latest
latest: Pulling from microsoft/iis
3889bb8d808b: Pull complete
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04ee5d718c7a: Pull complete
c0931dd15237: Pull complete
61784b745c20: Pull complete
d05122f129ca: Pull complete
Digest: sha256:25586570b058da9882d4af640d326d0cc26dfd60b67e1cee63f35ea54d83c882
Status: Downloaded newer image for microsoft/iis:latest
2. Create an Amazon ECR repository for your image.
PS C:\> aws ecr create-repository --repository-name iis
{
"repository": {
"registryId": "111122223333",
"repositoryName": "iis",
"repositoryArn": "arn:aws:ecr:us-west-2:111122223333:repository/iis",
"createdAt": 1481845593.0,
"repositoryUri": "111122223333.dkr.ecr.us-west-2.amazonaws.com/iis"
}
}
3. Tag the image with the repositoryUri that was returned from the previous command.
PS C:\> docker tag microsoft/iis 111122223333.dkr.ecr.us-west-2.amazonaws.com/iis
4. Authenticate your Docker client to the Amazon ECR registry.
PS C:\> Invoke-Expression -Command (aws ecr get-login)
5. Push the image to Amazon ECR.
PS C:\> docker push 111122223333.dkr.ecr.us-west-2.amazonaws.com/iis
The push refers to a repository [111122223333.dkr.ecr.us-west-2.amazonaws.com/iis]
1e4f77a75bd4: Pushed
ac90fb7da567: Pushed
c7090349c7b3: Pushed
b9454c3094c6: Skipped foreign layer
3fd27ecef6a3: Skipped foreign layer
latest: digest: sha256:0ddc7af8691072bb2dd8b3f189388b33604c90774d3dc0485b1bf379f9bec4c5
size: 1574
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AWS Glossary
For the latest AWS terminology, see the AWS Glossary in the AWS General Reference.
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