Performance Co Pilot™ User's And Administrator's Guide PCP 3 Users Administrators En US

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Performance Co-Pilot™ User's
and Administrator's Guide

Performance Co-Pilot™ User's and Administrator's Guide
Maintained by:
The Performance Co-Pilot Development Team

http://pcp.io

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TRADEMARKS AND ATTRIBUTIONS
Silicon Graphics, SGI and the SGI logo are registered trademarks and Performance Co-Pilot is a trademark of Silicon Graphics, Inc.
Red Hat and the Shadowman logo are trademarks of Red Hat, Inc., registered in the United States and other countries.
Cisco is a trademark of Cisco Systems, Inc. Linux is a registered trademark of Linus Torvalds, used with permission. UNIX is a registered trademark
of The Open Group.

Table of Contents
About This Guide .............................................................................................................. ix
What This Guide Contains .......................................................................................... ix
Audience for This Guide .............................................................................................. x
Related Resources ....................................................................................................... x
Man Pages ................................................................................................................. x
Web Site ................................................................................................................... x
Conventions .............................................................................................................. xi
Reader Comments ...................................................................................................... xi
1. Introduction to PCP ......................................................................................................... 1
Objectives .................................................................................................................. 1
PCP Target Usage ............................................................................................... 2
Empowering the PCP User ................................................................................... 2
Unification of Performance Metric Domains ............................................................ 2
Uniform Naming and Access to Performance Metrics ................................................ 2
PCP Distributed Operation ................................................................................... 2
Dynamic Adaptation to Change ............................................................................. 3
Logging and Retrospective Analysis ...................................................................... 3
Automated Operational Support ............................................................................. 3
PCP Extensibility ................................................................................................ 3
Metric Coverage ................................................................................................. 4
Conceptual Foundations ............................................................................................... 4
Performance Metrics ........................................................................................... 4
Performance Metric Instances ............................................................................... 4
Current Metric Context ........................................................................................ 5
Sources of Performance Metrics and Their Domains ................................................. 5
Distributed Collection .......................................................................................... 6
Performance Metrics Name Space ......................................................................... 6
Descriptions for Performance Metrics ..................................................................... 7
Values for Performance Metrics ............................................................................ 7
Collector and Monitor Roles ................................................................................. 8
Retrospective Sources of Performance Metrics ......................................................... 8
Product Extensibility ........................................................................................... 9
Overview of Component Software ................................................................................. 9
Performance Monitoring and Visualization .............................................................. 9
Collecting, Transporting, and Archiving Performance Information ............................. 10
Operational and Infrastructure Support .................................................................. 12
Application and Agent Development .................................................................... 13
2. Installing and Configuring Performance Co-Pilot ................................................................ 14
Product Structure ...................................................................................................... 14
Performance Metrics Collection Daemon (PMCD) .......................................................... 15
Starting and Stopping the PMCD ......................................................................... 15
Restarting an Unresponsive PMCD ...................................................................... 15
PMCD Diagnostics and Error Messages ................................................................ 15
PMCD Options and Configuration Files ................................................................ 16
Managing Optional PMDAs ........................................................................................ 20
PMDA Installation on a PCP Collector Host .......................................................... 21
PMDA Removal on a PCP Collector Host ............................................................. 22
Troubleshooting ........................................................................................................ 23
Performance Metrics Name Space ........................................................................ 23
Missing and Incomplete Values for Performance Metrics ......................................... 23
Kernel Metrics and the PMCD ............................................................................ 23

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Performance Co-Pilot™ User's
and Administrator's Guide
3. Common Conventions and Arguments ..............................................................................
Alternate Metrics Source Options ................................................................................
Fetching Metrics from Another Host ....................................................................
Fetching Metrics from an Archive Log .................................................................
General PCP Tool Options .........................................................................................
Common Directories and File Locations ................................................................
Alternate Performance Metric Name Spaces ..........................................................
Time Duration and Control .........................................................................................
Performance Monitor Reporting Frequency and Duration .........................................
Time Window Options .......................................................................................
Timezone Options .............................................................................................
PCP Environment Variables ........................................................................................
Running PCP Tools through a Firewall .........................................................................
The pmproxy service ........................................................................................
Transient Problems with Performance Metric Values .......................................................
Performance Metric Wraparound .........................................................................
Time Dilation and Time Skew ............................................................................
4. Monitoring System Performance ......................................................................................
The pmstat Command ...............................................................................................
The pmrep Command ...............................................................................................
The pmval Command ................................................................................................
The pminfo Command ...............................................................................................
The pmstore Command .............................................................................................
5. Performance Metrics Inference Engine ..............................................................................
Introduction to pmie ..................................................................................................
Basic pmie Usage .....................................................................................................
pmie use of PCP services ...................................................................................
Simple pmie Usage ...........................................................................................
Complex pmie Examples ...................................................................................
Specification Language for pmie .................................................................................
Basic pmie Syntax ............................................................................................
Setting Evaluation Frequency ..............................................................................
pmie Metric Expressions ....................................................................................
pmie Rate Conversion .......................................................................................
pmie Arithmetic Expressions ..............................................................................
pmie Logical Expressions ...................................................................................
pmie Rule Expressions ......................................................................................
pmie Intrinsic Operators .....................................................................................
pmie Examples .........................................................................................................
Developing and Debugging pmie Rules ........................................................................
Caveats and Notes on pmie ........................................................................................
Performance Metrics Wraparound ........................................................................
pmie Sample Intervals .......................................................................................
pmie Instance Names ........................................................................................
pmie Error Detection .........................................................................................
Creating pmie Rules with pmieconf .............................................................................
Management of pmie Processes ...................................................................................
Add a pmie crontab Entry .................................................................................
Global Files and Directories ................................................................................
pmie Instances and Their Progress .......................................................................
6. Archive Logging ...........................................................................................................
Introduction to Archive Logging ..................................................................................
Archive Logs and the PMAPI .............................................................................
Retrospective Analysis Using Archive Logs ...........................................................

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Using Archive Logs for Capacity Planning ............................................................ 72
Using Archive Logs with Performance Tools ................................................................. 72
Coordination between pmlogger and PCP tools ...................................................... 72
Administering PCP Archive Logs Using cron Scripts .............................................. 72
Archive Log File Management ............................................................................ 73
Cookbook for Archive Logging ................................................................................... 75
Primary Logger ................................................................................................. 76
Other Logger Configurations ............................................................................... 77
Archive Log Administration ................................................................................ 78
Other Archive Logging Features and Services ................................................................ 79
PCP Archive Folios ........................................................................................... 79
Manipulating Archive Logs with pmlogextract ...................................................... 79
Summarizing Archive Logs with pmlogsummary .................................................. 79
Primary Logger ................................................................................................. 80
Using pmlc ...................................................................................................... 80
Archive Logging Troubleshooting ................................................................................ 81
pmlogger Cannot Write Log ............................................................................... 81
Cannot Find Log ............................................................................................... 82
Primary pmlogger Cannot Start ........................................................................... 82
Identifying an Active pmlogger Process ............................................................... 83
Illegal Label Record .......................................................................................... 83
Empty Archive Log Files or pmlogger Exits Immediately ........................................ 84
7. Performance Co-Pilot Deployment Strategies ..................................................................... 85
Basic Deployment ..................................................................................................... 86
PCP Collector Deployment ......................................................................................... 86
Principal Server Deployment ............................................................................... 86
Quality of Service Measurement .......................................................................... 87
PCP Archive Logger Deployment ................................................................................ 87
Deployment Options .......................................................................................... 88
Resource Demands for the Deployment Options ..................................................... 88
Operational Management .................................................................................... 88
Exporting PCP Archive Logs .............................................................................. 88
PCP Inference Engine Deployment .............................................................................. 89
Deployment Options .......................................................................................... 89
Resource Demands for the Deployment Options ..................................................... 89
Operational Management .................................................................................... 90
8. Customizing and Extending PCP Services .......................................................................... 91
PMDA Customization ................................................................................................ 91
Customizing the Summary PMDA ....................................................................... 91
PCP Tool Customization ............................................................................................ 94
Archive Logging Customization .......................................................................... 94
Inference Engine Customization .......................................................................... 95
PMNS Management ................................................................................................... 96
PMNS Processing Framework ............................................................................. 97
PMNS Syntax ................................................................................................... 97
PMDA Development ................................................................................................. 98
PCP Tool Development .............................................................................................. 98
A. Acronyms .................................................................................................................. 100
Index ............................................................................................................................. 101

List of Figures
1.1. Performance Metric Domains as Autonomous Collections of Data ......................................... 5
1.2. Process Structure for Distributed Operation ....................................................................... 6
1.3. Small Performance Metrics Name Space (PMNS) .............................................................. 6
1.4. Architecture for Retrospective Analysis ............................................................................ 8
5.1. Sampling Time Line .................................................................................................... 53
5.2. Three-Dimensional Parameter Space ............................................................................... 53
6.1. Archive Log Directory Structure .................................................................................... 74
7.1. PCP Deployment for a Single System ............................................................................. 86
7.2. Basic PCP Deployment for Two Systems ........................................................................ 86
7.3. General PCP Deployment for Multiple Systems ................................................................ 86
7.4. PCP Deployment to Measure Client-Server Quality of Service ............................................ 87
7.5. Designated PCP Archive Site ........................................................................................ 88
7.6. PCP Management Site Deployment ................................................................................ 89
8.1. Small Performance Metrics Name Space (PMNS) ............................................................. 97

List of Tables
1.1. Sample Instance Identifiers for Disk Statistics .................................................................... 8
3.1. Physical Filenames for Components of a PCP Archive Log ................................................ 27
6.1. Filenames for PCP Archive Log Components (archive.*) ............................................... 73
A.1. Performance Co-Pilot Acronyms and Their Meanings ..................................................... 100

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List of Examples
2.1. PMNS Installation Output ............................................................................................
5.1. pmie with the -f Option .............................................................................................
5.2. pmie with the -d and -h Options .................................................................................
5.3. pmie with the -v Option .............................................................................................
5.4. Printed pmie Output ....................................................................................................
5.5. Labelled pmie Output ..................................................................................................
5.6. Relational Expressions .................................................................................................
5.7. Rule Expression Options ..............................................................................................
5.8. System Log Text ........................................................................................................
5.9. Standard Output ..........................................................................................................
5.10. Monitoring CPU Utilization ........................................................................................
5.11. Monitoring Disk Activity ............................................................................................
6.1. Using pminfo to Obtain Archive Information .................................................................
6.2. Using pmlogsummary to Summarize Archive Information ...............................................
6.3. Listing Available Commands ........................................................................................
8.1. PMNS Specification ....................................................................................................

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About This Guide
Table of Contents
What This Guide Contains .................................................................................................. ix
Audience for This Guide ...................................................................................................... x
Related Resources ............................................................................................................... x
Man Pages ......................................................................................................................... x
Web Site ........................................................................................................................... x
Conventions ...................................................................................................................... xi
Reader Comments .............................................................................................................. xi
This guide describes the Performance Co-Pilot (PCP) performance analysis toolkit. PCP provides a
systems-level suite of tools that cooperate to deliver distributed performance monitoring and performance
management services spanning hardware platforms, operating systems, service layers, database internals,
user applications and distributed architectures.
PCP is a cross-platform, open source software package - customizations, extensions, source code
inspection, and tinkering in general is actively encouraged.
“About This Guide” includes short descriptions of the chapters in this book, directs you to additional
sources of information, and explains typographical conventions.

What This Guide Contains
This guide contains the following chapters:
• Chapter 1, Introduction to PCP, provides an introduction, a brief overview of the software components,
and conceptual foundations of the PCP software.
• Chapter 2, Installing and Configuring Performance Co-Pilot, describes the basic installation and
configuration steps necessary to get PCP running on your systems.
• Chapter 3, Common Conventions and Arguments, describes the user interface components that are
common to most of the text-based utilities that make up the monitor portion of PCP.
• Chapter 4, Monitoring System Performance, describes the performance monitoring tools available in
Performance Co-Pilot (PCP).
• Chapter 5, Performance Metrics Inference Engine, describes the Performance Metrics Inference Engine
(pmie) tool that provides automated monitoring of, and reasoning about, system performance within
the PCP framework.
• Chapter 6, Archive Logging, covers the PCP services and utilities that support archive logging for
capturing accurate historical performance records.
• Chapter 7, Performance Co-Pilot Deployment Strategies, presents the various options for deploying
PCP functionality across cooperating systems.
• Chapter 8, Customizing and Extending PCP Services, describes the procedures necessary to ensure that
the PCP configuration is customized in ways that maximize the coverage and quality of performance
monitoring and management services.

About This Guide

• Appendix A, Acronyms, provides a comprehensive list of the acronyms used in this guide and in the
man pages for Performance Co-Pilot.

Audience for This Guide
This guide is written for the system administrator or performance analyst who is directly using and
administering PCP applications.

Related Resources
The Performance Co-Pilot Programmer's Guide, a companion document to the Performance Co-Pilot
User's and Administrator's Guide, is intended for developers who want to use the PCP framework and
services for exporting additional collections of performance metrics, or for delivering new or customized
applications to enhance performance management.
The Performance Co-Pilot Tutorials and Case Studies provides a series of real-world examples of using
various PCP tools, and lessons learned from deploying the toolkit in production environments. It serves
to provide reinforcement of the general concepts discussed in the other two books with additional case
studies, and in some cases very detailed discussion of specifics of individual tools.
Additional resources include man pages and the project web site.

Man Pages
The operating system man pages provide concise reference information on the use of commands,
subroutines, and system resources. There is usually a man page for each PCP command or subroutine. To
see a list of all the PCP man pages, start from the following command:
man PCPIntro
Each man page usually has a "SEE ALSO" section, linking to other, related entries.
To see a particular man page, supply its name to the man command, for example:
man pcp
The man pages are arranged in different sections - user commands, programming interfaces, and so on.
For a complete list of manual sections on a platform enter the command:
man man
When referring to man pages, this guide follows a standard convention: the section number in parentheses
follows the item. For example, pminfo(1) refers to the man page in section 1 for the pminfo command.

Web Site
The following web site is accessible to everyone:
URL

Description

http://pcp.io

PCP is open source software released under the GNU General Public
License (GPL) and GNU Lesser General Public License (LGPL)

About This Guide

Conventions
The following conventions are used throughout this document:
Convention

Meaning

${PCP_VARIABLE}

A brace-enclosed all-capital-letters syntax indicates a variable that
has been sourced from the global ${PCP_DIR}/etc/pcp.conf
file. These special variables indicate parameters that affect all PCP
commands, and are likely to be different between platforms.

command

This fixed-space font denotes literal items such as commands, files,
routines, path names, signals, messages, and programming language
structures.

variable

Italic typeface denotes variable entries and words or concepts being
defined.

user input

This bold, fixed-space font denotes literal items that the user enters in
interactive sessions. (Output is shown in nonbold, fixed-space font.)

[]

Brackets enclose optional portions of a command or directive line.

...

Ellipses indicate that a preceding element can be repeated.

ALL CAPS

All capital letters denote environment variables, operator names,
directives, defined constants, and macros in C programs.

()

Parentheses that follow function names surround function arguments
or are empty if the function has no arguments; parentheses that
follow commands surround man page section numbers.

Reader Comments
If you have comments about the technical accuracy, content, or organization of this document, contact the
PCP maintainers using either the email address or the web site listed earlier.
We value your comments and will respond to them promptly.

Chapter 1. Introduction to PCP
Table of Contents
Objectives .......................................................................................................................... 1
PCP Target Usage ....................................................................................................... 2
Empowering the PCP User ........................................................................................... 2
Unification of Performance Metric Domains .................................................................... 2
Uniform Naming and Access to Performance Metrics ....................................................... 2
PCP Distributed Operation ........................................................................................... 2
Dynamic Adaptation to Change ..................................................................................... 3
Logging and Retrospective Analysis .............................................................................. 3
Automated Operational Support .................................................................................... 3
PCP Extensibility ........................................................................................................ 3
Metric Coverage ......................................................................................................... 4
Conceptual Foundations ....................................................................................................... 4
Performance Metrics ................................................................................................... 4
Performance Metric Instances ....................................................................................... 4
Current Metric Context ................................................................................................ 5
Sources of Performance Metrics and Their Domains ......................................................... 5
Distributed Collection .................................................................................................. 6
Performance Metrics Name Space ................................................................................. 6
Descriptions for Performance Metrics ............................................................................. 7
Values for Performance Metrics .................................................................................... 7
Collector and Monitor Roles ......................................................................................... 8
Retrospective Sources of Performance Metrics ................................................................. 8
Product Extensibility ................................................................................................... 9
Overview of Component Software ......................................................................................... 9
Performance Monitoring and Visualization ...................................................................... 9
Collecting, Transporting, and Archiving Performance Information ..................................... 10
Operational and Infrastructure Support .......................................................................... 12
Application and Agent Development ............................................................................ 13
This chapter provides an introduction to Performance Co-Pilot (PCP), an overview of its individual
components, and conceptual information to help you use this software.
The following sections are included:
• the section called “Objectives” covers the intended purposes of PCP.
• the section called “Overview of Component Software”, describes PCP tools and agents.
• the section called “Conceptual Foundations”, discusses the design theories behind PCP.

Objectives
Performance Co-Pilot (PCP) provides a range of services that may be used to monitor and manage
system performance. These services are distributed and scalable to accommodate the most complex system
configurations and performance problems.

Introduction to PCP

PCP Target Usage
PCP is targeted at the performance analyst, benchmarker, capacity planner, developer, database
administrator, or system administrator with an interest in overall system performance and a need to
quickly isolate and understand performance behavior, resource utilization, activity levels, and bottlenecks
in complex systems. Platforms that can benefit from this level of performance analysis include large
servers, server clusters, or multiserver sites delivering Database Management Systems (DBMS), compute,
Web, file, or video services.

Empowering the PCP User
To deal efficiently with the dynamic behavior of complex systems, performance analysts need to filter
out noise from the overwhelming stream of performance data, and focus on exceptional scenarios.
Visualization of current and historical performance data, and automated reasoning about performance data,
effectively provide this filtering.
From the PCP end user's perspective, PCP presents an integrated suite of tools, user interfaces, and services
that support real-time and retrospective performance analysis, with a bias towards eliminating mundane
information and focusing attention on the exceptional and extraordinary performance behaviors. When this
is done, the user can concentrate on in-depth analysis or target management procedures for those critical
system performance problems.

Unification of Performance Metric Domains
At the lowest level, performance metrics are collected and managed in autonomous performance domains
such as the operating system kernel, a DBMS, a layered service, or an end-user application. These domains
feature a multitude of access control policies, access methods, data semantics, and multiversion support.
All this detail is irrelevant to the developer or user of a performance monitoring tool, and is hidden by
the PCP infrastructure.
Performance Metrics Domain Agents (PMDAs) within PCP encapsulate the knowledge about, and export
performance information from, autonomous performance domains.

Uniform Naming and Access to Performance Metrics
Usability and extensibility of performance management tools mandate a single scheme for naming
performance metrics. The set of defined names constitutes a Performance Metrics Name Space (PMNS).
Within PCP, the PMNS is adaptive so it can be extended, reshaped, and pruned to meet the needs of
particular applications and users.
PCP provides a single interface to name and retrieve values for all performance metrics, independently
of their source or location.

PCP Distributed Operation
From a purely pragmatic viewpoint, a single workstation must be able to monitor the concurrent
performance of multiple remote hosts. At the same time, a single host may be subject to monitoring from
multiple remote workstations.
These requirements suggest a classic client-server architecture, which is exactly what PCP uses to provide
concurrent and multiconnected access to performance metrics, independent of their host location.

Introduction to PCP

Dynamic Adaptation to Change
Complex systems are subject to continual changes as network connections fail and are reestablished; nodes
are taken out of service and rebooted; hardware is added and removed; and software is upgraded, installed,
or removed. Often these changes are asynchronous and remote (perhaps in another geographic region or
domain of administrative control).
The distributed nature of the PCP (and the modular fashion in which performance metrics domains can be
installed, upgraded, and configured on different hosts) enables PCP to adapt concurrently to changes in the
monitored system(s). Variations in the available performance metrics as a consequence of configuration
changes are handled automatically and become visible to all clients as soon as the reconfigured host is
rebooted or the responsible agent is restarted.
PCP also detects loss of client-server connections, and most clients support subsequent automated
reconnection.

Logging and Retrospective Analysis
A range of tools is provided to support flexible, adaptive logging of performance metrics for archive,
playback, remote diagnosis, and capacity planning. PCP archive logs may be accumulated either at the
host being monitored, at a monitoring workstation, or both.
A universal replay mechanism, modeled on media controls [http://en.wikipedia.org/wiki/Media_controls],
supports play, step, rewind, fast forward and variable speed processing of archived performance data.
Replay for multiple archives, from multiple hosts, is facilitated by an archive aggregation concept.
Most PCP applications are able to process archive logs and real-time performance data with equal facility.
Unification of real-time access and access to the archive logs, in conjunction with the media controls,
provides powerful mechanisms for building performance tools and to review both current and historical
performance data.

Automated Operational Support
For operational and production environments, PCP provides a framework with scripts to customize in
order to automate the execution of ongoing tasks such as these:
• Centralized archive logging for multiple remote hosts
• Archive log rotation, consolidation, and culling
• Web-based publishing of charts showing snapshots of performance activity levels in the recent past
• Flexible alarm monitoring: parameterized rules to address common critical performance scenarios and
facilities to customize and refine this monitoring
• Retrospective performance audits covering the recent past; for example, daily or weekly checks for
performance regressions or quality of service problems

PCP Extensibility
PCP permits the integration of new performance metrics into the PMNS, the collection infrastructure, and
the logging framework. The guiding principle is, “if it is important for monitoring system performance,
and you can measure it, you can easily integrate it into the PCP framework.”

Introduction to PCP

For many PCP users, the most important performance metrics are not those already supported, but new
performance metrics that characterize the essence of good or bad performance at their site, or within their
particular application environment.
One example is an application that measures the round-trip time for a benign “probe” transaction against
some mission-critical application.
For application developers, a library is provided to support easy-to-use insertion of trace and monitoring
points within an application, and the automatic export of resultant performance data into the PCP
framework. Other libraries and tools aid the development of customized and fully featured Performance
Metrics Domain Agents (PMDAs).
Extensive source code examples are provided in the distribution, and by using the PCP toolkit and
interfaces, these customized measures of performance or quality of service can be easily and seamlessly
integrated into the PCP framework.

Metric Coverage
The core PCP modules support export of performance metrics that include kernel instrumentation,
hardware instrumentation, process-level resource utilization, database and other system services
instrumentation, and activity in the PCP collection infrastructure.
The supplied agents support thousands of distinct performance metrics, many of which can have multiple
values, for example, per disk, per CPU, or per process.

Conceptual Foundations
The following sections provide a detailed overview of concepts that underpin Performance Co-Pilot (PCP).

Performance Metrics
Across all of the supported performance metric domains, there are a large number of performance metrics.
Each metric has its own structure and semantics. PCP presents a uniform interface to these metrics,
independent of the underlying metric data source.
The Performance Metrics Name Space (PMNS) provides a hierarchical classification of human-readable
metric names, and a mapping from these external names to internal metric identifiers. See the section
called “Performance Metrics Name Space”, for a description of the PMNS.

Performance Metric Instances
When performance metric values are returned to a requesting application, there may be more than one
value instance for a particular metric; for example, independent counts for each CPU, process, disk, or local
filesystem. Internal instance identifiers correspond one to one with external (human-readable) descriptions
of the members of an instance domain.
Transient performance metrics (such as per-process information) cause repeated requests for the same
metric to return different numbers of values, or changes in the particular instance identifiers returned.
These changes are expected and fully supported by the PCP infrastructure; however, metric instantiation
is guaranteed to be valid only at the time of collection.

Introduction to PCP

Current Metric Context
When performance metrics are retrieved, they are delivered in the context of a particular source of metrics,
a point in time, and a profile of desired instances. This means that the application making the request has
already negotiated to establish the context in which the request should be executed.
A metric source may be the current performance data from a particular host (a live or real-time source),
or a set of archive logs of performance data collected by pmlogger at some distant host or at an earlier
time (a retrospective or archive source).
By default, the collection time for a performance metric is the current time of day for real-time sources, or
current point within an archive source. For archives, the collection time may be reset to an arbitrary time
within the bounds of the set of archive logs.

Sources of Performance Metrics and Their Domains
Instrumentation for the purpose of performance monitoring typically consists of counts of activity
or events, attribution of resource consumption, and service-time or response-time measures. This
instrumentation may exist in one or more of the functional domains as shown in Figure 1.1, “Performance
Metric Domains as Autonomous Collections of Data”.

Figure 1.1. Performance Metric Domains as Autonomous Collections of Data

Each domain has an associated access method:
• The operating system kernel, including sub-system data structures - per-process resource consumption,
network statistics, disk activity, or memory management instrumentation.
• A layered software service such as activity logs for a World Wide Web server or an email delivery server.
• An application program such as measured response time for a production application running a periodic
and benign probe transaction (as often required in service level agreements), or rate of computation and
throughput in jobs per minute for a batch stream.
• External equipment such as network routers and bridges.
For each domain, the set of performance metrics may be viewed as an abstract data type, with an associated
set of methods that may be used to perform the following tasks:
• Interrogate the metadata that describes the syntax and semantics of the performance metrics
• Control (enable or disable) the collection of some or all of the metrics
• Extract instantiations (current values) for some or all of the metrics
We refer to each functional domain as a performance metrics domain and assume that domains are
functionally, architecturally, and administratively independent and autonomous. Obviously the set of
performance metrics domains available on any host is variable, and changes with time as software and
hardware are installed and removed.
The number of performance metrics domains may be further enlarged in cluster-based or network-based
configurations, where there is potentially an instance of each performance metrics domain on each node.

Introduction to PCP

Hence, the management of performance metrics domains must be both extensible at a particular host and
distributed across a number of hosts.
Each performance metrics domain on a particular host must be assigned a unique Performance Metric
Identifier (PMID). In practice, this means unique identifiers are assigned globally for each performance
metrics domain type. For example, the same identifier would be used for the Apache Web Server
performance metrics domain on all hosts.

Distributed Collection
The performance metrics collection architecture is distributed, in the sense that any performance tool may
be executing remotely. However, a PMDA usually runs on the system for which it is collecting performance
measurements. In most cases, connecting these tools together on the collector host is the responsibility of
the PMCD process, as shown in Figure 1.2, “Process Structure for Distributed Operation”.

Figure 1.2. Process Structure for Distributed Operation

The host running the monitoring tools does not require any collection tools, including pmcd, because all
requests for metrics are sent to the pmcd process on the collector host. These requests are then forwarded
to the appropriate PMDAs, which respond with metric descriptions, help text, and most importantly, metric
values.
The connections between monitor clients and pmcd processes are managed in libpcp, below the PMAPI
level; see the pmapi(3) man page. Connections between PMDAs and pmcd are managed by the PMDA
routines; see the pmda(3) man page. There can be multiple monitor clients and multiple PMDAs on the
one host, but normally there would be only one pmcd process.

Performance Metrics Name Space
Internally, each unique performance metric is identified by a Performance Metric Identifier (PMID) drawn
from a universal set of identifiers, including some that are reserved for site-specific, application-specific,
and customer-specific use.
An external name space - the Performance Metrics Name Space (PMNS) - maps from a hierarchy (or tree)
of human-readable names to PMIDs.

Performance Metrics Name Space Diagram
Each node in the PMNS tree is assigned a label that must begin with an alphabet character, and be followed
by zero or more alphanumeric characters or the underscore (_) character. The root node of the tree has
the special label of root.
A metric name is formed by traversing the tree from the root to a leaf node with each node label on the
path separated by a period. The common prefix root. is omitted from all names. For example, Figure 1.3,
“Small Performance Metrics Name Space (PMNS) ” shows the nodes in a small subsection of a PMNS.

Figure 1.3. Small Performance Metrics Name Space (PMNS)

In this subsection, the following are valid names for performance metrics:
kernel.percpu.syscall

Introduction to PCP

network.tcp.rcvpack
hw.router.recv.total_util

Descriptions for Performance Metrics
Through the various performance metric domains, the PCP must support a wide range of formats
and semantics for performance metrics. This metadata describing the performance metrics includes the
following:
• The internal identifier, Performance Metric Identifier (PMID), for the metric
• The format and encoding for the values of the metric, for example, an unsigned 32-bit integer or a string
or a 64-bit IEEE format floating point number
• The semantics of the metric, particularly the interpretation of the values as free-running counters or
instantaneous values
• The dimensionality of the values, in the dimensions of events, space, and time
• The scale of values; for example, bytes, kilobytes (KB), or megabytes (MB) for the space dimension
• An indication if the metric may have one or many associated values
• Short (and extended) help text describing the metric
For each metric, this metadata is defined within the associated PMDA, and PCP arranges for the
information to be exported to performance tools that use the metadata when interpreting the values for
each metric.

Values for Performance Metrics
The following sections describe two types of performance metrics, single-valued and set-valued.

Single-Valued Performance Metrics
Some performance metrics have a singular value within their performance metric domains. For example,
available memory (or the total number of context switches) has only one value per performance metric
domain, that is, one value per host. The metadata describing the metric makes this fact known to
applications that process values for these metrics.

Set-Valued Performance Metrics
Some performance metrics have a set of values or instances in each implementing performance metric
domain. For example, one value for each disk, one value for each process, one value for each CPU, or one
value for each activation of a given application.
When a metric has multiple instances, the PCP framework does not pollute the Name Space with additional
metric names; rather, a single metric may have an associated set of values. These multiple values are
associated with the members of an instance domain, such that each instance has a unique instance identifier
within the associated instance domain. For example, the “per CPU” instance domain may use the instance
identifiers 0, 1, 2, 3, and so on to identify the configured processors in the system.
Internally, instance identifiers are encoded as binary values, but each performance metric domain also
supports corresponding strings as external names for the instance identifiers, and these names are used at
the user interface to the PCP utilities.

Introduction to PCP

For example, the performance metric disk.dev.total counts I/O operations for each disk spindle,
and the associated instance domain contains one member for each disk spindle. On a system with five
specific disks, one value would be associated with each of the external and internal instance identifier pairs
shown in Table 1.1, “Sample Instance Identifiers for Disk Statistics ”.

Table 1.1. Sample Instance Identifiers for Disk Statistics
External Instance Identifier

Internal Instance Identifier

disk0

131329

disk1

131330

disk2

131331

disk3

131841

disk4

131842

Multiple performance metrics may be associated with a single instance domain.
Each performance metric domain may dynamically establish the instances within an instance domain.
For example, there may be one instance for the metric kernel.percpu.idle on a workstation,
but multiple instances on a multiprocessor server. Even more dynamic is filesys.free, where the
values report the amount of free space per file system, and the number of values tracks the mounting and
unmounting of local filesystems.
PCP arranges for information describing instance domains to be exported from the performance metric
domains to the applications that require this information. Applications may also choose to retrieve values
for all instances of a performance metric, or some arbitrary subset of the available instances.

Collector and Monitor Roles
Hosts supporting PCP services are broadly classified into two categories:
Collector

Hosts that have pmcd and one or more performance metric domain agents (PMDAs)
running to collect and export performance metrics

Monitor

Hosts that import performance metrics from one or more collector hosts to be
consumed by tools to monitor, manage, or record the performance of the collector
hosts

Each PCP enabled host can operate as a collector, a monitor, or both.

Retrospective Sources of Performance Metrics
The PMAPI also supports delivery of performance metrics from a historical source in the form of a PCP
archive log. Archive logs are created using the pmlogger utility, and are replayed in an architecture as
shown in Figure 1.4, “Architecture for Retrospective Analysis”.

Figure 1.4. Architecture for Retrospective Analysis

The PMAPI has been designed to minimize the differences required for an application to process
performance data from an archive or from a real-time source. As a result, most PCP tools support live and
retrospective monitoring with equal facility.

Introduction to PCP

Product Extensibility
Much of the PCP software's potential for attacking difficult performance problems in production
environments comes from the design philosophy that considers extensibility to be critically important.
The performance analyst can take advantage of the PCP infrastructure to deploy value-added performance
monitoring tools and services. Here are some examples:
• Easy extension of the PCP collector to accommodate new performance metrics and new sources of
performance metrics, in particular using the interfaces of a special-purpose library to develop new
PMDAs (see the pmda(3) man page)
• Use of libraries (libpcp_pmda and libpcp_mmv) to aid in the development of new capabilities to
export performance metrics from local applications
• Operation on any performance metric using generalized toolkits
• Distribution of PCP components such as collectors across the network, placing the service where it can
do the most good
• Dynamic adjustment to changes in system configuration
• Flexible customization built into the design of all PCP tools
• Creation of new monitor applications, using the routines described in the pmapi(3) man page

Overview of Component Software
Performance Co-Pilot (PCP) is composed of both text-based and graphical tools. Each tool is fully
documented by a man page. These man pages are named after the tools or commands they describe, and
are accessible through the man command. For example, to see the pminfo(1) man page for the pminfo
command, enter this command:
man pminfo
A representative list of PCP tools and commands, grouped by functionality, is provided in the following
four sections.

Performance Monitoring and Visualization
The following tools provide the principal services for the PCP end-user with an interest in monitoring,
visualizing, or processing performance information collected either in real time or from PCP archive logs:
pcp-atop

Full-screen monitor of the load on a system from a kernel, hardware and
processes point of view. It is modeled on the Linux atop(1) tool (home page
[http://www.atoptool.nl/]) and provides a showcase for the variety of data
available using PCP services and the Python scripting interfaces.

pmchart

Strip chart tool for arbitrary performance metrics. Interactive graphical
utility that can display multiple charts simultaneously, from multiple hosts
or set of archives, aligned on a unified time axis (X-axis), or on multiple tabs.

pcp-collectl

Statistics collection tool with good coverage of a number of Linux
kernel subsystems, with the everything-in-one-tool approach pioneered by
sar(1). It is modeled on the Linux collectl(1) utility (home page [http://

Introduction to PCP

collectl.sourceforge.net/]) and provides another example of use of the
Python scripting interfaces to build more complex functionality with relative
ease, with PCP as a foundation.
pmrep

Outputs the values of arbitrary performance metrics collected live or from
a single PCP archive, in textual format.

pmevent

Reports on event metrics, decoding the timestamp and event parameters for
text-based reporting.

pmie

Evaluates predicate-action rules over performance metrics for alarms,
automated system management tasks, dynamic configuration tuning, and so
on. It is an inference engine.

pmieconf

Creates parameterized rules to be used with the PCP inference engine
(pmie). It can be run either interactively or from scripts for automating the
setup of inference (the PCP start scripts do this, for example, to generate a
default configuration).

pminfo

Displays information about arbitrary performance metrics available from
PCP, including help text with -T.

pmlogsummary

Calculates and reports various statistical summaries of the performance
metric values from a set of PCP archives.

pmprobe

Probes for performance metric availability, values, and instances.

pmstat

Provides a text-based display of metrics that summarize the performance of
one or more systems at a high level.

pmval

Provides a text-based display of the values for arbitrary instances of a
selected performance metric, suitable for ASCII logs or inquiry over a slow
link.

Collecting, Transporting, and Archiving Performance
Information
PCP provides the following tools to support real-time data collection, network transport, and archive log
creation services for performance data:
mkaf

Aggregates an arbitrary collection of PCP archive logs into a folio
to be used with pmafm.

pmafm

Interrogates, manages, and replays an archive folio as created
by mkaf, or the periodic archive log management scripts, or the
record mode of other PCP tools.

pmcd

Is the Performance Metrics Collection Daemon (PMCD). This
daemon must run on each system being monitored, to collect
and export the performance information necessary to monitor the
system.

pmcd_wait

Waits for pmcd to be ready to accept client connections.

pmdaapache

Exports performance metrics from the Apache Web Server. It is
a Performance Metrics Domain Agent (PMDA).

Introduction to PCP

pmdacisco

Extracts performance metrics from one or more Cisco routers.

pmdaelasticseach

Extracts performance metrics from an elasticsearch cluster.

pmdagfs2

Exports performance metrics from the GFS2 clustered filesystem.

pmdagluster

Extracts performance metrics from the Gluster filesystem.

pmdainfiniband

Exports performance metrics from the Infiniband kernel driver.

pmdakvm

Extracts performance metrics from the Linux Kernel Virtual
Machine (KVM) infrastructure.

pmdalustrecomm

Exports performance metrics from the Lustre clustered filesystem.

pmdamailq

Exports performance metrics describing the current state of items
in the sendmail queue.

pmdamemcache

Extracts performance metrics from memcached, a distributed
memory caching daemon commonly used to improve web serving
performance.

pmdammv
Exports metrics from instrumented applications linked with the
pcp_mmv shared library or the Parfait [http://code.google.com/
p/parfait/] framework for Java instrumentation. These metrics are
custom developed per application, and in the case of Parfait,
automatically include numerous JVM, Tomcat and other server or
container statistics.
pmdamysql

Extracts performance metrics from the MySQL relational
database.

pmdanamed

Exports performance metrics from the Internet domain name
server, named.

pmdanginx

Extracts performance metrics from the nginx HTTP and reverse
proxy server.

pmdapostfix

Export performance metrics from the Postfix mail transfer agent.

pmdapostgres

Extracts performance metrics from the PostgreSQL relational
database.

pmdaproc

Exports performance metrics for running processes.

pmdarsyslog

Extracts performance metrics from the Reliable System Log
daemon.

pmdasamba

Extracts performance metrics from Samba, a Windows SMB/
CIFS server.

pmdasendmail

Exports mail activity statistics from sendmail.

pmdashping

Exports performance metrics for the availability and quality of
service (response-time) for arbitrary shell commands.

pmdasnmp

Extracts SNMP performance metrics from local or remote SNMPenabled devices.

Introduction to PCP

pmdasummary

Derives performance metrics values from values made available
by other PMDAs. It is a PMDA itself.

pmdasystemd

Extracts performance metrics from the systemd and journald
services.

pmdatrace

Exports transaction performance metrics from application
processes that use the pcp_trace library.

pmdavmware

Extracts performance metrics from a VMWare virtualization host.

pmdaweblog
Scans Web-server logs to extract metrics characterizing.
pmdaxfs

Extracts performance metrics from the Linux kernel XFS
filesystem implementation.

pmdumplog

Displays selected state information, control data, and metric
values from a set of PCP archive logs created by pmlogger.

pmlc

Exercises control over an instance of the PCP archive logger
pmlogger, to modify the profile of which metrics are logged and/
or how frequently their values are logged.

pmlogcheck

Performs integrity check for individual PCP archives.

pmlogconf

Creates or modifies pmlogger configuration files for many
common logging scenarios, optionally probing for available
metrics and enabled functionality. It can be run either interactively
or from scripts for automating the setup of data logging (the
PCP start scripts do this, for example, to generate a default
configuration).

pmlogextract

Reads one or more PCP archive logs and creates a temporally
merged and reduced PCP archive log as output.

pmlogger

Creates PCP archive logs of performance metrics over time. Many
tools accept these PCP archive logs as alternative sources of
metrics for retrospective analysis.

pmproxy

Allows the execution of PCP tools through a network firewall
system.

pmtrace

Provides a simple command line interface to the trace PMDA and
its associated pcp_trace library.

pmwebd

Is the Performance Metrics Web Daemon, a front-end to both
pmcd and PCP archives, providing a JSON interface suitable for
use by web-based tools wishing to access performance data over
HTTP.

Operational and Infrastructure Support
PCP provides the following tools to support the PCP infrastructure and assist operational procedures for
PCP deployment in a production environment:
pcp

Summarizes that state of a PCP installation.

Introduction to PCP

pmdbg

Describes the available facilities and associated control flags. PCP tools include
internal diagnostic and debugging facilities that may be activated by run-time
flags.

pmerr

Translates PCP error codes into human-readable error messages.

pmhostname

Reports hostname as returned by gethostbyname. Used in assorted PCP
management scripts.

pmie_check

Administration of the Performance Co-Pilot inference engine (pmie).

pmlock

Attempts to acquire an exclusive lock by creating a file with a mode of 0.

pmlogger_*

Allows you to create a customized regime of administration and management
for PCP archive log files. The pmlogger_check, pmlogger_daily, and
pmlogger_merge scripts are intended for periodic execution via the cron
command.

pmnewlog

Performs archive log rotation by stopping and restarting an instance of pmlogger.

pmnsadd

Adds a subtree of new names into a PMNS, as used by the components of PCP.

pmnsdel

Removes a subtree of names from a PMNS, as used by the components of the
PCP.

pmnsmerge

Merges multiple PMNS files together, as used by the components of PCP.

pmstore

Reinitializes counters or assigns new values to metrics that act as control
variables. The command changes the current values for the specified instances
of a single performance metric.

Application and Agent Development
The following PCP tools aid the development of new programs to consume performance data, and new
agents to export performance data within the PCP framework:
chkhelp

Checks the consistency of performance metrics help database files.

dbpmda

Allows PMDA behavior to be exercised and tested. It is an interactive debugger for
PMDAs.

newhelp

Generates the database files for one or more source files of PCP help text.

pmapi

Defines a procedural interface for developing PCP client applications. It is the
Performance Metrics Application Programming Interface (PMAPI).

pmclient

Is a simple client that uses the PMAPI to report some high-level system performance
metrics.

pmda

Is a library used by many shipped PMDAs to communicate with a pmcd process. It
can expedite the development of new and custom PMDAs.

pmgenmap

Generates C declarations and cpp(1) macros to aid the development of customized
programs that use the facilities of PCP. It is a PMDA development tool.

Chapter 2. Installing and Configuring
Performance Co-Pilot
Table of Contents
Product Structure ..............................................................................................................
Performance Metrics Collection Daemon (PMCD) ..................................................................
Starting and Stopping the PMCD .................................................................................
Restarting an Unresponsive PMCD ..............................................................................
PMCD Diagnostics and Error Messages ........................................................................
PMCD Options and Configuration Files ........................................................................
Managing Optional PMDAs ................................................................................................
PMDA Installation on a PCP Collector Host ..................................................................
PMDA Removal on a PCP Collector Host .....................................................................
Troubleshooting ................................................................................................................
Performance Metrics Name Space ................................................................................
Missing and Incomplete Values for Performance Metrics .................................................
Kernel Metrics and the PMCD ....................................................................................

14
15
15
15
15
16
20
21
22
23
23
23
23

The sections in this chapter describe the basic installation and configuration steps necessary to run
Performance Co-Pilot (PCP) on your systems. The following major sections are included:
• the section called “Product Structure” describes the main packages of PCP software and how they must
be installed on each system.
• the section called “Performance Metrics Collection Daemon (PMCD)”, describes the fundamentals of
maintaining the performance data collector.
• the section called “Managing Optional PMDAs”, describes the basics of installing a new Performance
Metrics Domain Agent (PMDA) to collect metric data and pass it to the PMCD.
• the section called “Troubleshooting”, offers advice on problems involving the PMCD.

Product Structure
In a typical deployment, Performance Co-Pilot (PCP) would be installed in a collector configuration on
one or more hosts, from which the performance information could then be collected, and in a monitor
configuration on one or more workstations, from which the performance of the server systems could then
be monitored.
On some platforms Performance Co-Pilot is presented as multiple packages; typically separating the server
components from graphical user interfaces and documentation.
pcp-X.Y.Z-rev

package for core PCP

pcp-gui-X.Y.Z-rev

package for graphical PCP client tools

pcp-doc-X.Y.Z-rev

package for online PCP documentation

Installing and Configuring
Performance Co-Pilot

Performance Metrics Collection Daemon
(PMCD)
On each Performance Co-Pilot (PCP) collection system, you must be certain that the pmcd daemon is
running. This daemon coordinates the gathering and exporting of performance statistics in response to
requests from the PCP monitoring tools.

Starting and Stopping the PMCD
To start the daemon, enter the following commands as root on each PCP collection system:
chkconfig pmcd on
${PCP_RC_DIR}/pmcd start
These commands instruct the system to start the daemon immediately, and again whenever the system
is booted. It is not necessary to start the daemon on the monitoring system unless you wish to collect
performance information from it as well.
To stop pmcd immediately on a PCP collection system, enter the following command:
${PCP_RC_DIR}/pmcd stop

Restarting an Unresponsive PMCD
Sometimes, if a daemon is not responding on a PCP collection system, the problem can be resolved by
stopping and then immediately restarting a fresh instance of the daemon. If you need to stop and then
immediately restart PMCD on a PCP collection system, use the start argument provided with the script
in ${PCP_RC_DIR}. The command syntax is, as follows:
${PCP_RC_DIR}/pmcd start
On startup, pmcd looks for a configuration file at ${PCP_PMCDCONF_PATH}. This file specifies which
agents cover which performance metrics domains and how PMCD should make contact with the agents.
A comprehensive description of the configuration file syntax and semantics can be found in the pmcd(1)
man page.
If the configuration is changed, pmcd reconfigures itself when it receives the SIGHUP signal. Use the
following command to send the SIGHUP signal to the daemon:
${PCP_BINADM_DIR}/pmsignal -a -s HUP pmcd
This is also useful when one of the PMDAs managed by pmcd has failed or has been terminated by
pmcd. Upon receipt of the SIGHUP signal, pmcd restarts any PMDA that is configured but inactive. The
exception to this rule is the case of a PMDA which must run with superuser privileges (where possible,
this is avoided) - for these PMDAs, a full pmcd restart must be performed, using the process described
earlier (not SIGHUP).

PMCD Diagnostics and Error Messages
If there is a problem with pmcd, the first place to investigate should be the pmcd.log file. By default,
this file is in the ${PCP_LOG_DIR}/pmcd directory.

Installing and Configuring
Performance Co-Pilot

PMCD Options and Configuration Files
There are two files that control PMCD operation. These are the ${PCP_PMCDCONF_PATH} and
${PCP_PMCDOPTIONS_PATH} files. The pmcd.options file contains the command line options
used with PMCD; it is read when the daemon is invoked by ${PCP_RC_DIR}/pmcd. The pmcd.conf
file contains configuration information regarding domain agents and the metrics that they monitor. These
configuration files are described in the following sections.

The pmcd.options File
Command line options for the PMCD are stored in the ${PCP_PMCDOPTIONS_PATH} file. The PMCD
can be invoked directly from a shell prompt, or it can be invoked by ${PCP_RC_DIR}/pmcd as part
of the boot process. It is usual and normal to invoke it using ${PCP_RC_DIR}/pmcd, reserving shell
invocation for debugging purposes.
The PMCD accepts certain command line options to control its execution, and these options are placed
in the pmcd.options file when ${PCP_RC_DIR}/pmcd is being used to start the daemon. The
following options (amongst others) are available:
-i address

For hosts with more than one network interface, this option specifies the
interface on which this instance of the PMCD accepts connections. Multiple i options may be specified. The default in the absence of any -i option is for
PMCD to accept connections on all interfaces.

-l file

Specifies a log file. If no -l option is specified, the log file name is pmcd.log
and it is created in the directory ${PCP_LOG_DIR}/pmcd/.

-s file

Specifies the path to a local unix domain socket (for platforms supporting
this socket family only). The default value is ${PCP_RUN_DIR}/
pmcd.socket.

-t seconds

Specifies the amount of time, in seconds, before PMCD times out on protocol
data unit (PDU) exchanges with PMDAs. If no time out is specified, the default
is five seconds. Setting time out to zero disables time outs (not recommended,
PMDAs should always respond quickly).
The time out may be dynamically modified by storing the number of seconds
into the metric pmcd.control.timeout using pmstore.

-T mask

Specifies whether connection and PDU tracing are turned on for debugging
purposes.

See the pmcd(1) man page for complete information on these options.
The default pmcd.options file shipped with PCP is similar to the following:
# command-line options to pmcd, uncomment/edit lines as required
# longer timeout delay for slow agents
# -t 10
# suppress timeouts
# -t 0

Installing and Configuring
Performance Co-Pilot
# make log go someplace else
# -l /some/place/else
# debugging knobs, see pmdbg(1)
# -D N
# -f
# Restricting (further) incoming PDU size to prevent DOS attacks
# -L 16384
# enable event tracing bit fields
#
1
trace connections
#
2
trace PDUs
# 256
unbuffered tracing
# -T 3
# setting of environment variables for pmcd and
# the PCP rc scripts. See pmcd(1) and PMAPI(3).
# PMCD_WAIT_TIMEOUT=120
The most commonly used options have been placed in this file for your convenience. To uncomment and
use an option, simply remove the pound sign (#) at the beginning of the line with the option you wish to
use. Restart pmcd for the change to take effect; that is, as superuser, enter the command:
${PCP_RC_DIR}/pmcd start

The pmcd.conf File
When the PMCD is invoked, it reads its configuration file, which is ${PCP_PMCDCONF_PATH}. This
file contains entries that specify the PMDAs used by this instance of the PMCD and which metrics are
covered by these PMDAs. Also, you may specify access control rules in this file for the various hosts,
users and groups on your network. This file is described completely in the pmcd(1) man page.
With standard PCP operation (even if you have not created and added your own PMDAs), you might need
to edit this file in order to add any additional access control you wish to impose. If you do not add access
control rules, all access for all operations is granted to the local host, and read-only access is granted to
remote hosts. The pmcd.conf file is automatically generated during the software build process and on
Linux, for example, is similar to the following:
Performance Metrics Domain Specifications
#
# This file is automatically generated during the build
# Name Id
IPC
IPC Params
File/Cmd
root 1 pipe binary /var/lib/pcp/pmdas/root/pmdaroot
pmcd
2
dso
pmcd_init
${PCP_PMDAS_DIR}/pmcd/pmda_pmcd.so
proc
3
pipe
binary
${PCP_PMDAS_DIR}/proc/pmdaproc -d 3
xfs
11
pipe
binary
${PCP_PMDAS_DIR}/xfs/pmdaxfs -d 11
linux
60
dso
linux_init
${PCP_PMDAS_DIR}/linux/pmda_linux.so
mmv 70 dso mmv_init /var/lib/pcp/pmdas/mmv/pmda_mmv.so
[access]
disallow ".*" : store;
disallow ":*" : store;
allow "local:*" : all;

Installing and Configuring
Performance Co-Pilot

Note
Even though PMCD does not run with root privileges, you must be very careful not to configure
PMDAs in this file if you are not sure of their action. This is because all PMDAs are initially
started as root (allowing them to assume alternate identities, such as postgres for example),
after which pmcd drops its privileges. Pay close attention that permissions on this file are not
inadvertently downgraded to allow public write access.
Each entry in this configuration file contains rules that specify how to connect the PMCD to a particular
PMDA and which metrics the PMDA monitors. A PMDA may be attached as a Dynamic Shared Object
(DSO) or by using a socket or a pair of pipes. The distinction between these attachment methods is
described below.
An entry in the pmcd.conf file looks like this:
label_name

domain_number

type

path

The label_name field specifies a name for the PMDA. The domain_number is an integer value that
specifies a domain of metrics for the PMDA. The type field indicates the type of entry (DSO, socket, or
pipe). The path field is for additional information, and varies according to the type of entry.
The following rules are common to DSO, socket, and pipe syntax:
label_name

An alphanumeric string identifying the agent.

domain_number

An unsigned integer specifying the agent's domain.

DSO entries follow this syntax:
label_name domain_number dso entry-point path
The following rules apply to the DSO syntax:
dso

The entry type.

entry-point

The name of an initialization function called when the DSO is loaded.

path

Designates the location of the DSO. An absolute path must be used. On most
platforms this will be a so suffixed file, on Windows it is a dll, and on Mac
OS X it is a dylib file.

Socket entries in the pmcd.conf file follow this syntax:
label_name domain_number socket addr_family address command [args]
The following rules apply to the socket syntax:
socket

The entry type.

addr_family

Specifies if the socket is AF_INET, AF_IPV6 or AF_UNIX. If the socket is
INET, the word inet appears in this place. If the socket is IPV6, the word
ipv6 appears in this place. If the socket is UNIX, the word unix appears in
this place.

address

Specifies the address of the socket. For INET or IPv6 sockets, this is a port
number or port name. For UNIX sockets, this is the name of the PMDA's socket
on the local host.

Installing and Configuring
Performance Co-Pilot
command

Specifies a command to start the PMDA when the PMCD is invoked and reads
the configuration file.

args

Optional arguments for command.

Pipe entries in the pmcd.conf file follow this syntax:
label_name domain_number pipe protocol command [args]
The following rules apply to the pipe syntax:
pipe

The entry type.

protocol

Specifies whether a text-based or a binary PCP protocol should be used over the pipes.
Historically, this parameter was able to be “text” or “binary.” The text-based protocol
has long since been deprecated and removed, however, so nowadays “binary” is the
only valid value here.

command

Specifies a command to start the PMDA when the PMCD is invoked and reads the
configuration file.

args

Optional arguments for command.

Controlling Access to PMCD with pmcd.conf
You can place this option extension in the pmcd.conf file to control access to performance metric data
based on hosts, users and groups. To add an access control section, begin by placing the following line
at the end of your pmcd.conf file:
[access]
Below this line, you can add entries of the following forms:
allow hosts hostlist : operations ;
disallow hosts hostlist : operations ;
allow users userlist : operations ;
disallow users userlist : operations ;
allow groups grouplist : operations ;
disallow groups grouplist : operations ;
The keywords users, groups and hosts can be used in either plural or singular form.
The userlist and grouplist fields are comma-separated lists of authenticated users and groups
from the local /etc/passwd and /etc/groups files, NIS (network information service) or LDAP
(lightweight directory access protocol) service.
The hostlist is a comma-separated list of host identifiers; the following rules apply:
• Host names must be in the local system's /etc/hosts file or known to the local DNS (domain name
service).
• IP and IPv6 addresses may be given in the usual numeric notations.
• A wildcarded IP or IPv6 address may be used to specify groups of hosts, with the single wildcard
character * as the last-given component of the address. The wildcard .* refers to all IP (IPv4) addresses.
The wildcard :* refers to all IPv6 addresses. If an IPv6 wildcard contains a :: component, then the final
* refers to the final 16 bits of the address only, otherwise it refers to the remaining unspecified bits of
the address.
The wildcard ``*'' refers to all users, groups or host addresses. Names of users, groups or hosts may not
be wildcarded.

Installing and Configuring
Performance Co-Pilot
For example, the following hostlist entries are all valid:
babylon
babylon.acme.com
123.101.27.44
localhost
155.116.24.*
192.*
.*
fe80::223:14ff:feaf:b62c
fe80::223:14ff:feaf:*
fe80:*
:*
*
The operations field can be any of the following:
• A comma-separated list of the operation types described below.
• The word all to allow or disallow all operations as specified in the first field.
• The words all except and a list of operations. This entry allows or disallows all operations as specified
in the first field except those listed.
• The phrase maximum N connections to set an upper bound (N) on the number of connections an
individual host, user or group of users may make. This can only be added to the operations list of
an allow statement.
The operations that can be allowed or disallowed are as follows:
fetch

Allows retrieval of information from the PMCD. This may be information about a metric
(such as a description, instance domain, or help text) or an actual value for a metric.

store

Allows the PMCD to store metric values in PMDAs that permit store operations. Be cautious
in allowing this operation, because it may be a security opening in large networks, although the
PMDAs shipped with the PCP package typically reject store operations, except for selected
performance metrics where the effect is benign.

For example, here is a sample access control portion of a ${PCP_PMCDCONF_PATH} file:
allow hosts babylon, moomba : all ;
disallow user sam : all ;
allow group dev : fetch ;
allow hosts 192.127.4.* : fetch ;
disallow host gate-inet : store ;
Complete information on access control syntax rules in the pmcd.conf file can be found in the pmcd(1)
man page.

Managing Optional PMDAs
Some Performance Metrics Domain Agents (PMDAs) shipped with Performance Co-Pilot (PCP) are
designed to be installed and activated on every collector host, for example, linux, windows, darwin,
pmcd, and process PMDAs.
Other PMDAs are designed for optional activation and require some user action to make them operational.
In some cases these PMDAs expect local site customization to reflect the operational environment, the

Installing and Configuring
Performance Co-Pilot
system configuration, or the production workload. This customization is typically supported by interactive
installation scripts for each PMDA.
Each PMDA has its own directory located below ${PCP_PMDAS_DIR}. Each directory contains a
Remove script to unconfigure the PMDA, remove the associated metrics from the PMNS, and restart the
pmcd daemon; and an Install script to install the PMDA, update the PMNS, and restart the PMCD
daemon.
As a shortcut mechanism to support automated PMDA installation, a file named .NeedInstall can be
created in a PMDA directory below ${PCP_PMDAS_DIR}. The next restart of PCP services will invoke
that PMDAs installation automatically, with default options taken.

PMDA Installation on a PCP Collector Host
To install a PMDA you must perform a collector installation for each host on which the PMDA is required
to export performance metrics. PCP provides a distributed metric namespace (PMNS) and metadata, so it
is not necessary to install PMDAs (with their associated PMNS) on PCP monitor hosts.
You need to update the PMNS, configure the PMDA, and notify PMCD. The Install script for each
PMDA automates these operations, as follows:
1. Log in as root (the superuser).
2. Change to the PMDA's directory as shown in the following example:
cd ${PCP_PMDAS_DIR}/cisco
3. In the unlikely event that you wish to use a non-default Performance Metrics Domain (PMD)
assignment, determine the current PMD assignment:
cat domain.h
Check that there is no conflict in the PMDs as defined in ${PCP_VAR_DIR}/pmns/stdpmid
and the other PMDAs currently in use (listed in ${PCP_PMCDCONF_PATH}). Edit domain.h to
assign the new domain number if there is a conflict (this is highly unlikely to occur in a regular PCP
installation).
4. Enter the following command:
./Install
You may be prompted to enter some local parameters or configuration options. The script applies all
required changes to the control files and to the PMNS, and then notifies PMCD. Example 2.1, “PMNS
Installation Output ” is illustrative of the interactions:

Example 2.1. PMNS Installation Output
Cisco hostname or IP address? [return to quit] wanmelb
A user-level password may be required for Cisco “show int” command.
If you are unsure, try the command
$ telnet wanmelb
and if the prompt “Password:” appears, a user-level password is
required; otherwise answer the next question with an empty line.
User-level Cisco password? ********

Installing and Configuring
Performance Co-Pilot
Probing Cisco for list of interfaces ...
Enter interfaces to monitor, one per line in the format
tX where “t” is a type and one of “e” (Ethernet), or “f” (Fddi), or
“s” (Serial), or “a” (ATM), and “X” is an interface identifier
which is either an integer (e.g. 4000 Series routers) or two
integers separated by a slash (e.g. 7000 Series routers).
The currently unselected interfaces for the Cisco “wanmelb” are:
e0 s0 s1
Enter “quit” to terminate the interface selection process.
Interface? [e0] s0
The currently unselected interfaces for the Cisco “wanmelb” are:
e0 s1
Enter “quit” to terminate the interface selection process.
Interface? [e0] s1
The currently unselected interfaces for the Cisco “wanmelb” are:
e0
Enter “quit” to terminate the interface selection process.
Interface? [e0] quit
Cisco hostname or IP address? [return to quit]
Updating the Performance Metrics Name Space (PMNS) ...
Installing pmchart view(s) ...
Terminate PMDA if already installed ...
Installing files ...
Updating the PMCD control file, and notifying PMCD ...
Check cisco metrics have appeared ... 5 metrics and 10 values

PMDA Removal on a PCP Collector Host
To remove a PMDA, you must perform a collector removal for each host on which the PMDA is currently
installed.
The PMNS needs to be updated, the PMDA unconfigured, and PMCD notified. The Remove script for
each PMDA automates these operations, as follows:
1. Log in as root (the superuser).
2. Change to the PMDA's directory as shown in the following example:
cd ${PCP_PMDAS_DIR}/elasticsearch
3. Enter the following command:
./Remove
The following output illustrates the result:
Culling the Performance Metrics Name Space ...
elasticsearch ... done
Updating the PMCD control file, and notifying PMCD ...
Removing files ...

Installing and Configuring
Performance Co-Pilot
Check elasticsearch metrics have gone away ... OK

Troubleshooting
The following sections offer troubleshooting advice on the Performance Metrics Name Space (PMNS),
missing and incomplete values for performance metrics, kernel metrics and the PMCD.
Advice for troubleshooting the archive logging system is provided in Chapter 6, Archive Logging.

Performance Metrics Name Space
To display the active PMNS, use the pminfo command; see the pminfo(1) man page.
The PMNS at the collector host is updated whenever a PMDA is installed or removed, and may also be
updated when new versions of PCP are installed. During these operations, the PMNS is typically updated
by merging the (plaintext) namespace components from each installed PMDA. These separate PMNS
components reside in the ${PCP_VAR_DIR}/pmns directory and are merged into the root file there.

Missing and Incomplete Values for Performance Metrics
Missing or incomplete performance metric values are the result of their unavailability.

Metric Values Not Available
The following symptom has a known cause and resolution:
Symptom:

Values for some or all of the instances of a performance metric are not
available.

Cause:

This can occur as a consequence of changes in the installation of modules (for
example, a DBMS or an application package) that provide the performance
instrumentation underpinning the PMDAs. Changes in the selection of
modules that are installed or operational, along with changes in the version of
these modules, may make metrics appear and disappear over time.
In simple terms, the PMNS contains a metric name, but when that metric is
requested, no PMDA at the collector host supports the metric.
For archive logs, the collection of metrics to be logged is a subset of the metrics
available, so utilities replaying from a PCP archive log may not have access to
all of the metrics available from a live (PMCD) source.

Resolution:

Make sure the underlying instrumentation is available and the module is active.
Ensure that the PMDA is running on the host to be monitored. If necessary,
create a new archive log with a wider range of metrics to be logged.

Kernel Metrics and the PMCD
The following issues involve the kernel metrics and the PMCD:
• Cannot connect to remote PMCD
• PMCD not reconfiguring after hang-up
• PMCD does not start

Installing and Configuring
Performance Co-Pilot

Cannot Connect to Remote PMCD
The following symptom has a known cause and resolution:
Symptom:

A PCP client tool (such as pmchart, pmie, or pmlogger) complains that
it is unable to connect to a remote PMCD (or establish a PMAPI context), but
you are sure that PMCD is active on the remote host.

Cause:

To avoid hanging applications for the duration of TCP/IP time outs, the PMAPI
library implements its own time out when trying to establish a connection to
a PMCD. If the connection to the host is over a slow network, then successful
establishment of the connection may not be possible before the time out, and
the attempt is abandoned.
Alternatively, there may be a firewall in-between the client tool and PMCD
which is blocking the connection attempt.
Finally, PMCD may be running in a mode where it does not acept remote
connections, or only listening on certain interface.

Resolution:

Establish that the PMCD on far-away-host is really alive, by connecting
to its control port (TCP port number 44321 by default):
telnet far-away-host 44321
This response indicates the PMCD is not running and needs restarting:
Unable to connect to remote host: Connection refused
To restart the PMCD on that host, enter the following command:
${PCP_RC_DIR}/pmcd start
This response indicates the PMCD is running:
Connected to far-away-host
Interrupt the telnet session, increase the PMAPI time out by setting
the PMCD_CONNECT_TIMEOUT environment variable to some number of
seconds (60 for instance), and try the PCP client tool again.
Verify that PMCD is not running in local-only mode, by looking for an enabled
value (one) from:
pminfo -f pmcd.feature.local
This setting is controlled from the PMCD_LOCAL environment variable usually
set via ${PCP_SYSCONFIG_PATH}/pmcd.
If these techniques are ineffective, it is likely an intermediary firewall is
blocking the client from accessing the PMCD port - resolving such issues is
firewall-host platform-specific and cannot practically be covered here.

PMCD Not Reconfiguring after SIGHUP
The following symptom has a known cause and resolution:
24

Installing and Configuring
Performance Co-Pilot
Symptom

PMCD does not reconfigure itself after receiving the SIGHUP signal.

Cause:

If there is a syntax error in ${PCP_PMCDCONF_PATH}, PMCD does not use
the contents of the file. This can lead to situations in which the configuration
file and PMCD's internal state do not agree.

Resolution:

Always monitor PMCD's log. For example, use the following command in
another window when reconfiguring PMCD, to watch errors occur:
tail -f ${PCP_LOG_DIR}/pmcd/pmcd.log

PMCD Does Not Start
The following symptom has a known cause and resolution:
Symptom:
If the following messages appear in the PMCD log (${PCP_LOG_DIR}/
pmcd/pmcd.log), consider the cause and resolution:

pcp[27020] Error: OpenRequestSocket(44321) bind: Address already
use
pcp[27020] Error: pmcd is already running
pcp[27020] Error: pmcd not started due to errors!
Cause:

PMCD is already running or was terminated before it could clean up properly.
The error occurs because the socket it advertises for client connections is
already being used or has not been cleared by the kernel.

Resolution:

Start PMCD as root (superuser) by typing:
${PCP_RC_DIR}/pmcd start
Any existing PMCD is shut down, and a new one is started in such a way that
the symptomatic message should not appear.
If you are starting PMCD this way and the symptomatic message appears,
a problem has occurred with the connection to one of the deceased PMCD's
clients.
This could happen when the network connection to a remote client is lost and
PMCD is subsequently terminated. The system may attempt to keep the socket
open for a time to allow the remote client a chance to reestablish the connection
and read any outstanding data.
The only solution in these circumstances is to wait until the socket times out
and the kernel deletes it. This netstat command displays the status of the socket
and any connections:
netstat -ant | grep 44321
If the socket is in the FIN_WAIT or TIME_WAIT state, then you must wait
for it to be deleted. Once the command above produces no output, PMCD may
be restarted. Less commonly, you may have another program running on your
system that uses the same Internet port number (44321) that PMCD uses.
Refer to the PCPIntro(1) man page for a description of how to override the
default PMCD port assignment using the PMCD_PORT environment variable.

Chapter 3. Common Conventions and
Arguments
Table of Contents
Alternate Metrics Source Options ........................................................................................
Fetching Metrics from Another Host ............................................................................
Fetching Metrics from an Archive Log .........................................................................
General PCP Tool Options .................................................................................................
Common Directories and File Locations .......................................................................
Alternate Performance Metric Name Spaces ..................................................................
Time Duration and Control .................................................................................................
Performance Monitor Reporting Frequency and Duration .................................................
Time Window Options ...............................................................................................
Timezone Options .....................................................................................................
PCP Environment Variables ................................................................................................
Running PCP Tools through a Firewall .................................................................................
The pmproxy service ................................................................................................
Transient Problems with Performance Metric Values ...............................................................
Performance Metric Wraparound .................................................................................
Time Dilation and Time Skew ....................................................................................

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This chapter deals with the user interface components that are common to most text-based utilities that
make up the monitor portion of Performance Co-Pilot (PCP). These are the major sections in this chapter:
• the section called “Alternate Metrics Source Options”, details some basic standards used in the
development of PCP tools.
• the section called “General PCP Tool Options”, details other options to use with PCP tools.
• the section called “Time Duration and Control”, describes the time control dialog and time-related
command line options available for use with PCP tools.
• the section called “PCP Environment Variables”, describes the environment variables supported by PCP
tools.
• the section called “Running PCP Tools through a Firewall”, describes how to execute PCP tools that
must retrieve performance data from the Performance Metrics Collection Daemon (PMCD) on the other
side of a TCP/IP security firewall.
• the section called “Transient Problems with Performance Metric Values ”, covers some uncommon
scenarios that may compromise performance metric integrity over the short term.
Many of the utilities provided with PCP conform to a common set of naming and syntactic conventions
for command line arguments and options. This section outlines these conventions and their meaning. The
options may be generally assumed to be honored for all utilities supporting the corresponding functionality.
In all cases, the man pages for each utility fully describe the supported command arguments and options.
Command line options are also relevant when starting PCP applications from the desktop using the Alt
double-click method. This technique launches the pmrun program to collect additional arguments to pass
along when starting a PCP application.

Common Conventions and Arguments

Alternate Metrics Source Options
The default source of performance metrics is from PMCD on the local host. This default pmcd connection
will be made using the Unix domain socket, if the platform supports that, else a localhost Inet socket
connection is made. This section describes how to obtain metrics from sources other than this default.

Fetching Metrics from Another Host
The option -h host directs any PCP utility (such as pmchart or pmie) to make a connection with
the PMCD instance running on host. Once established, this connection serves as the principal real-time
source of performance metrics and metadata. The host specification may be more than a simple host
name or address - it can also contain decorations specifying protocol type (secure or not), authentication
information, and other connection attributes. Refer to the PCPIntro(1) man page for full details of these,
and examples of use of these specifications can also be found in the PCP Tutorials and Case Studies
companion document.

Fetching Metrics from an Archive Log
The option -aarchive directs the utility to treat the set of PCP archive logs designated by archive as
the principal source of performance metrics and metadata. archive is a comma-sparated list of names,
each of which may be the base name of an archive or the name of a directory containing archives.
PCP archive logs are created with pmlogger. Most PCP utilities operate with equal facility for performance
information coming from either a real-time feed via PMCD on some host, or for historical data from a set
of PCP archive logs. For more information on archive logs and their use, see Chapter 6, Archive Logging.
The list of names (archive) used with the -a option implies the existence of the files created
automatically by pmlogger, as listed in Table 3.1, “Physical Filenames for Components of a PCP Archive
Log”.

Table 3.1. Physical Filenames for Components of a PCP Archive Log
Filename

Contents

archive. index

Temporal index for rapid access to archive contents

archive. meta

Metadata descriptions for performance metrics and instance domains
appearing in the archive

archive.N

Volumes of performance metrics values, for N = 0,1,2,...

Most tools are able to concurrently process multiple PCP archive logs (for example, for retrospective
analysis of performance across multiple hosts), and accept either multiple -a options or a comma separated
list of archive names following the -a option.

Note
The -h and -a options are almost always mutually exclusive. Currently, pmchart is the exception
to this rule but other tools may continue to blur this line in the future.

General PCP Tool Options
The following sections provide information relevant to most of the PCP tools. It is presented here in a
single place for convenience.

Common Conventions and Arguments

Common Directories and File Locations
The following files and directories are used by the PCP tools as repositories for option and configuration
files and for binaries:
${PCP_DIR}/etc/pcp.env

Script to set PCP run-time environment
variables.

${PCP_DIR}/etc/pcp.conf

PCP configuration and environment file.

${PCP_PMCDCONF_PATH}

Configuration
file
for
Performance
Metrics Collection Daemon (PMCD). Sets
environment variables, including PATH.

${PCP_BINADM_DIR}/pmcd

The PMCD binary.

${PCP_PMCDOPTIONS_PATH}

Command line options for PMCD.

${PCP_RC_DIR}/pmcd

The PMCD startup script.

${PCP_BIN_DIR}/pcptool

Directory containing PCP tools such
as
pmstat
,
pminfo,
pmlogger,
pmlogsummary, pmchart, pmie, and so on.

${PCP_SHARE_DIR}

Directory containing shareable PCP-specific
files and repository directories such as bin,
demos, examples and lib.

${PCP_VAR_DIR}

Directory containing non-shareable (that is,
per-host) PCP specific files and repository
directories.

${PCP_BINADM_DIR}/pcptool

PCP tools that are typically not executed
directly by the end user such as pmcd_wait.

${PCP_SHARE_DIR}/lib/pcplib

Miscellaneous PCP libraries and executables.

${PCP_PMDAS_DIR}

Performance Metric Domain Agents
(PMDAs), one directory per PMDA.

${PCP_VAR_DIR}/config

Configuration files for PCP tools, typically
with one directory per tool.

${PCP_DEMOS_DIR}

Demonstration data files and example
programs.

${PCP_LOG_DIR}

By default, diagnostic and trace log files
generated by PMCD and PMDAs. Also,
the PCP archive logs are managed in one
directory per logged host below here.

${PCP_VAR_DIR}/pmns

Files and scripts for the Performance Metrics
Name Space (PMNS).

Common Conventions and Arguments

Alternate Performance Metric Name Spaces
The Performance Metrics Name Space (PMNS) defines a mapping from a collection of human-readable
names for performance metrics (convenient to the user) into corresponding internal identifiers (convenient
for the underlying implementation).
The distributed PMNS used in PCP avoids most requirements for an alternate PMNS, because clients'
PMNS operations are supported at the Performance Metrics Collection Daemon (PMCD) or by means of
PMNS data in a PCP archive log. The distributed PMNS is the default, but alternates may be specified
using the -n namespace argument to the PCP tools. When a PMNS is maintained on a host, it is likely
to reside in the ${PCP_VAR_DIR}/pmns directory.

Time Duration and Control
The periodic nature of sampling performance metrics and refreshing the displays of the PCP tools makes
specification and control of the temporal domain a common operation. In the following sections, the
services and conventions for specifying time positions and intervals are described.

Performance Monitor Reporting Frequency and Duration
Many of the performance monitoring utilities have periodic reporting patterns. The -t interval
and -s samples options are used to control the sampling (reporting) interval, usually expressed as a
real number of seconds (interval), and the number of samples to be reported, respectively. In the
absence of the -s flag, the default behavior is for the performance monitoring utilities to run until they
are explicitly stopped.
The interval argument may also be expressed in terms of minutes, hours, or days, as described in
the PCPIntro(1) man page.

Time Window Options
The following options may be used with most PCP tools (typically when the source of the performance
metrics is a PCP archive log) to tailor the beginning and end points of a display, the sample origin, and
the sample time alignment to your convenience.
The -S, -T, -O and -A command line options are used by PCP applications to define a time window
of interest.
-S duration

The start option may be used to request that the display start at the
nominated time. By default, the first sample of performance data is
retrieved immediately in real-time mode, or coincides with the first
sample of data of the first archive in a set of PCP archive logs in archive
mode. For archive mode, the -S option may be used to specify a later
time for the start of sampling. By default, if duration is an integer, the
units are assumed to be seconds.
To specify an offset from the beginning of a set of PCP archives (in
archive mode) simply specify the offset as the duration. For example,
the following entry retrieves the first sample of data at exactly 30 minutes
from the beginning of a set of PCP archives.
-S 30min

Common Conventions and Arguments

To specify an offset from the end of a set of PCP archives, prefix the
duration with a minus sign. In this case, the first sample time precedes
the end of archived data by the given duration. For example, the
following entry retrieves the first sample exactly one hour preceding the
last sample in a set of PCP archives.
-S -1hour
To specify the calendar date and time (local time in the reporting
timezone) for the first sample, use the ctime(3) syntax preceded by
an “at” sign (@). For example, the following entry specifies the date and
time to be used.
-S '@ Mon Mar 4 13:07:47 2017'
Note that this format corresponds to the output format of the date
command for easy “cut and paste.” However, be sure to enclose the string
in quotes so it is preserved as a single argument for the PCP tool.
For more complete information on the date and time syntax, see the
PCPIntro(1) man page.
-T duration

The terminate option may be used to request that the display stop at the
time designated by duration. By default, the PCP tools keep sampling
performance data indefinitely (in real-time mode) or until the end of a set
of PCP archives (in archive mode). The -T option may be used to specify
an earlier time to terminate sampling.
The interpretation for the duration argument in a -T option is the
same as for the -S option, except for an unsigned time interval that is
interpreted as being an offset from the start of the time window as defined
by the default (now for real time, else start of archive set) or by a -S
option. For example, these options define a time window that spans 45
minutes, after an initial offset (or delay) of 1 hour:
-S 1hour -T 45mins

-O duration

By default, samples are fetched from the start time (see the description
of the -S option) to the terminate time (see the description of the -T
option). The offset -O option allows the specification of a time between
the start time and the terminate time where the tool should position its
initial sample time. This option is useful when initial attention is focused
at some point within a larger time window of interest, or when one PCP
tool wishes to launch another PCP tool with a common current point of
time within a shared time window.
The duration argument accepted by -O conforms to the same syntax
and semantics as the duration argument for -T. For example, these
options specify that the initial position should be the end of the time
window:
-O -0
This is most useful with the pmchart command to display the tail-end of
the history up to the end of the time window.

Common Conventions and Arguments

-A alignment

By default, performance data samples do not necessarily happen at any
natural unit of measured time. The -A switch may be used to force the
initial sample to be on the specified alignment. For example, these
three options specify alignment on seconds, half hours, and whole hours:
-A 1sec
-A 30min
-A 1hour
The -A option advances the time to achieve the desired alignment as soon
as possible after the start of the time window, whether this is the default
window, or one specified with some combination of -A and -O command
line options.

Obviously the time window may be overspecified by using multiple options from the set -t, -s, -S, -T,
-A, and -O. Similarly, the time window may shrink to nothing by injudicious choice of options.
In all cases, the parsing of these options applies heuristics guided by the principal of “least surprise”; the
time window is always well-defined (with the end never earlier than the start), but may shrink to nothing
in the extreme.

Timezone Options
All utilities that report time of day use the local timezone by default. The following timezone options are
available:
-z

Forces times to be reported in the timezone of the host that provided the
metric values (the PCP collector host). When used in conjunction with a and multiple archives, the convention is to use the timezone from the
first named archive.

-Z timezone

Sets the TZ variable to a timezone string, as defined in environ(7), for
example, -Z UTC for universal time.

PCP Environment Variables
When you are using PCP tools and utilities and are calling PCP library functions, a standard set of
defined environment variables are available in the ${PCP_DIR}/etc/pcp.conf file. These variables
are generally used to specify the location of various PCP pieces in the file system and may be loaded
into shell scripts by sourcing the ${PCP_DIR}/etc/pcp.env shell script. They may also be queried
by C, C++, perl and python programs using the pmGetConfig library function. If a variable is already
defined in the environment, the values in the pcp.conf file do not override those values; that is, the
values in pcp.conf serve only as installation defaults. For additional information, see the pcp.conf(5),
pcp.env(5), and pmGetConfig(3) man pages.
The following environment variables are recognized by PCP (these definitions are also available on the
PCPIntro(1) man page):
Many of the performance metrics exported
from PCP agents expect that counters increase
monotonically. Under some circumstances, one
value of a metric may be smaller than the
previously fetched value. This can happen when
a counter of finite precision overflows, when the
PCP agent has been reset or restarted, or when

PCP_COUNTER_WRAP

Common Conventions and Arguments

the PCP agent exports values from an underlying
instrumentation that is subject to asynchronous
discontinuity.
If set, the PCP_COUNTER_WRAP environment
variable indicates that all such cases of a
decreasing counter should be treated as a counter
overflow; and hence the values are assumed
to have wrapped once in the interval between
consecutive samples. Counter wrapping was the
default in versions before the PCP release 1.3.
PCP_STDERR

Specifies whether pmprintf() error messages are
sent to standard error, an pmconfirm dialog box,
or to a named file; see the pmprintf(3) man page.
Messages go to standard error if PCP_STDERR is
unset or set without a value. If this variable is set to
DISPLAY, then messages go to an pmconfirm
dialog box; see the pmconfirm(1) man page.
Otherwise, the value of PCP_STDERR is assumed
to be the name of an output file.

PMCD_CONNECT_TIMEOUT

When attempting to connect to a remote PMCD
on a system that is booting or at the other end of
a slow network link, some PMAPI routines could
potentially block for a long time until the remote
system responds. These routines abort and return
an error if the connection has not been established
after some specified interval has elapsed. The
default interval is 5 seconds. This may be modified
by setting this variable in the environment to a
larger number of seconds for the desired time out.
This is most useful in cases where the remote host
is at the end of a slow network, requiring longer
latencies to establish the connection correctly.

PMCD_PORT

This TCP/IP port is used by PMCD to create the
socket for incoming connections and requests. The
default is port number 44321, which you may
override by setting this variable to a different
port number. If a non-default port is in effect
when PMCD is started, then every monitoring
application connecting to that PMCD must also
have this variable set in its environment before
attempting a connection.

PMCD_LOCAL

This setting indicates that PMCD must only bind
to the loopback interface for incoming connections
and requests. In this mode, connections from
remote hosts are not possible.

PMCD_RECONNECT_TIMEOUT

When a monitor or client application
loses its connection to a PMCD, the
connection may be reestablished by calling
the pmReconnectContext(3) PMAPI function.

Common Conventions and Arguments

However, attempts to reconnect are controlled by
a back-off strategy to avoid flooding the network
with reconnection requests. By default, the backoff delays are 5, 10, 20, 40, and 80 seconds for
consecutive reconnection requests from a client
(the last delay is repeated for any further attempts
after the last delay in the list). Setting this
environment variable to a comma-separated list of
positive integers redefines the back-off delays. For
example, setting the delays to 1,2 will back off for
1 second, then back off every 2 seconds thereafter.
PMCD_REQUEST_TIMEOUT

For monitor or client applications connected to
PMCD, there is a possibility of the application
hanging on a request for performance metrics or
metadata or help text. These delays may become
severe if the system running PMCD crashes or the
network connection is lost or the network link is
very slow. By setting this environment variable
to a real number of seconds, requests to PMCD
timeout after the specified number of seconds.
The default behavior is to wait 10 seconds for a
response from every PMCD for all applications.

PMLOGGER_PORT

This environment variable may be used to change
the base TCP/IP port number used by pmlogger
to create the socket to which pmlc instances
try to connect. The default base port number
is 4330. If used, this variable should be set in
the environment before pmlogger is executed. If
pmlc and pmlogger are on different hosts, then
obviously PMLOGGER_PORT must be set to the
same value in both places.

PMLOGGER_LOCAL

This environment variable indicates that pmlogger
must only bind to the loopback interface for pmlc
connections and requests. In this mode, pmlc
connections from remote hosts are not possible. If
used, this variable should be set in the environment
before pmlogger is executed.

PMPROXY_PORT

This environment variable may be used to change
the base TCP/IP port number used by pmproxy to
create the socket to which proxied clients connect,
on their way to a distant pmcd.

PMPROXY_LOCAL

This setting indicates that pmproxy must
only bind to the loopback interface for
incoming connections and requests. In this mode,
connections from remote hosts are not possible.

Running PCP Tools through a Firewall
In some production environments, the Performance Co-Pilot (PCP) monitoring hosts are on one side of a
TCP/IP firewall, and the PCP collector hosts may be on the other side.

Common Conventions and Arguments

If the firewall service sits between the monitor and collector tools, the pmproxy service may be used to
perform both packet forwarding and DNS proxying through the firewall; see the pmproxy(1) man page.
Otherwise, it is necessary to arrange for packet forwarding to be enabled for those TCP/IP ports used by
PCP, namely 44321 (or the value of the PMCD_PORT environment variable) for connections to PMCD.

The pmproxy service
The pmproxy service allows PCP clients running on hosts located on one side of a firewall to monitor
remote hosts on the other side. The basic connection syntax is as follows, where tool is an arbitrary PCP
application, typically a monitoring tool:
pmprobe -h remotehost@proxyhost
This extended host specification syntax is part of a larger set of available extensions to the basic host
naming syntax - refer to the PCPIntro(1) man page for further details.

Transient Problems with Performance Metric
Values
Sometimes the values for a performance metric as reported by a PCP tool appear to be incorrect. This
is typically caused by transient conditions such as metric wraparound or time skew, described below.
These conditions result from design decisions that are biased in favor of lightweight protocols and minimal
resource demands for PCP components.
In all cases, these events are expected to occur infrequently, and should not persist beyond a few samples.

Performance Metric Wraparound
Performance metrics are usually expressed as numbers with finite precision. For metrics that are
cumulative counters of events or resource consumption, the value of the metric may occasionally overflow
the specified range and wraparound to zero.
Because the value of these counter metrics is computed from the rate of change with respect to the
previous sample, this may result in a transient condition where the rate of change is an unknown value.
If the PCP_COUNTER_WRAP environment variable is set, this condition is treated as an overflow, and
speculative rate calculations are made. In either case, the correct rate calculation for the metric returns
with the next sample.

Time Dilation and Time Skew
If a PMDA is tardy in returning results, or the PCP monitoring tool is connected to PMCD via a slow or
congested network, an error might be introduced in rate calculations due to a difference between the time
the metric was sampled and the time PMCD sends the result to the monitoring tool.
In practice, these errors are usually so small as to be insignificant, and the errors are self-correcting (not
cumulative) over consecutive samples.
A related problem may occur when the system time is not synchronized between multiple hosts, and the
time stamps for the results returned from PMCD reflect the skew in the system times. In this case, it is
recommended that NTP (network time protocol) be used to keep the system clocks on the collector systems
synchronized; for information on NTP refer to the ntpd(1) man page.

Chapter 4. Monitoring System
Performance
Table of Contents
The
The
The
The
The

pmstat Command .......................................................................................................
pmrep Command .......................................................................................................
pmval Command ........................................................................................................
pminfo Command .......................................................................................................
pmstore Command .....................................................................................................

35
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42

This chapter describes the performance monitoring tools available in Performance Co-Pilot (PCP). This
product provides a group of commands and tools for measuring system performance. Each tool is described
completely by its own man page. The man pages are accessible through the man command. For example,
the man page for the tool pmrep is viewed by entering the following command:
man pmrep
The following major sections are covered in this chapter:
• the section called “The pmstat Command”, discusses pmstat, a utility that provides a periodic one-line
summary of system performance.
• the section called “The pmrep Command”, discusses pmrep, a utility that shows the current values for
named performance metrics.
• the section called “The pmval Command”, describes pmval, a utility that displays performance metrics
in a textual format.
• the section called “The pminfo Command”, describes pminfo, a utility that displays information about
performance metrics.
• the section called “The pmstore Command”, describes the use of the pmstore utility to arbitrarily set
or reset selected performance metric values.
The following sections describe the various graphical and text-based PCP tools used to monitor local or
remote system performance.

The pmstat Command
The pmstat command provides a periodic, one-line summary of system performance. This command
is intended to monitor system performance at the highest level, after which other tools may be used for
examining subsystems to observe potential performance problems in greater detail. After entering the
pmstat command, you see output similar to the following, with successive lines appearing periodically:
pmstat
@ Thu Aug 15 09:25:56 2017
loadavg
memory
1 min
swpd
free
buff cache

swap
po

io
bo

system
in
cs

cpu
id

Monitoring System Performance

1.29 833960
1.51 833956
1.55 833956

5614m 144744 265824
5607m 144744 265712
5595m 145196 271908

0
0
0

0 1664
0 1664
14K 1056

13K
13K
13K

23K
24K
24K

6
5
7

7
7
7

81
83
74

sy
?
5
5
5
5
4
4

cpu
id
?
84
85
84
85
85
85

An additional line of output is added every five seconds. The -t interval option may be used to vary
the update interval (i.e. the sampling interval).
The output from pmstat is directed to standard output, and the columns in the report are interpreted as
follows:
loadavg

The 1-minute load average (runnable processes).

memory

The swpd column indicates average swap space used during the interval (all columns
reported in Kbytes unless otherwise indicated). The free column indicates average free
memory during the interval. The buff column indicates average buffer memory in use
during the interval. The cache column indicates average cached memory in use during
the interval.

swap

Reports the average number of pages that are paged-in (pi) and paged-out (po) per
second during the interval. It is normal for the paged-in values to be non-zero, but the
system is suffering memory stress if the paged-out values are non-zero over an extended
period.

The bi and bo columns indicate the average rate per second of block input and block
output operations respectfully, during the interval. These rates are independent of the I/
O block size. If the values become large, they are reported as thousands of operations
per second (K suffix) or millions of operations per second (M suffix).

system

Context switch rate (cs) and interrupt rate (in). Rates are expressed as average
operations per second during the interval. Note that the interrupt rate is normally at least
HZ (the clock interrupt rate, and kernel.all.hz metric) interrupts per second.

cpu

Percentage of CPU time spent executing user code (us), system and interrupt code (sy),
idle loop (id).

As with most PCP utilities, real-time metric, and archive logs are interchangeable.
For example, the following command uses a local system PCP archive log 20170731 and the timezone
of the host (smash) from which performance metrics in the archive were collected:
pmstat -a ${PCP_LOG_DIR}/pmlogger/smash/20170731 -t 2hour
Note: timezone set to local timezone of host "smash"
@ Wed Jul 31 10:00:00 2017
loadavg
memory
swap
io
1 min
swpd
free
buff cache
pi
po
bi
bo
3.90 24648 6234m 239176 2913m
?
?
?
?
1.72 24648 5273m 239320 2921m
0
0
4
86
3.12 24648 5194m 241428 2969m
0
0
0
84
1.97 24644 4945m 244004 3146m
0
0
0
84
3.82 24640 4908m 244116 3147m
0
0
0
83
3.38 24620 4860m 244116 3148m
0
0
0
83
2.89 24600 4804m 244120 3149m
0
0
0
83
pmFetch: End of PCP archive log

-A 1hour -z

system
in
cs
?
?
11K 19K
10K 19K
10K 19K
10K 18K
10K 18K
10K 18K

For complete information on pmstat usage and command line options, see the pmstat(1) man page.

us
?
5
5
5
5
5
5

Monitoring System Performance

The pmrep Command
The pmrep command displays performance metrics in ASCII tables, suitable for export into databases
or report generators. It is a flexible command. For example, the following command provides continuous
memory statistics on a host named surf:
pmrep -p -h surf kernel.all.load kernel.all.pswitch
k.a.load k.a.load k.a.load k.a.pswitch
1 minute 5 minute 15 minut
count/s
10:41:37
0.160
0.170
0.180
N/A
10:41:38
0.160
0.170
0.180
1427.016
10:41:39
0.160
0.170
0.180
2129.040
10:41:40
0.160
0.170
0.180
5335.163
10:41:41
0.160
0.170
0.180
723.125
10:41:42
0.140
0.160
0.180
591.859
See the pmrep(1) man page for more information.

The pmval Command
The pmval command dumps the current values for the named performance metrics. For example, the
following command reports the value of performance metric proc.nprocs once per second (by default),
and produces output similar to this:
pmval proc.nprocs
metric:
proc.nprocs
host:
localhost
semantics: instantaneous value
units:
none
samples:
all
interval: 1.00 sec
81
81
82
81
In this example, the number of running processes was reported once per second.
Where the semantics of the underlying performance metrics indicate that it would be sensible, pmval
reports the rate of change or resource utilization.
For example, the following command reports idle processor utilization for each of four CPUs on the remote
host dove, each five seconds apart, producing output of this form:
pmval -h dove -t 5sec -s 4 kernel.percpu.cpu.idle
metric:
kernel.percpu.cpu.idle
host:
dove
semantics: cumulative counter (converting to rate)
units:
millisec (converting to time utilization)
samples:
4
interval: 5.00 sec
cpu:1.1.0.a cpu:1.1.0.c cpu:1.1.1.a cpu:1.1.1.c

Monitoring System Performance

1.000
1.000
0.8989
0.9568

0.9998
0.9998
0.9987
0.9998

0.9998
0.9998
0.9997
0.9996

1.000
1.000
0.9995
1.000

Similarly, the following command reports disk I/O read rate every minute for just the disk /dev/disk1,
and produces output similar to the following:
pmval -t 1min -i disk1 disk.dev.read
metric:
disk.dev.read
host:
localhost
semantics: cumulative counter (converting to rate)
units:
count (converting to count / sec)
samples:
indefinite
interval: 60.00 sec
disk1
33.67
48.71
52.33
11.33
2.333
The -r flag may be used to suppress the rate calculation (for metrics with counter semantics) and display
the raw values of the metrics.
In the example below, manipulation of the time within the archive is achieved by the exchange of time
control messages between pmval and pmtime.
pmval -g -a ${PCP_LOG_DIR}/pmlogger/myserver/20170731 kernel.all.load
The pmval command is documented by the pmval(1) man page, and annotated examples of the use of
pmval can be found in the PCP Tutorials and Case Studies companion document.

The pminfo Command
The pminfo command displays various types of information about performance metrics available through
the Performance Co-Pilot (PCP) facilities.
The -T option is extremely useful; it provides help text about performance metrics:
pminfo -T mem.util.cached
mem.util.cached
Help:
Memory used by the page cache, including buffered file data.
This is in-memory cache for files read from the disk (the pagecache)
but doesn't include SwapCached.
The -t option displays the one-line help text associated with the selected metrics. The -T option prints
more verbose help text.
Without any options, pminfo verifies that the specified metrics exist in the namespace, and echoes those
names. Metrics may be specified as arguments to pminfo using their full metric names. For example, this
command returns the following response:
pminfo hinv.ncpu network.interface.total.bytes

Monitoring System Performance

hinv.ncpu
network.interface.total.bytes
A group of related metrics in the namespace may also be specified. For example, to list all of the hinv
metrics you would use this command:
pminfo hinv
hinv.physmem
hinv.pagesize
hinv.ncpu
hinv.ndisk
hinv.nfilesys
hinv.ninterface
hinv.nnode
hinv.machine
hinv.map.scsi
hinv.map.cpu_num
hinv.map.cpu_node
hinv.map.lvname
hinv.cpu.clock
hinv.cpu.vendor
hinv.cpu.model
hinv.cpu.stepping
hinv.cpu.cache
hinv.cpu.bogomips
If no metrics are specified, pminfo displays the entire collection of metrics. This can be useful for searching
for metrics, when only part of the full name is known. For example, this command returns the following
response:
pminfo | grep nfs
nfs.client.calls
nfs.client.reqs
nfs.server.calls
nfs.server.reqs
nfs3.client.calls
nfs3.client.reqs
nfs3.server.calls
nfs3.server.reqs
nfs4.client.calls
nfs4.client.reqs
nfs4.server.calls
nfs4.server.reqs
The -d option causes pminfo to display descriptive information about metrics (refer to the
pmLookupDesc(3) man page for an explanation of this metadata information). The following command
and response show use of the -d option:
pminfo -d proc.nprocs disk.dev.read filesys.free
proc.nprocs
Data Type: 32-bit unsigned int InDom: PM_INDOM_NULL 0xffffffff
Semantics: instant Units: none
disk.dev.read
Data Type: 32-bit unsigned int

InDom: 60.1 0xf000001

Monitoring System Performance

Semantics: counter

Units: count

filesys.free
Data Type: 64-bit unsigned int InDom: 60.5 0xf000005
Semantics: instant Units: Kbyte
The -l option causes pminfo to display labels about metrics (refer to the pmLookupLabels(3) man page
for an explanation of this metadata information). If the metric has an instance domain, the labels associated
with each instance of the metric is printed. The following command and response show use of the -l
option:

pminfo -l -h shard kernel.pernode.cpu.user
kernel.percpu.cpu.sys
inst [0 or "cpu0"] labels {"agent":"linux","cpu":0,"device_type":"cpu","domainn
inst [1 or "cpu1"] labels {"agent":"linux","cpu":1,"device_type":"cpu","domainn
inst [2 or "cpu2"] labels {"agent":"linux","cpu":2,"device_type":"cpu","domainn
inst [3 or "cpu3"] labels {"agent":"linux","cpu":3,"device_type":"cpu","domainn
inst [4 or "cpu4"] labels {"agent":"linux","cpu":4,"device_type":"cpu","domainn
inst [5 or "cpu5"] labels {"agent":"linux","cpu":5,"device_type":"cpu","domainn
inst [6 or "cpu6"] labels {"agent":"linux","cpu":6,"device_type":"cpu","domainn
inst [7 or "cpu7"] labels {"agent":"linux","cpu":7,"device_type":"cpu","domainn
The -f option to pminfo forces the current value of each named metric to be fetched and printed. In the
example below, all metrics in the group hinv are selected:
pminfo -f hinv
hinv.physmem
value 15701
hinv.pagesize
value 16384
hinv.ncpu
value 4
hinv.ndisk
value 6
hinv.nfilesys
value 2
hinv.ninterface
value 8
hinv.nnode
value 2
hinv.machine
value "IP35"
hinv.map.cpu_num
inst [0 or "cpu:1.1.0.a"]
inst [1 or "cpu:1.1.0.c"]
inst [2 or "cpu:1.1.1.a"]
inst [3 or "cpu:1.1.1.c"]

value
value
value
value

0
1
2
3

Monitoring System Performance

hinv.map.cpu_node
inst [0 or "node:1.1.0"] value "/dev/hw/module/001c01/slab/0/node"
inst [1 or "node:1.1.1"] value "/dev/hw/module/001c01/slab/1/node"
hinv.cpu.clock
inst [0 or
inst [1 or
inst [2 or
inst [3 or

"cpu:1.1.0.a"]
"cpu:1.1.0.c"]
"cpu:1.1.1.a"]
"cpu:1.1.1.c"]

value
value
value
value

800
800
800
800

hinv.cpu.vendor
inst [0 or "cpu:1.1.0.a"]
inst [1 or "cpu:1.1.0.c"]
inst [2 or "cpu:1.1.1.a"]
inst [3 or "cpu:1.1.1.c"]

value
value
value
value

"GenuineIntel"
"GenuineIntel"
"GenuineIntel"
"GenuineIntel"

hinv.cpu.model
inst [0 or
inst [1 or
inst [2 or
inst [3 or

"cpu:1.1.0.a"]
"cpu:1.1.0.c"]
"cpu:1.1.1.a"]
"cpu:1.1.1.c"]

value
value
value
value

"0"
"0"
"0"
"0"

hinv.cpu.stepping
inst [0 or "cpu:1.1.0.a"]
inst [1 or "cpu:1.1.0.c"]
inst [2 or "cpu:1.1.1.a"]
inst [3 or "cpu:1.1.1.c"]

value
value
value
value

"6"
"6"
"6"
"6"

hinv.cpu.cache
inst [0 or
inst [1 or
inst [2 or
inst [3 or

"cpu:1.1.0.a"]
"cpu:1.1.0.c"]
"cpu:1.1.1.a"]
"cpu:1.1.1.c"]

value
value
value
value

0
0
0
0

hinv.cpu.bogomips
inst [0 or "cpu:1.1.0.a"]
inst [1 or "cpu:1.1.0.c"]
inst [2 or "cpu:1.1.1.a"]
inst [3 or "cpu:1.1.1.c"]

value
value
value
value

1195.37
1195.37
1195.37
1195.37

The -h option directs pminfo to retrieve information from the specified host. If the metric has an instance
domain, the value associated with each instance of the metric is printed:
pminfo -h dove -f filesys.mountdir
filesys.mountdir
inst [0 or "/dev/xscsi/pci00.01.0/target81/lun0/part3"] value "/"
inst [1 or "/dev/xscsi/pci00.01.0/target81/lun0/part1"] value "/boot/efi"
The -m option prints the Performance Metric Identifiers (PMIDs) of the selected metrics. This is useful
for finding out which PMDA supplies the metric. For example, the output below identifies the PMDA
supporting domain 4 (the leftmost part of the PMID) as the one supplying information for the metric
environ.extrema.mintemp:
pminfo -m environ.extrema.mintemp

Monitoring System Performance

environ.extrema.mintemp PMID: 4.0.3
The -v option verifies that metric definitions in the PMNS correspond with supported metrics, and checks
that a value is available for the metric. Descriptions and values are fetched, but not printed. Only errors
are reported.
Complete information on the pminfo command is found in the pminfo(1) man page. There are further
examples of the use of pminfo in the PCP Tutorials and Case Studies.

The pmstore Command
From time to time you may wish to change the value of a particular metric. Some metrics are counters that
may need to be reset, and some are simply control variables for agents that collect performance metrics.
When you need to change the value of a metric for any reason, the command to use is pmstore.

Note
For obvious reasons, the ability to arbitrarily change the value of a performance metric is not
supported. Rather, PCP collectors selectively allow some metrics to be modified in a very
controlled fashion.
The basic syntax of the command is as follows:
pmstore metricname value
There are also command line flags to further specify the action. For example, the -i option restricts the
change to one or more instances of the performance metric.
The value may be in one of several forms, according to the following rules:
1. If the metric has an integer type, then value should consist of an optional leading hyphen, followed
either by decimal digits or “0x” and some hexadecimal digits; “0X” is also acceptable instead of “0x.”
2. If the metric has a floating point type, then value should be in the form of an integer (described above),
a fixed point number, or a number in scientific notation.
3. If the metric has a string type, then value is interpreted as a literal string of ASCII characters.
4. If the metric has an aggregate type, then an attempt is made to interpret value as an integer, a floating
point number, or a string. In the first two cases, the minimal word length encoding is used; for example,
“123” would be interpreted as a four-byte aggregate, and “0x100000000” would be interpreted as an
eight-byte aggregate.
The following example illustrates the use of pmstore to enable performance metrics collection in the
txmon PMDA (see ${PCP_PMDAS_DIR}/txmon for the source code of the txmon PMDA). When the
metric txmon.control.level has the value 0, no performance metrics are collected. Values greater
than 0 enable progressively more verbose instrumentation.
pminfo -f txmon.count
txmon.count
No value(s) available!
pmstore txmon.control.level 1
txmon.control.level old value=0 new value=1
pminfo -f txmon.count
txmon.count

Monitoring System Performance

inst
inst
inst
inst
inst
inst
inst

[0
[1
[2
[3
[4
[5
[6

or
or
or
or
or
or
or

"ord-entry"] value 23
"ord-enq"] value 11
"ord-ship"] value 10
"part-recv"] value 3
"part-enq"] value 2
"part-used"] value 1
"b-o-m"] value 0

For complete information on pmstore usage and syntax, see the pmstore(1) man page.

Chapter 5. Performance Metrics
Inference Engine
Table of Contents
Introduction to pmie ..........................................................................................................
Basic pmie Usage .............................................................................................................
pmie use of PCP services ...........................................................................................
Simple pmie Usage ...................................................................................................
Complex pmie Examples ...........................................................................................
Specification Language for pmie .........................................................................................
Basic pmie Syntax ....................................................................................................
Setting Evaluation Frequency ......................................................................................
pmie Metric Expressions ............................................................................................
pmie Rate Conversion ...............................................................................................
pmie Arithmetic Expressions ......................................................................................
pmie Logical Expressions ...........................................................................................
pmie Rule Expressions ..............................................................................................
pmie Intrinsic Operators .............................................................................................
pmie Examples .................................................................................................................
Developing and Debugging pmie Rules ................................................................................
Caveats and Notes on pmie ................................................................................................
Performance Metrics Wraparound ................................................................................
pmie Sample Intervals ...............................................................................................
pmie Instance Names ................................................................................................
pmie Error Detection .................................................................................................
Creating pmie Rules with pmieconf .....................................................................................
Management of pmie Processes ...........................................................................................
Add a pmie crontab Entry .........................................................................................
Global Files and Directories ........................................................................................
pmie Instances and Their Progress ...............................................................................

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47
48
48
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52
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57
59
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62
63
63
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63
64
66
67
68
68

The Performance Metrics Inference Engine (pmie) is a tool that provides automated monitoring of, and
reasoning about, system performance within the Performance Co-Pilot (PCP) framework.
The major sections in this chapter are as follows:
• the section called “Introduction to pmie”, provides an introduction to the concepts and design of pmie.
• the section called “Basic pmie Usage”, describes the basic syntax and usage of pmie.
• the section called “Specification Language for pmie”, discusses the complete pmie rule specification
language.
• the section called “pmie Examples”, provides an example, covering several common performance
scenarios.
• the section called “Developing and Debugging pmie Rules”, presents some tips and techniques for pmie
rule development.
• the section called “Caveats and Notes on pmie”, presents some important information on using pmie.

Performance Metrics Inference Engine

• the section called “Creating pmie Rules with pmieconf”, describes how to use the pmieconf command
to generate pmie rules.
• the section called “Management of pmie Processes”, provides support for running pmie as a daemon.

Introduction to pmie
Automated reasoning within Performance Co-Pilot (PCP) is provided by the Performance Metrics
Inference Engine, (pmie), which is an applied artificial intelligence application.
The pmie tool accepts expressions describing adverse performance scenarios, and periodically evaluates
these against streams of performance metric values from one or more sources. When an expression is
found to be true, pmie is able to execute arbitrary actions to alert or notify the system administrator of
the occurrence of an adverse performance scenario. These facilities are very general, and are designed to
accommodate the automated execution of a mixture of generic and site-specific performance monitoring
and control functions.
The stream of performance metrics to be evaluated may be from one or more hosts, or from one or more
PCP archive logs. In the latter case, pmie may be used to retrospectively identify adverse performance
conditions.
Using pmie, you can filter, interpret, and reason about the large volume of performance data made available
from PCP collector systems or PCP archives.
Typical pmie uses include the following:
• Automated real-time monitoring of a host, a set of hosts, or client-server pairs of hosts to raise
operational alarms when poor performance is detected in a production environment
• Nightly processing of archive logs to detect and report performance regressions, or quantify quality of
service for service level agreements or management reports, or produce advance warning of pending
performance problems
• Strategic performance management, for example, detection of slightly abnormal to chronic system
behavior, trend analysis, and capacity planning
The pmie expressions are described in a language with expressive power and operational flexibility. It
includes the following operators and functions:
• Generalized predicate-action pairs, where a predicate is a logical expression over the available
performance metrics, and the action is arbitrary. Predefined actions include the following:
• Launch a visible alarm with pmconfirm; see the pmconfirm(1) man page.
• Post an entry to the system log file; see the syslog(3) man page.
• Post an entry to the PCP noticeboard file ${PCP_LOG_DIR}/NOTICES; see the pmpost(1) man
page.
• Execute a shell command or script, for example, to send e-mail, initiate a pager call, warn the help
desk, and so on.
• Echo a message on standard output; useful for scripts that generate reports from retrospective
processing of PCP archive logs.
• Arithmetic and logical expressions in a C-like syntax.

Performance Metrics Inference Engine

• Expression groups may have an independent evaluation frequency, to support both short-term and longterm monitoring.
• Canonical scale and rate conversion of performance metric values to provide sensible expression
evaluation.
• Aggregation functions of sum, avg, min, and max, that may be applied to collections of performance
metrics values clustered over multiple hosts, or multiple instances, or multiple consecutive samples in
time.
• Universal and existential quantification, to handle expressions of the form “for every....” and “at least
one...”.
• Percentile aggregation to handle statistical outliers, such as “for at least 80% of the last 20 samples, ...”.
• Macro processing to expedite repeated use of common subexpressions or specification components.
• Transparent operation against either live-feeds of performance metric values from PMCD on one or
more hosts, or against PCP archive logs of previously accumulated performance metric values.
The power of pmie may be harnessed to automate the most common of the deterministic system
management functions that are responses to changes in system performance. For example, disable a batch
stream if the DBMS transaction commit response time at the ninetieth percentile goes over two seconds,
or stop accepting uploads and send e-mail to the sysadmin alias if free space in a storage system falls
below five percent.
Moreover, the power of pmie can be directed towards the exceptional and sporadic performance problems.
For example, if a network packet storm is expected, enable IP header tracing for ten seconds, and send
e-mail to advise that data has been collected and is awaiting analysis. Or, if production batch throughput
falls below 50 jobs per minute, activate a pager to the systems administrator on duty.
Obviously, pmie customization is required to produce meaningful filtering and actions in each production
environment. The pmieconf tool provides a convenient customization method, allowing the user to
generate parameterized pmie rules for some of the more common performance scenarios.

Basic pmie Usage
This section presents and explains some basic examples of pmie usage. The pmie tool accepts the common
PCP command line arguments, as described in Chapter 3, Common Conventions and Arguments. In
addition, pmie accepts the following command line arguments:
d

Enables interactive debug mode.

Verbose mode: expression values are displayed.

Verbose mode: annotated expression values are displayed.

When-verbose mode: when a condition is true, the satisfying expression bindings are displayed.

One of the most basic invocations of this tool is this form:
pmie filename

Performance Metrics Inference Engine

In this form, the expressions to be evaluated are read from filename. In the absence of a given
filename, expressions are read from standard input, which may be your system keyboard.

pmie use of PCP services
Before you use pmie, it is strongly recommended that you familiarize yourself with the concepts from the
the section called “Conceptual Foundations”. The discussion in this section serves as a very brief review
of these concepts.
PCP makes available thousands of performance metrics that you can use when formulating expressions
for pmie to evaluate. If you want to find out which metrics are currently available on your system, use
this command:
pminfo
Use the pmie command line arguments to find out more about a particular metric. In Example 5.1, “pmie
with the -f Option”, to fetch new metric values from host dove, you use the -f flag:

Example 5.1. pmie with the -f Option
pminfo -f -h dove disk.dev.total
This produces the following response:
disk.dev.total
inst [0 or "xscsi/pci00.01.0/target81/lun0/disc"] value 131233
inst [4 or "xscsi/pci00.01.0/target82/lun0/disc"] value 4
inst [8 or "xscsi/pci00.01.0/target83/lun0/disc"] value 4
inst [12 or "xscsi/pci00.01.0/target84/lun0/disc"] value 4
inst [16 or "xscsi/pci00.01.0/target85/lun0/disc"] value 4
inst [18 or "xscsi/pci00.01.0/target86/lun0/disc"] value 4
This reveals that on the host dove, the metric disk.dev.total has six instances, one for each disk
on the system.
Use the following command to request help text (specified with the -T flag) to provide more information
about performance metrics:
pminfo -T network.interface.in.packets
The metadata associated with a performance metric is used by pmie to determine how the value should be
interpreted. You can examine the descriptor that encodes the metadata by using the -d flag for pminfo,
as shown in Example 5.2, “pmie with the -d and -h Options”:

Example 5.2. pmie with the -d and -h Options
pminfo -d -h somehost mem.util.cached kernel.percpu.cpu.user
In response, you see output similar to this:
mem.util.cached
Data Type: 64-bit unsigned int InDom: PM_INDOM_NULL 0xffffffff
Semantics: instant Units: Kbyte
kernel.percpu.cpu.user
Data Type: 64-bit unsigned int

InDom: 60.0 0xf000000

Performance Metrics Inference Engine

Semantics: counter

Units: millisec

Note
A cumulative counter such as kernel.percpu.cpu.user is automatically converted by
pmie into a rate (measured in events per second, or count/second), while instantaneous values
such as mem.util.cached are not subjected to rate conversion. Metrics with an instance
domain (InDom in the pminfo output) of PM_INDOM_NULL are singular and always produce
one value per source. However, a metric like kernel.percpu.cpu.user has an instance
domain, and may produce multiple values per source (in this case, it is one value for each
configured CPU).

Simple pmie Usage
Example 5.3, “pmie with the -v Option” directs the inference engine to evaluate and print values
(specified with the -v flag) for a single performance metric (the simplest possible expression), in this case
disk.dev.total, collected from the local PMCD:

Example 5.3. pmie with the -v Option
pmie -v
iops = disk.dev.total;
Ctrl+D
iops:
?
?
iops:
14.4
0
iops:
25.9 0.112
iops:
12.2
0
iops:
12.3
64.1
iops: 8.594 52.17
iops: 2.001 71.64
On this system, there are two disk spindles, hence two values of the expression iops per sample. Notice
that the values for the first sample are unknown (represented by the question marks [?] in the first line
of output), because rates can be computed only when at least two samples are available. The subsequent
samples are produced every ten seconds by default. The second sample reports that during the preceding
ten seconds there was an average of 14.4 transfers per second on one disk and no transfers on the other disk.
Rates are computed using time stamps delivered by PMCD. Due to unavoidable inaccuracy in the actual
sampling time (the sample interval is not exactly 10 seconds), you may see more decimal places in values
than you expect. Notice, however, that these errors do not accumulate but cancel each other out over
subsequent samples.
In Example 5.3, “pmie with the -v Option”, the expression to be evaluated was entered using the keyboard,
followed by the end-of-file character [Ctrl+D]. Usually, it is more convenient to enter expressions into a
file (for example, myrules) and ask pmie to read the file. Use this command syntax:
pmie -v myrules
Please refer to the pmie(1) man page for a complete description of pmie command line options.

Complex pmie Examples
This section illustrates more complex pmie expressions of the specification language. the section called
“Specification Language for pmie”, provides a complete description of the pmie specification language.

Performance Metrics Inference Engine

The following arithmetic expression computes the percentage of write operations over the total number
of disk transfers.
(disk.all.write / disk.all.total) * 100;
The disk.all metrics are singular, so this expression produces exactly one value per sample,
independent of the number of disk devices.

Note
If there is no disk activity, disk.all.total will be zero and pmie evaluates this expression
to be not a number. When -v is used, any such values are displayed as question marks.
The following logical expression has the value true or false for each disk:
disk.dev.total > 10 &&
disk.dev.write > disk.dev.read;
The value is true if the number of writes exceeds the number of reads, and if there is significant disk activity
(more than 10 transfers per second). Example 5.4, “Printed pmie Output” demonstrates a simple action:

Example 5.4. Printed pmie Output
some_inst disk.dev.total > 60
-> print "[%i] high disk i/o";
This prints a message to the standard output whenever the total number of transfers for some disk
(some_inst) exceeds 60 transfers per second. The %i (instance) in the message is replaced with the
name(s) of the disk(s) that caused the logical expression to be true.
Using pmie to evaluate the above expressions every 3 seconds, you see output similar to Example 5.5,
“Labelled pmie Output”. Notice the introduction of labels for each pmie expression.

Example 5.5. Labelled pmie Output
pmie -v -t 3sec
pct_wrt = (disk.all.write / disk.all.total) * 100;
busy_wrt = disk.dev.total > 10 &&
disk.dev.write > disk.dev.read;
busy = some_inst disk.dev.total > 60
-> print "[%i] high disk i/o ";
Ctrl+D
pct_wrt:
?
busy_wrt:
?
?
busy:
?
pct_wrt:
busy_wrt:
busy:

18.43
false
false

Mon Aug 5
pct_wrt:
busy_wrt:
busy:

14:56:08 2012: [disk2] high disk i/o
10.83
false false
true

false

Performance Metrics Inference Engine

pct_wrt:
busy_wrt:
busy:

19.85
true
false

false

pct_wrt:
busy_wrt:
busy:

?
false
false

false

Mon Aug 5 14:56:17 2012: [disk1] high disk i/o [disk2] high disk i/o
pct_wrt:
14.8
busy_wrt: false false
busy:
true
The first sample contains unknowns, since all expressions depend on computing rates. Also notice that the
expression pct_wrt may have an undefined value whenever all disks are idle, as the denominator of the
expression is zero. If one or more disks is busy, the expression busy is true, and the message from the
print in the action part of the rule appears (before the -v values).

Specification Language for pmie
This section describes the complete syntax of the pmie specification language, as well as macro facilities
and the issue of sampling and evaluation frequency. The reader with a preference for learning by example
may choose to skip this section and go straight to the examples in the section called “pmie Examples”.
Complex expressions are built up recursively from simple elements:
1. Performance metric values are obtained from PMCD for real-time sources, otherwise from PCP archive
logs.
2. Metrics values may be combined using arithmetic operators to produce arithmetic expressions.
3. Arithmetic expressions may be compared using relational operators to produce logical expressions.
4. Logical expressions may be combined using Boolean operators, including powerful quantifiers.
5. Aggregation operators may be used to compute summary expressions, for either arithmetic or logical
operands.
6. The final logical expression may be used to initiate a sequence of actions.

Basic pmie Syntax
The pmie rule specification language supports a number of basic syntactic elements.

Lexical Elements
All pmie expressions are composed of the following lexical elements:
Identifier

Begins with an alphabetic character (either upper or lowercase),
followed by zero or more letters, the numeric digits, and the
special characters period (.) and underscore (_), as shown in the
following example:
x, disk.dev.total and my_stuff

Performance Metrics Inference Engine

As a special case, an arbitrary sequence of letters enclosed by
apostrophes (') is also interpreted as an identifier; for
example:
'vms$slow_response'
Keyword

The aggregate operators, units, and predefined actions are
represented by keywords; for example, some_inst, print,
and hour.

Numeric constant

Any likely representation of a decimal integer or floating point
number; for example, 124, 0.05, and -45.67

String constant

An arbitrary sequence of characters, enclosed by double quotation
marks ("x").

Within quotes of any sort, the backslash (\) may be used as an escape character as shown in the following
example:
"A \"gentle\" reminder"

Comments
Comments may be embedded anywhere in the source, in either of these forms:
/* text */

Comment, optionally spanning multiple lines, with no nesting of comments.

// text

Comment from here to the end of the line.

Macros
When they are fully specified, expressions in pmie tend to be verbose and repetitive. The use of macros can
reduce repetition and improve readability and modularity. Any statement of the following form associates
the macro name identifier with the given string constant.
identifier = "string";
Any subsequent occurrence of the macro name identifier is replaced by the string most recently
associated with a macro definition for identifier.
$identifier
For example, start with the following macro definition:
disk = "disk.all";
You can then use the following syntax:
pct_wrt = ($disk.write / $disk.total) * 100;

Note
Macro expansion is performed before syntactic parsing; so macros may only be assigned constant
string values.

Performance Metrics Inference Engine

Units
The inference engine converts all numeric values to canonical units (seconds for time, bytes for space, and
events for count). To avoid surprises, you are encouraged to specify the units for numeric constants. If
units are specified, they are checked for dimension compatibility against the metadata for the associated
performance metrics.
The syntax for a units specification is a sequence of one or more of the following keywords separated
by either a space or a slash (/), to denote per: byte, KByte, MByte, GByte, TByte, nsec,
nanosecond, usec, microsecond, msec, millisecond, sec, second, min, minute, hour,
count, Kcount, Mcount, Gcount, or Tcount. Plural forms are also accepted.
The following are examples of units usage:
disk.dev.blktotal > 1 Mbyte / second;
mem.util.cached < 500 Kbyte;

Note
If you do not specify the units for numeric constants, it is assumed that the constant is in the
canonical units of seconds for time, bytes for space, and events for count, and the dimensionality
of the constant is assumed to be correct. Thus, in the following expression, the 500 is interpreted
as 500 bytes.
mem.util.cached < 500

Setting Evaluation Frequency
The identifier name delta is reserved to denote the interval of time between consecutive evaluations of
one or more expressions. Set delta as follows:
delta = number [units];
If present, units must be one of the time units described in the preceding section. If absent, units
are assumed to be seconds. For example, the following expression has the effect that any subsequent
expressions (up to the next expression that assigns a value to delta) are scheduled for evaluation at a
fixed frequency, once every five minutes.
delta = 5 min;
The default value for delta may be specified using the -t command line option; otherwise delta is
initially set to be 10 seconds.

pmie Metric Expressions
The performance metrics namespace (PMNS) provides a means of naming performance metrics, for
example, disk.dev.read. PCP allows an application to retrieve one or more values for a performance
metric from a designated source (a collector host running PMCD, or a set of PCP archive logs). To specify
a single value for some performance metric requires the metric name to be associated with all three of
the following:
• A particular host (or source of metrics values)
• A particular instance (for metrics with multiple values)

Performance Metrics Inference Engine

• A sample time
The permissible values for hosts are the range of valid hostnames as provided by Internet naming
conventions.
The names for instances are provided by the Performance Metrics Domain Agents (PMDA) for the instance
domain associated with the chosen performance metric.
The sample time specification is defined as the set of natural numbers 0, 1, 2, and so on. A number refers
to one of a sequence of sampling events, from the current sample 0 to its predecessor 1, whose predecessor
was 2, and so on. This scheme is illustrated by the time line shown in Figure 5.1, “Sampling Time Line”.

Figure 5.1. Sampling Time Line

Each sample point is assumed to be separated from its predecessor by a constant amount of real time, the
delta. The most recent sample point is always zero. The value of delta may vary from one expression
to the next, but is fixed for each expression; for more information on the sampling interval, see the section
called “Setting Evaluation Frequency”.
For pmie, a metrics expression is the name of a metric, optionally qualified by a host, instance and sample
time specification. Special characters introduce the qualifiers: colon (:) for hosts, hash or pound sign (#)
for instances, and at (@) for sample times. The following expression refers to the previous value (@1) of
the counter for the disk read operations associated with the disk instance #disk1 on the host moomba.
disk.dev.read :moomba #disk1 @1
In fact, this expression defines a point in the three-dimensional (3D) parameter space of {host} x
{instance} x {sample time} as shown in Figure 5.2, “Three-Dimensional Parameter Space”.

Figure 5.2. Three-Dimensional Parameter Space

A metric expression may also identify sets of values corresponding to one-, two-, or three-dimensional
slices of this space, according to the following rules:
1. A metric expression consists of a PCP metric name, followed by optional host specifications, followed
by optional instance specifications, and finally, optional sample time specifications.
2. A host specification consists of one or more host names, each prefixed by a colon (:). For example:
:indy :far.away.domain.com :localhost
3. A missing host specification implies the default pmie source of metrics, as defined by a -h option on
the command line, or the first named archive in an -a option on the command line, or PMCD on the
local host.
4. An instance specification consists of one or more instance names, each prefixed by a hash or pound
(#) sign. For example: #eth0 #eth2
Recall that you can discover the instance names for a particular metric, using the pminfo command.
See the section called “pmie use of PCP services”.
Within the pmie grammar, an instance name is an identifier. If the instance name contains characters
other than alphanumeric characters, enclose the instance name in single quotes; for example, #'/
boot' #'/usr'

Performance Metrics Inference Engine

5. A missing instance specification implies all instances for the associated performance metric from each
associated pmie source of metrics.
6. A sample time specification consists of either a single time or a range of times. A single time is
represented as an at (@) followed by a natural number. A range of times is an at (@), followed by a
natural number, followed by two periods (..) followed by a second natural number. The ordering of
the end points in a range is immaterial. For example, @0..9 specifies the last 10 sample times.
7. A missing sample time specification implies the most recent sample time.
The following metric expression refers to a three-dimensional set of values, with two hosts in one
dimension, five sample times in another, and the number of instances in the third dimension being
determined by the number of configured disk spindles on the two hosts.
disk.dev.read :foo :bar @0..4

pmie Rate Conversion
Many of the metrics delivered by PCP are cumulative counters. Consider the following metric:
disk.all.total
A single value for this metric tells you only that a certain number of disk I/O operations have occurred
since boot time, and that information may be invalid if the counter has exceeded its 32-bit range and
wrapped. You need at least two values, sampled at known times, to compute the recent rate at which the
I/O operations are being executed. The required syntax would be this:
(disk.all.total @0 - disk.all.total @1) / delta
The accuracy of delta as a measure of actual inter-sample delay is an issue. pmie requests samples, at
intervals of approximately delta, while the results exported from PMCD are time stamped with the highresolution system clock time when the samples were extracted. For these reasons, a built-in and implicit
rate conversion using accurate time stamps is provided by pmie for performance metrics that have counter
semantics. For example, the following expression is unconditionally converted to a rate by pmie.
disk.all.total

pmie Arithmetic Expressions
Within pmie, simple arithmetic expressions are constructed from metrics expressions (see the section
called “pmie Metric Expressions”) and numeric constants, using all of the arithmetic operators and
precedence rules of the C programming language.
All pmie arithmetic is performed in double precision.
the section called “pmie Intrinsic Operators”, describes additional operators that may be used for aggregate
operations to reduce the dimensionality of an arithmetic expression.

pmie Logical Expressions
A number of logical expression types are supported:
• Logical constants
• Relational expressions

Performance Metrics Inference Engine

• Boolean expressions
• Quantification operators

Logical Constants
Like in the C programming language, pmie interprets an arithmetic value of zero to be false, and all other
arithmetic values are considered true.

Relational Expressions
Relational expressions are the simplest form of logical expression, in which values may be derived
from arithmetic expressions using pmie relational operators. For example, the following is a relational
expression that is true or false, depending on the aggregate total of disk read operations per second being
greater than 50.
disk.all.read > 50 count/sec
All of the relational logical operators and precedence rules of the C programming language are supported
in pmie.
As described in the section called “pmie Metric Expressions”, arithmetic expressions in pmie may assume
set values. The relational operators are also required to take constant, singleton, and set-valued expressions
as arguments. The result has the same dimensionality as the operands. Suppose the rule in Example 5.6,
“Relational Expressions ” is given:

Example 5.6. Relational Expressions
hosts = ":gonzo";
intfs = "#eth0 #eth2";
all_intf = network.interface.in.packets
$hosts $intfs @0..2 > 300 count/sec;
Then the execution of pmie may proceed as follows:
pmie -V uag.11
all_intf:
gonzo: [eth0]
gonzo: [eth2]
all_intf:
gonzo: [eth0]
gonzo: [eth2]
all_intf:
gonzo: [eth0]
gonzo: [eth2]
all_intf:
gonzo: [eth0]
gonzo: [eth2]

?
?

false
false

?
?

true
false

false
false

?
?

true
false

false
false

At each sample, the relational operator greater than (>) produces six truth values for the cross-product of
the instance and sample time dimensions.
the section called “Quantification Operators”, describes additional logical operators that may be used to
reduce the dimensionality of a relational expression.

Performance Metrics Inference Engine

Boolean Expressions
The regular Boolean operators from the C programming language are supported: conjunction (&&),
disjunction (||) and negation (!).
As with the relational operators, the Boolean operators accommodate set-valued operands, and set-valued
results.

Quantification Operators
Boolean and relational operators may accept set-valued operands and produce set-valued results. In many
cases, rules that are appropriate for performance management require a set of truth values to be reduced
along one or more of the dimensions of hosts, instances, and sample times described in the section called
“pmie Metric Expressions”. The pmie quantification operators perform this function.
Each quantification operator takes a one-, two-, or three-dimension set of truth values as an operand, and
reduces it to a set of smaller dimension, by quantification along a single dimension. For example, suppose
the expression in the previous example is simplified and prefixed by some_sample, to produce the
following expression:
intfs = "#eth0 #eth2";
all_intf = some_sample network.interface.in.packets
$intfs @0..2 > 300 count/sec;
Then the expression result is reduced from six values to two (one per interface instance), such that the
result for a particular instance will be false unless the relational expression for the same interface instance
is true for at least one of the preceding three sample times.
There are existential, universal, and percentile quantification operators in each of the host, instance,
and sample time dimensions to produce the nine operators as follows:
some_host

True if the expression is true for at least one host for the same
instance and sample time.

all_host

True if the expression is true for every host for the same
instance and sample time.

N%_host

True if the expression is true for at least N% of the hosts for the
same instance and sample time.

some_inst

True if the expression is true for at least one instance for the
same host and sample time.

all_instance

True if the expression is true for every instance for the same
host and sample time.

N%_instance

True if the expression is true for at least N% of the instances
for the same host and sample time.

some_sample time

True if the expression is true for at least one sample time for
the same host and instance.

all_sample time

True if the expression is true for every sample time for the
same host and instance.

N%_sample time

True if the expression is true for at least N% of the sample
times for the same host and instance.

Performance Metrics Inference Engine

These operators may be nested. For example, the following expression answers the question: “Are all hosts
experiencing at least 20% of their disks busy either reading or writing?”
Servers = ":moomba :babylon";
all_host (
20%_inst disk.dev.read $Servers > 40 ||
20%_inst disk.dev.write $Servers > 40
);
The following expression uses different syntax to encode the same semantics:
all_host (
20%_inst (
disk.dev.read $Servers > 40 ||
disk.dev.write $Servers > 40
)
);

Note
To avoid confusion over precedence and scope for the quantification operators, use explicit
parentheses.
Two additional quantification operators are available for the instance dimension only, namely
match_inst and nomatch_inst, that take a regular expression and a boolean expression. The result
is the boolean AND of the expression and the result of matching (or not matching) the associated instance
name against the regular expression.
For example, this rule evaluates error rates on various 10BaseT Ethernet network interfaces (such as ecN,
ethN, or efN):
some_inst
match_inst "^(ec|eth|ef)"
network.interface.total.errors > 10 count/sec
-> syslog "Ethernet errors:" " %i"

pmie Rule Expressions
Rule expressions for pmie have the following syntax:
lexpr -> actions ;
The semantics are as follows:
• If the logical expression lexpr evaluates true, then perform the actions that follow. Otherwise,
do not perform the actions.
• It is required that lexpr has a singular truth value. Aggregation and quantification operators must have
been applied to reduce multiple truth values to a single value.
• When executed, an action completes with a success/failure status.
• One or more actions may appear; consecutive actions are separated by operators that control the
execution of subsequent actions, as follows:

Performance Metrics Inference Engine

action-1 &

Always execute subsequent actions (serial execution).

action-1 |

If action-1 fails, execute subsequent actions, otherwise skip the
subsequent actions (alternation).

An action is composed of a keyword to identify the action method, an optional time specification,
and one or more arguments.
A time specification uses the same syntax as a valid time interval that may be assigned to delta, as
described in the section called “Setting Evaluation Frequency”. If the action is executed and the time
specification is present, pmie will suppress any subsequent execution of this action until the wall clock
time has advanced by time.
The arguments are passed directly to the action method.
The following action methods are provided:
shell

The single argument is passed to the shell for execution. This action is implemented
using system in the background. The action does not wait for the system call to return,
and succeeds unless the fork fails.

alarm

A notifier containing a time stamp, a single argument as a message, and a Cancel button is
posted on the current display screen (as identified by the DISPLAY environment variable).
Each alarm action first checks if its notifier is already active. If there is an identical active
notifier, a duplicate notifier is not posted. The action succeeds unless the fork fails.

syslog

A message is written into the system log. If the first word of the first argument is -p, the
second word is interpreted as the priority (see the syslog(3) man page); the message tag is
pcp-pmie. The remaining argument is the message to be written to the system log. This
action always succeeds.

A message containing a time stamp in ctime(3) format and the argument is displayed out
to standard output (stdout). This action always succeeds.

Within the argument passed to an action method, the following expansions are supported to allow some
of the context from the logical expression on the left to appear to be embedded in the argument:
%h The value of a host that makes the expression true.
%i The value of an instance that makes the expression true.
%v The value of a performance metric from the logical expression.
Some ambiguity may occur in respect to which host, instance, or performance metric is bound to a %token. In most cases, the leftmost binding in the top-level subexpression is used. You may need to use
pmie in the interactive debugging mode (specify the -d command line option) in conjunction with the W command line option to discover which subexpressions contributes to the %-token bindings.
Example 5.7, “Rule Expression Options ” illustrates some of the options when constructing rule
expressions:

Example 5.7. Rule Expression Options
some_inst ( disk.dev.total > 60 )
-> syslog 10 mins "[%i] busy, %v IOPS " &

Performance Metrics Inference Engine

shell 1 hour "echo \
'Disk %i is REALLY busy. Running at %v I/Os per second' \
| Mail -s 'pmie alarm' sysadm";
In this case, %v and %i are both associated with the instances for the metric disk.dev.total that
make the expression true. If more than one instance makes the expression true (more than one disk is busy),
then the argument is formed by concatenating the result from each %-token binding. The text added to the
system log file might be as shown in Example 5.8, “System Log Text”:

Example 5.8. System Log Text
Aug 6 08:12:44 5B:gonzo pcp-pmie[3371]:
[disk1] busy, 3.7 IOPS [disk2] busy, 0.3 IOPS

Note
When pmie is processing performance metrics from a set of PCP archive logs, the actions
will be processed in the expected manner; however, the action methods are modified to report a
textual facsimile of the action on the standard output.
Consider the rule in Example 5.9, “Standard Output”:

Example 5.9. Standard Output
delta = 2 sec; // more often for demonstration purposes
percpu = "kernel.percpu";
// Unusual usr-sys split when some CPU is more than 20% in usr mode
// and sys mode is at least 1.5 times usr mode
//
cpu_usr_sys = some_inst (
$percpu.cpu.sys > $percpu.cpu.user * 1.5 &&
$percpu.cpu.user > 0.2
) -> alarm "Unusual sys time: " "%i ";
When evaluated against an archive, the following output is generated (the alarm action produces a message
on standard output):
pmafm
alarm
alarm
alarm
alarm
alarm

${HOME}/f4
Wed Aug 7
Wed Aug 7
Wed Aug 7
Wed Aug 7
Wed Aug 7

pmie cpu.head cpu.00
14:54:48 2012: Unusual
14:54:50 2012: Unusual
14:54:52 2012: Unusual
14:55:02 2012: Unusual
14:55:06 2012: Unusual

sys
sys
sys
sys
sys

time:
time:
time:
time:
time:

cpu0
cpu0
cpu0
cpu0
cpu0

pmie Intrinsic Operators
The following sections describe some other useful intrinsic operators for pmie. These operators are divided
into three groups:
• Arithmetic aggregation
• The rate operator
• Transitional operators

Performance Metrics Inference Engine

Arithmetic Aggregation
For set-valued arithmetic expressions, the following operators reduce the dimensionality of the result by
arithmetic aggregation along one of the host, instance, or sample time dimensions. For example,
to aggregate in the host dimension, the following operators are provided:
avg_host

Computes the average value across all instances for the same host and
sample time

sum_host

Computes the total value across all instances for the same host and
sample time

count_host

Computes the number of values across all instances for the same host and
sample time

min_host

Computes the minimum value across all instances for the same host and
sample time

max_host

Computes the maximum value across all instances for the same host and
sample time

Ten additional operators correspond to the forms *_inst and *_sample.
The following example illustrates the use of an aggregate operator in combination with an existential
operator to answer the question “Does some host currently have two or more busy processors?”
// note '' to escape - in host name
poke = ":moomba :'mac-larry' :bitbucket";
some_host (
count_inst ( kernel.percpu.cpu.user $poke +
kernel.percpu.cpu.sys $poke > 0.7 ) >= 2
)
-> alarm "2 or more busy CPUs";

The rate Operator
The rate operator computes the rate of change of an arithmetic expression as shown in the following
example:
rate mem.util.cached
It returns the rate of change for the mem.util.cached performance metric; that is, the rate at which
page cache memory is being allocated and released.
The rate intrinsic operator is most useful for metrics with instantaneous value semantics. For metrics
with counter semantics, pmie already performs an implicit rate calculation (see the the section called
“pmie Rate Conversion”) and the rate operator would produce the second derivative with respect to
time, which is less likely to be useful.

Transitional Operators
In some cases, an action needs to be triggered when an expression changes from true to false or vice versa.
The following operators take a logical expression as an operand, and return a logical expression:
rising

Has the value true when the operand transitions from false to true in consecutive
samples.

Performance Metrics Inference Engine

falling

Has the value false when the operand transitions from true to false in consecutive
samples.

pmie Examples
The examples presented in this section are task-oriented and use the full power of the pmie specification
language as described in the section called “Specification Language for pmie”.
Source code for the pmie examples in this chapter, and many more examples, is provided within the PCP
Tutorials and Case Studies. Example 5.10, “Monitoring CPU Utilization” and Example 5.11, “Monitoring
Disk Activity ” illustrate monitoring CPU utilization and disk activity.

Example 5.10. Monitoring CPU Utilization
// Some Common Performance Monitoring Scenarios
//
// The CPU Group
//
delta = 2 sec; // more often for demonstration purposes
// common prefixes
//
percpu = "kernel.percpu";
all
= "kernel.all";
// Unusual usr-sys split when some CPU is more than 20% in usr mode
// and sys mode is at least 1.5 times usr mode
//
cpu_usr_sys =
some_inst (
$percpu.cpu.sys > $percpu.cpu.user * 1.5 &&
$percpu.cpu.user > 0.2
)
-> alarm "Unusual sys time: " "%i ";
// Over all CPUs, syscall_rate > 1000 * no_of_cpus
//
cpu_syscall =
$all.syscall > 1000 count/sec * hinv.ncpu
-> print "high aggregate syscalls: %v";
// Sustained high syscall rate on a single CPU
//
delta = 30 sec;
percpu_syscall =
some_inst (
$percpu.syscall > 2000 count/sec
)
-> syslog "Sustained syscalls per second? " "[%i] %v ";
// the 1 minute load average exceeds 5 * number of CPUs on any host
hosts = ":gonzo :moomba";
// change as required
delta = 1 minute;
// no need to evaluate more often than this
high_load =
some_host (
$all.load $hosts #'1 minute' > 5 * hinv.ncpu
)
-> alarm "High Load Average? " "%h: %v ";

Performance Metrics Inference Engine

Example 5.11. Monitoring Disk Activity
// Some Common Performance Monitoring Scenarios
//
// The Disk Group
//
delta = 15 sec;
// often enough for disks?
// common prefixes
//
disk
= "disk";
// Any disk performing more than 40 I/Os per second, sustained over
// at least 30 seconds is probably busy
//
delta = 30 seconds;
disk_busy =
some_inst (
$disk.dev.total > 40 count/sec
)
]
-> shell "Mail -s 'Heavy systained disk traffic' sysadm";
// Try and catch bursts of activity ... more than 60 I/Os per second
// for at least 25% of 8 consecutive 3 second samples
//
delta = 3 sec;
disk_burst =
some_inst (
25%_sample (
$disk.dev.total @0..7 > 60 count/sec
)
)
-> alarm "Disk Burst? " "%i ";
// any SCSI disk controller performing more than 3 Mbytes per
// second is busy
// Note: the obscure 512 is to convert blocks/sec to byte/sec,
//
and pmie handles the rest of the scale conversion
//
some_inst $disk.ctl.blktotal * 512 > 3 Mbyte/sec
-> alarm "Busy Disk Controller: " "%i ";

Developing and Debugging pmie Rules
Given the -d command line option, pmie executes in interactive mode, and the user is presented with a
menu of options:
pmie debugger commands
f [file-name]
l [expr-name]
r [interval]
S time-spec
T time-spec
v [expr-name]
h or ?
q
pmie>

load expressions from given file or stdin
list named expression or all expressions
run for given or default interval
set start time for run
set default interval for run command
print subexpression for %h, %i and %v bindings
print this menu of commands
quit

Performance Metrics Inference Engine

If both the -d option and a filename are present, the expressions in the given file are loaded before entering
interactive mode. Interactive mode is useful for debugging new rules.

Caveats and Notes on pmie
The following sections provide important information for users of pmie.

Performance Metrics Wraparound
Performance metrics that are cumulative counters may occasionally overflow their range and wraparound
to 0. When this happens, an unknown value (printed as ?) is returned as the value of the metric for one
sample (recall that the value returned is normally a rate). You can have PCP interpolate a value based on
expected rate of change by setting the PCP_COUNTER_WRAP environment variable.

pmie Sample Intervals
The sample interval (delta) should always be long enough, particularly in the case of rates, to ensure that
a meaningful value is computed. Interval may vary according to the metric and your needs. A reasonable
minimum is in the range of ten seconds or several minutes. Although PCP supports sampling rates up to
hundreds of times per second, using small sample intervals creates unnecessary load on the monitored
system.

pmie Instance Names
When you specify a metric instance name (#identifier) in a pmie expression, it is compared against
the instance name looked up from either a live collector system or an archive as follows:
• If the given instance name and the looked up name are the same, they are considered to match.
• Otherwise, the first two space separated tokens are extracted from the looked up name. If the given
instance name is the same as either of these tokens, they are considered a match.
For some metrics, notably the per process (proc.xxx.xxx) metrics, the first token in the looked up
instance name is impossible to determine at the time you are writing pmie expressions. The above policy
circumvents this problem.

pmie Error Detection
The parser used in pmie is not particularly robust in handling syntax errors. It is suggested that you check
any problematic expressions individually in interactive mode:
pmie -v -d
pmie> f
expression
Ctrl+D
If the expression was parsed, its internal representation is shown:
pmie> l
The expression is evaluated twice and its value printed:
pmie> r 10sec
Then quit:

Performance Metrics Inference Engine

pmie> q
It is not always possible to detect semantic errors at parse time. This happens when a performance metric
descriptor is not available from the named host at this time. A warning is issued, and the expression is put
on a wait list. The wait list is checked periodically (about every five minutes) to see if the metric descriptor
has become available. If an error is detected at this time, a message is printed to the standard error stream
(stderr) and the offending expression is set aside.

Creating pmie Rules with pmieconf
The pmieconf tool is a command line utility that is designed to aid the specification of pmie rules from
parameterized versions of the rules. pmieconf is used to display and modify variables or parameters
controlling the details of the generated pmie rules.
pmieconf reads two different forms of supplied input files and produces a localized pmie configuration
file as its output.
The first input form is a generalized pmie rule file such as those found below ${PCP_VAR_DIR}/
config/pmieconf. These files contain the generalized rules which pmieconf is able to manipulate.
Each of the rules can be enabled or disabled, or the individual variables associated with each rule can be
edited.
The second form is an actual pmie configuration file (that is, a file which can be interpreted by pmie,
conforming to the pmie syntax described in the section called “Specification Language for pmie”). This
file is both input to and output from pmieconf.
The input version of the file contains any changed variables or rule states from previous invocations
of pmieconf, and the output version contains both the changes in state (for any subsequent pmieconf
sessions) and the generated pmie syntax. The pmieconf state is embedded within a pmie comment block
at the head of the output file and is not interpreted by pmie itself.
pmieconf is an integral part of the pmie daemon management process described in the section called
“Management of pmie Processes”. Procedure 5.1, “Display pmieconf Rules” and Procedure 5.2, “Modify
pmieconf Rules and Generate a pmie File” introduce the pmieconf tool through a series of typical
operations.

Procedure 5.1. Display pmieconf Rules
1.

Start pmieconf interactively (as the superuser).
pmieconf -f ${PCP_SYSCONF_DIR}/pmie/config.demo
Updates will be made to ${PCP_SYSCONF_DIR}/pmie/config.demo
pmieconf>

List the set of available pmieconf rules by using the rules command.

List the set of rule groups using the groups command.

List only the enabled rules, using the rules enabled command.

List a single rule:
pmieconf> list memory.swap_low
rule: memory.swap_low [Low free swap space]
help: There is only threshold percent swap space remaining - the system

Performance Metrics Inference Engine

may soon run out of virtual memory. Reduce the number and size of
the running programs or add more swap(1) space before it
completely
runs out.
predicate =
some_host (
( 100 * ( swap.free $hosts$ / swap.length $hosts$ ) )
< $threshold$
&& swap.length $hosts$ > 0
// ensure swap in use
)
vars: enabled = no
threshold = 10%
pmieconf>
6.

List one rule variable:
pmieconf> list memory.swap_low threshold
rule: memory.swap_low [Low free swap space]
threshold = 10%
pmieconf>

Procedure 5.2. Modify pmieconf Rules and Generate a pmie File
1.

Lower the threshold for the memory.swap_low rule, and also change the pmie sample interval
affecting just this rule. The delta variable is special in that it is not associated with any particular
rule; it has been defined as a global pmieconf variable. Global variables can be displayed using the
list global command to pmieconf, and can be modified either globally or local to a specific rule.
pmieconf> modify memory.swap_low threshold 5
pmieconf> modify memory.swap_low delta "1 sec"
pmieconf>

Disable all of the rules except for the memory.swap_low rule so that you can see the effects of
your change in isolation.
This produces a relatively simple pmie configuration file:
pmieconf> disable all
pmieconf> enable memory.swap_low
pmieconf> status
verbose: off
enabled rules: 1 of 35
pmie configuration file: ${PCP_SYSCONF_DIR}/pmie/config.demo
pmie processes (PIDs) using this file: (none found)
pmieconf> quit
You can also use the status command to verify that only one rule is enabled at the end of this step.

Performance Metrics Inference Engine

Run pmie with the new configuration file. Use a text editor to view the newly generated pmie
configuration file (${PCP_SYSCONF_DIR}/pmie/config.demo), and then run the command:
pmie -T "1.5 sec" -v -l ${HOME}/demo.log ${PCP_SYSCONF_DIR}/pmie/config.demo
memory.swap_low: false
memory.swap_low: false
cat ${HOME}/demo.log
Log for pmie on venus started Mon Jun 21 16:26:06 2012
pmie: PID = 21847, default host = venus
[Mon Jun 21 16:26:07] pmie(21847) Info: evaluator exiting
Log finished Mon Jun 21 16:26:07 2012

Notice that both of the pmieconf files used in the previous step are simple text files, as described in
the pmieconf(5) man page:
file ${PCP_SYSCONF_DIR}/pmie/config.demo
${PCP_SYSCONF_DIR}/pmie/config.demo: PCP pmie config (V.1)
file ${PCP_VAR_DIR}/config/pmieconf/memory/swap_low
${PCP_VAR_DIR}/config/pmieconf/memory/swap_low:
PCP pmieconf rules (V.1)

Management of pmie Processes
The pmie process can be run as a daemon as part of the system startup sequence, and can thus be used
to perform automated, live performance monitoring of a running system. To do this, run these commands
(as superuser):
chkconfig pmie on
${PCP_RC_DIR}/pmie start
By default, these enable a single pmie process monitoring the local host, with the default set of pmieconf
rules enabled (for more information about pmieconf, see the section called “Creating pmie Rules with
pmieconf”). Procedure 5.3, “Add a New pmie Instance to the pmie Daemon Management Framework”
illustrates how you can use these commands to start any number of pmie processes to monitor local or
remote machines.

Procedure 5.3. Add a New pmie Instance to the pmie Daemon Management
Framework
1.

Use a text editor (as superuser) to edit the pmie${PCP_PMIECONTROL_PATH} and
${PCP_PMIECONTROL_PATH}.d control files. Notice the default entry, which looks like this:
#Host
LOCALHOSTNAME

P?
y

S?
n

Log File
PCP_LOG_DIR/pmie/LOCALHOSTNAME/pmie.log

Arguments
-c config.def

This entry is used to enable a local pmie process. Add a new entry for a remote host on your
local network (for example, venus), by using your pmie configuration file (see the section called
“Creating pmie Rules with pmieconf”):
#Host

Log File

Arguments

Performance Metrics Inference Engine

venus

PCP_LOG_DIR/pmie/venus/pmie.log

-c config.dem

Note
Without an absolute path, the configuration file (-c above) will be resolved using
${PCP_SYSCONF_DIR}/pmie - if config.demo was created in Procedure 5.2,
“Modify pmieconf Rules and Generate a pmie File” it would be used here for host
venus, otherwise a new configuration file will be generated using the default rules (at
${PCP_SYSCONF_DIR}/pmie/config.demo).
2.

Enable pmie daemon management:
chkconfig pmie on
This simple step allows pmie to be started as part of your machine's boot process.

Start the two pmie daemons. At the end of this step, you should see two new pmie processes
monitoring the local and remote hosts:
${PCP_RC_DIR}/pmie start
Performance Co-Pilot starting inference engine(s) ...
Wait a few moments while the startup scripts run. The pmie start script uses the pmie_check script
to do most of its work.
Verify that the pmie processes have started:
pcp
Performance Co-Pilot configuration on pluto:
platform:
hardware:
timezone:
pmcd:
pmda:
pmie:

Linux pluto 3.10.0-0.rc7.64.el7.x86_64 #1 SMP
8 cpus, 2 disks, 23960MB RAM
EST-10
Version 3.11.3-1, 8 agents
pmcd proc xfs linux mmv infiniband gluster elasticsearch
pluto: ${PCP_LOG_DIR}/pmie/pluto/pmie.log
venus: ${PCP_LOG_DIR}/pmie/venus/pmie.log

If a remote host is not up at the time when pmie is started, the pmie process may exit. pmie processes
may also exit if the local machine is starved of memory resources. To counter these adverse cases, it can
be useful to have a crontab entry running. Adding an entry as shown in the section called “Add a pmie
crontab Entry” ensures that if one of the configured pmie processes exits, it is automatically restarted.

Add a pmie crontab Entry
To activate the maintenance and housekeeping scripts for a collection of inference engines, execute the
following tasks while logged into the local host as the superuser (root):
1. Augment the crontab file for the pcp user. For example:

Performance Metrics Inference Engine

crontab -l -u pcp > ${HOME}/crontab.txt
2. Edit ${HOME}/crontab.txt, adding lines similar to those from the sample ${PCP_VAR_DIR}/
config/pmie/crontab file for pmie_daily and pmie_check; for example:
# daily processing of pmie logs
10
0
*
*
*
${PCP_BINADM_DIR}/pmie_daily
# every 30 minutes, check pmie instances are running
25,55 *
*
*
*
${PCP_BINADM_DIR}/pmie_check
3. Make these changes permanent with this command:
crontab -u pcp < ${HOME}/crontab.txt

Global Files and Directories
The following global files and directories influence the behavior of pmie and the pmie management scripts:
${PCP_DEMOS_DIR}/pmie/*

Contains sample pmie rules that may be used
as a basis for developing local rules.

${PCP_SYSCONF_DIR}/pmie/config.default

Is the default pmie configuration file that
is used when the pmie daemon facility
is enabled. Generated by pmieconf if not
manually setup beforehand.

${PCP_VAR_DIR}/config/pmieconf/*/*

Contains the pmieconf rule definitions
(templates) in its subdirectories.

${PCP_PMIECONTROL_PATH} and
${PCP_PMIECONTROL_PATH}.d files

Defines which PCP collector hosts require
a daemon pmie to be launched on the local
host, where the configuration file comes
from, where the pmie log file should be
created, and pmie startup options.

${PCP_VAR_DIR}/config/pmlogger/crontab

Contains default crontab entries that may
be merged with the crontab entries for root
to schedule the periodic execution of the
pmie_check script, for verifying that pmie
instances are running. Only for platforms
where a default crontab is not automatically
installed during the initial PCP package
installation.

${PCP_LOG_DIR}/pmie/*

Contains the pmie log files for the host. These
files are created by the default behavior of the
${PCP_RC_DIR}/pmie startup scripts.

pmie Instances and Their Progress
The PMCD PMDA exports information about executing pmie instances and their progress in terms of rule
evaluations and action execution rates.
pmie_check

This command is similar to the pmlogger support script,
pmlogger_check.

Performance Metrics Inference Engine

${PCP_RC_DIR}/pmie

This start script supports the starting and stopping of
multiple pmie instances that are monitoring one or more
hosts.

${PCP_TMP_DIR}/pmie

The statistics that pmie gathers are maintained in binary
data structure files. These files are located in this directory.

pmcd.pmie metrics

If pmie is running on a system with a PCP collector
deployment, the PMCD PMDA exports these metrics via
the pmcd.pmie group of metrics.

Chapter 6. Archive Logging
Table of Contents
Introduction to Archive Logging ..........................................................................................
Archive Logs and the PMAPI .....................................................................................
Retrospective Analysis Using Archive Logs ...................................................................
Using Archive Logs for Capacity Planning ....................................................................
Using Archive Logs with Performance Tools .........................................................................
Coordination between pmlogger and PCP tools ..............................................................
Administering PCP Archive Logs Using cron Scripts ......................................................
Archive Log File Management ....................................................................................
Cookbook for Archive Logging ...........................................................................................
Primary Logger .........................................................................................................
Other Logger Configurations .......................................................................................
Archive Log Administration ........................................................................................
Other Archive Logging Features and Services ........................................................................
PCP Archive Folios ...................................................................................................
Manipulating Archive Logs with pmlogextract ..............................................................
Summarizing Archive Logs with pmlogsummary ..........................................................
Primary Logger .........................................................................................................
Using pmlc ..............................................................................................................
Archive Logging Troubleshooting ........................................................................................
pmlogger Cannot Write Log .......................................................................................
Cannot Find Log .......................................................................................................
Primary pmlogger Cannot Start ...................................................................................
Identifying an Active pmlogger Process .......................................................................
Illegal Label Record ..................................................................................................
Empty Archive Log Files or pmlogger Exits Immediately ................................................

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Performance monitoring and management in complex systems demands the ability to accurately capture
performance characteristics for subsequent review, analysis, and comparison. Performance Co-Pilot (PCP)
provides extensive support for the creation and management of archive logs that capture a user-specified
profile of performance information to support retrospective performance analysis.
The following major sections are included in this chapter:
• the section called “Introduction to Archive Logging”, presents the concepts and issues involved with
creating and using archive logs.
• the section called “Using Archive Logs with Performance Tools”, describes the interaction of the PCP
tools with archive logs.
• the section called “Cookbook for Archive Logging”, shows some shortcuts for setting up useful PCP
archive logs.
• the section called “Other Archive Logging Features and Services”, provides information about other
archive logging features and sevices.
• the section called “Archive Logging Troubleshooting”, presents helpful directions if your archive
logging implementation is not functioning correctly.

Archive Logging

Introduction to Archive Logging
Within the PCP, the pmlogger utility may be configured to collect archives of performance metrics. The
archive creation process is simple and very flexible, incorporating the following features:
• Archive log creation at either a PCP collector (typically a server) or a PCP monitor system (typically a
workstation), or at some designated PCP archive logger host.
• Concurrent independent logging, both local and remote. The performance analyst can activate a private
pmlogger instance to collect only the metrics of interest for the problem at hand, independent of other
logging on the workstation or remote host.
• Independent determination of logging frequency for individual metrics or metric instances. For example,
you could log the “5 minute” load average every half hour, the write I/O rate on the DBMS log spindle
every 10 seconds, and aggregate I/O rates on the other disks every minute.
• Dynamic adjustment of what is to be logged, and how frequently, via pmlc. This feature may be used to
disable logging or to increase the sample interval during periods of low activity or chronic high activity.
A local pmlc may interrogate and control a remote pmlogger, subject to the access control restrictions
implemented by pmlogger.
• Self-contained logs that include all system configuration and metadata required to interpret the values
in the log. These logs can be kept for analysis at a much later time, potentially after the hardware or
software has been reconfigured and the logs have been stored as discrete, autonomous files for remote
analysis. The logs are endian-neutral and platform independent - there is no requirement that the monitor
host machine used for analysis be similar to the collector machine in any way, nor do they have to have
the same versions of PCP. PCP archives created over 15 years ago can still be replayed with the current
versions of PCP!
• cron-based scripts to expedite the operational management, for example, log rotation, consolidation,
and culling. Another helper tool, pmlogconf can be used to generate suitable logging configurations
for a variety of situations.
• Archive folios as a convenient aggregation of multiple archive logs. Archive folios may be created with
the mkaf utility and processed with the pmafm tool.

Archive Logs and the PMAPI
Critical to the success of the PCP archive logging scheme is the fact that the library routines providing
access to real-time feeds of performance metrics also provide access to the archive logs.
Live feeds (or real-time) sources of performance metrics and archives are literally interchangeable, with
a single Performance Metrics Application Programming Interface (PMAPI) that preserves the same
semantics for both styles of metric source. In this way, applications and tools developed against the PMAPI
can automatically process either live or historical performance data.

Retrospective Analysis Using Archive Logs
One of the most important applications of archive logging services provided by PCP is in the area of
retrospective analysis. In many cases, understanding today's performance problems can be assisted by sideby-side comparisons with yesterday's performance. With routine creation of performance archive logs,
you can concurrently replay pictures of system performance for two or more periods in the past.

Archive Logging

Archive logs are also an invaluable source of intelligence when trying to diagnose what went wrong, as
in a performance post-mortem. Because the PCP archive logs are entirely self-contained, this analysis can
be performed off-site if necessary.
Each archive log contains metric values from only one host. However, many PCP tools can simultaneously
visualize values from multiple archives collected from different hosts.
The archives can be replayed using the inference engine (pmie is an application that uses the PMAPI).
This allows you to automate the regular, first-level analysis of system performance.
Such analysis can be performed by constructing suitable expressions to capture the essence of common
resource saturation problems, then periodically creating an archive and playing it against the expressions.
For example, you may wish to create a daily performance audit (perhaps run by the cron command) to
detect performance regressions.
For more about pmie, see Chapter 5, Performance Metrics Inference Engine.

Using Archive Logs for Capacity Planning
By collecting performance archives with relatively long sampling periods, or by reducing the daily archives
to produce summary logs, the capacity planner can collect the base data required for forward projections,
and can estimate resource demands and explore “what if” scenarios by replaying data using visualization
tools and the inference engine.

Using Archive Logs with Performance Tools
Most PCP tools default to real-time display of current values for performance metrics from PCP collector
host(s). However, most PCP tools also have the capability to display values for performance metrics
retrieved from PCP archive log(s). The following sections describe plans, steps, and general issues
involving archive logs and the PCP tools.

Coordination between pmlogger and PCP tools
Most commonly, a PCP tool would be invoked with the -a option to process sets of archive logs some
time after pmlogger had finished creating the archive. However, a tool such as pmchart that uses a Time
Control dialog (see the section called “Time Duration and Control”) stops when the end of a set of archives
is reached, but could resume if more data is written to the PCP archive log.

Note
pmlogger uses buffered I/O to write the archive log so that the end of the archive may be aligned
with an I/O buffer boundary, rather than with a logical archive log record. If such an archive was
read by a PCP tool, it would appear truncated and might confuse the tool. These problems may
be avoided by sending pmlogger a SIGUSR1 signal, or by using the flush command of pmlc to
force pmlogger to flush its output buffers.

Administering PCP Archive Logs Using cron Scripts
Many operating systems support the cron process scheduling system.
PCP supplies shell scripts to use the cron functionality to help manage your archive logs. The following
scripts are supplied:

Archive Logging

Script

Description

pmlogger_daily(1)

Performs a daily housecleaning of archive logs and notices.

pmlogger_merge(1)

Merges archive logs and is called by pmlogger_daily.

pmlogger_check(1)

Checks to see that all desired pmlogger processes are running
on your system, and invokes any that are missing for any reason.

pmlogconf(1)

Generates suitable pmlogger configuration files based on a
pre-defined set of templates. It can probe the state of the
system under observation to make informed decisions about
which metrics to record. This is an extensible facility, allowing
software upgrades and new PMDA installations to add to the
existing set of templates.

pmsnap(1)

Generates graphic image snapshots of pmchart performance
charts at regular intervals.

The configuration files used by these scripts can be edited to suit your particular
needs, and are generally controlled by the ${PCP_PMLOGGERCONTROL_PATH} and
${PCP_PMLOGGERCONTROL_PATH}.d files (pmsnap has an additional control file,
${PCP_PMSNAPCONTROL_PATH}). Complete information on these scripts is available in the
pmlogger_daily(1) and pmsnap(1) man pages.

Archive Log File Management
PCP archive log files can occupy a great deal of disk space, and management of archive logs can be a large
task in itself. The following sections provide information to assist you in PCP archive log file management.

Basename Conventions
When a PCP archive is created by pmlogger, an archive basename must be specified and several physical
files are created, as shown in Table 6.1, “Filenames for PCP Archive Log Components (archive.*)”.

Table 6.1. Filenames for PCP Archive Log Components (archive.*)
Filename

Contents

archive.index

Temporal index for rapid access to archive contents.

archive.meta

Metadata descriptions for performance metrics and instance domains
appearing in the archive.

archive.N

Volumes of performance metrics values, for N = 0,1,2,...

Log Volumes
A single PCP archive may be partitioned into a number of volumes. These volumes may expedite
management of the archive; however, the metadata file and at least one volume must be present before a
PCP tool can process the archive.
You can control the size of an archive log volume by using the -v command line option to pmlogger.
This option specifies how large a volume should become before pmlogger starts a new volume. Archive
log volumes retain the same base filename as other files in the archive log, and are differentiated by a
numeric suffix that is incremented with each volume change. For example, you might have a log volume
sequence that looks like this:

Archive Logging

netserver-log.0
netserver-log.1
netserver-log.2
You can also cause an existing log to be closed and a new one to be opened by sending a SIGHUP signal
to pmlogger, or by using the pmlc command to change the pmlogger instructions dynamically, without
interrupting pmlogger operation. Complete information on log volumes is found in the pmlogger(1) man
page.

Basenames for Managed Archive Log Files
The PCP archive management tools support a consistent scheme for selecting the basenames for the files
in a collection of archives and for mapping these files to a suitable directory hierarchy.
Once configured, the PCP tools that manage archive logs employ a consistent scheme for selecting
the basename for an archive each time pmlogger is launched, namely the current date and time in the
format YYYYMMDD.HH.MM. Typically, at the end of each day, all archives for a particular host
on that day would be merged to produce a single archive with a basename constructed from the date,
namely YYYYMMDD. The pmlogger_daily script performs this action and a number of other routine
housekeeping chores.

Directory Organization for Archive Log Files
If you are using a deployment of PCP tools and daemons to collect metrics from a variety of hosts and
storing them all at a central location, you should develop an organized strategy for storing and naming
your log files.

Note
There are many possible configurations of pmlogger, as described in the section called
“PCP Archive Logger Deployment”. The directory organization described in this section is
recommended for any system on which pmlogger is configured for permanent execution (as
opposed to short-term executions, for example, as launched from pmchart to record some
performance data of current interest).
Typically, the filesystem structure can be used to reflect the number of hosts for which a pmlogger instance
is expected to be running locally, obviating the need for lengthy and cumbersome filenames. It makes
considerable sense to place all logs for a particular host in a separate directory named after that host.
Because each instance of pmlogger can only log metrics fetched from a single host, this also simplifies
some of the archive log management and administration tasks.
For example, consider the filesystem and naming structure shown in Figure 6.1, “Archive Log Directory
Structure”.

Figure 6.1. Archive Log Directory Structure

The specification of where to place the archive log files for particular pmlogger instances is encoded in the
${PCP_PMLOGGERCONTROL_PATH} and ${PCP_PMLOGGERCONTROL_PATH}.d configuration
files, and these files should be customized on each host running an instance of pmlogger.
If many archives are being created, and the associated PCP collector systems form peer classes based upon
service type (Web servers, DBMS servers, NFS servers, and so on), then it may be appropriate to introduce

Archive Logging

another layer into the directory structure, or use symbolic links to group together hosts providing similar
service types.

Configuration of pmlogger
The configuration files used by pmlogger describe which metrics are to be logged. Groups of metrics may
be logged at different intervals to other groups of metrics. Two states, mandatory and advisory, also apply
to each group of metrics, defining whether metrics definitely should be logged or not logged, or whether
a later advisory definition may change that state.
The mandatory state takes precedence if it is on or off, causing any subsequent request for a change in
advisory state to have no effect. If the mandatory state is maybe, then the advisory state determines if
logging is enabled or not.
The mandatory states are on, off, and maybe. The advisory states, which only affect metrics that are
mandatory maybe, are on and off. Therefore, a metric that is mandatory maybe in one definition and
advisory on in another definition would be logged at the advisory interval. Metrics that are not specified
in the pmlogger configuration file are mandatory maybe and advisory off by default and are not logged.
A complete description of the pmlogger configuration format can be found on the pmlogger(1) man page.

PCP Archive Contents
Once a PCP archive log has been created, the pmdumplog utility may be used to display various
information about the contents of the archive. For example, start with the following command:
pmdumplog -l ${PCP_LOG_DIR}/pmlogger/www.sgi.com/19960731
It might produce the following output:
Log Label (Log Format Version 1)
Performance metrics from host www.sgi.com
commencing Wed Jul 31 00:16:34.941 1996
ending
Thu Aug 1 00:18:01.468 1996
The simplest way to discover what performance metrics are contained within a set of archives is to use
pminfo as shown in Example 6.1, “Using pminfo to Obtain Archive Information”:

Example 6.1. Using pminfo to Obtain Archive Information
pminfo -a ${PCP_LOG_DIR}/pmlogger/www.sgi.com/19960731 network.mbuf
network.mbuf.alloc
network.mbuf.typealloc
network.mbuf.clustalloc
network.mbuf.clustfree
network.mbuf.failed
network.mbuf.waited
network.mbuf.drained

Cookbook for Archive Logging
The following sections present a checklist of tasks that may be performed to enable PCP archive logging
with minimal effort. For a complete explanation, refer to the other sections in this chapter and the man
pages for pmlogger and related tools.

Archive Logging

Primary Logger
Assume you wish to activate primary archive logging on the PCP collector host pluto. Execute the
following while logged into pluto as the superuser (root).
1. Start pmcd and pmlogger:
chkconfig pmcd on
chkconfig pmlogger on
${PCP_RC_DIR}/pmcd start
Starting pmcd ...
${PCP_RC_DIR}/pmlogger start
Starting pmlogger ...
2. Verify that the primary pmlogger instance is running:
pcp
Performance Co-Pilot configuration on pluto:
platform: Linux pluto 3.10.0-0.rc7.64.el7.x86_64 #1 SMP
hardware: 8 cpus, 2 disks, 23960MB RAM
timezone: EST-10
pmcd: Version 4.0.0-1, 8 agents
pmda: pmcd proc xfs linux mmv infiniband gluster elasticsearch
pmlogger: primary logger: pluto/20170815.10.00
pmie: pluto: ${PCP_LOG_DIR}/pmie/pluto/pmie.log
venus: ${PCP_LOG_DIR}/pmie/venus/pmie.log
3. Verify that the archive files are being created in the expected place:
ls ${PCP_LOG_DIR}/pmlogger/pluto
20170815.10.00.0
20170815.10.00.index
20170815.10.00.meta
Latest
pmlogger.log
4. Verify that no errors are being logged, and the rate of expected growth of the archives:
cat ${PCP_LOG_DIR}/pmlogger/pluto/pmlogger.log
Log for pmlogger on pluto started Thu Aug 15 10:00:11 2017
Config parsed
Starting primary logger for host "pluto"
Archive basename: 20170815.00.10
Group [26 metrics] {
hinv.map.lvname
...
hinv.ncpu
} logged once: 1912 bytes
Group [11 metrics] {
kernel.all.cpu.user
...

Archive Logging

kernel.all.load
} logged every 60 sec: 372 bytes or 0.51 Mbytes/day
...

Other Logger Configurations
Assume you wish to create archive logs on the local host for performance metrics collected from the remote
host venus. Execute all of the following tasks while logged into the local host as the superuser (root).

Procedure 6.1. Creating Archive Logs
1.

Create a suitable pmlogger configuration file. There are several options:
• Run the pmlogconf(1) utility to generate a configuration file, and (optionally) interactively
customize it further to suit local needs.
${PCP_BINADM_DIR}/pmlogconf ${PCP_SYSCONF_DIR}/pmlogger/config.venus
Creating config file "${PCP_SYSCONF_DIR}/pmlogger/config.venus" using default
${PCP_BINADM_DIR}/pmlogconf ${PCP_SYSCONF_DIR}/pmlogger/config.venus
Group: utilization per CPU
Log this group? [n] y
Logging interval? [default]
Group: utilization (usr, sys, idle, ...) over all CPUs
Log this group? [y] y
Logging interval? [default]
Group: per spindle disk activity
Log this group? [n] y
...
• Do nothing - a default configuration will be created in the following step, using pmlogconf(1)
probing and automatic file generation based on the metrics available at the remote host. The
${PCP_RC_DIR}/pmlogger start script handles this.
• Manually - create a configuration file with a text editor, or arrange to have one put in
place by configuration management tools like Puppet [https://puppetlabs.com/] or Chef [http://
www.opscode.com/chef/].

Edit
${PCP_PMLOGGERCONTROL_PATH},
or
one
of
the
${PCP_PMLOGGERCONTROL_PATH}.d files. Using the line for remote as a template, add the
following line:
venus n n PCP_LOG_DIR/pmlogger/venus -r -T24h10m -c config.venus

Start pmlogger:
${PCP_BINADM_DIR}/pmlogger_check
Restarting pmlogger for host "venus" ..... done

Verify that the pmlogger instance is running:

Archive Logging

pcp
Performance Co-Pilot configuration on pluto:
platform: Linux pluto 3.10.0-0.rc7.64.el7.x86_64 #1 SMP
hardware: 8 cpus, 2 disks, 23960MB RAM
timezone: EST-10
pmcd: Version 3.8.3-1, 8 agents
pmda: pmcd proc linux xfs mmv infiniband gluster elasticsearch
pmlogger: primary logger: pluto/20170815.10.00
venus.redhat.com: venus/20170815.11.15
pmlc
pmlc> show loggers
The following pmloggers are running on pluto:
primary (19144) 5141
pmlc> connect 5141
pmlc> status
pmlogger [5141] on host pluto is logging metrics from host venus
log started
Thu Aug 15 11:15:39 2017 (times in local time)
last log entry
Thu Aug 15 11:47:39 2017
current time
Thu Aug 15 11:48:13 2017
log volume
0
log size
146160
To create archive logs on the local host for performance metrics collected from multiple remote hosts,
repeat the steps in Procedure 6.1, “Creating Archive Logs” for each remote host (each with a new
control file entry).

Archive Log Administration
Assume the local host has been set up to create archive logs of performance metrics collected from one or
more hosts (which may be either the local host or a remote host).

Note
Depending on your platform, the crontab entry discussed here may already have been installed
for you, as part of the package installation process. In this case, the file /etc/cron.d/pcppmlogger will exist, and the rest of this section can be skipped.
To activate the maintenance and housekeeping scripts for a collection of archive logs, execute the following
tasks while logged into the local host as the superuser (root):
1. Augment the crontab file for the pcp user. For example:
crontab -l -u pcp > ${HOME}/crontab.txt
2. Edit ${HOME}/crontab.txt, adding lines similar to those from the sample ${PCP_VAR_DIR}/
config/pmlogger/crontab file for pmlogger_daily and pmlogger_check; for
example:
# daily processing of archive logs
10
0
*
*
*
${PCP_BINADM_DIR}/pmlogger_daily
# every 30 minutes, check pmlogger instances are running
25,55 *
*
*
*
${PCP_BINADM_DIR}/pmlogger_check

Archive Logging

3. Make these changes permanent with this command:
crontab -u pcp < ${HOME}/crontab.txt

Other Archive Logging Features and Services
Other archive logging features and services include PCP archive folios, manipulating archive logs, primary
logger, and using pmlc.

PCP Archive Folios
A collection of one or more sets of PCP archive logs may be combined with a control file to produce a
PCP archive folio. Archive folios are created using either mkaf or the interactive record mode services
of various PCP monitor tools (e.g. pmchart and pmrep).
The automated archive log management services also create an archive folio named Latest for
each managed pmlogger instance, to provide a symbolic name to the most recent archive log. With
reference to Figure 6.1, “Archive Log Directory Structure”, this would mean the creation of the
folios ${PCP_LOG_DIR}/pmlogger/one/Latest and ${PCP_LOG_DIR}/pmlogger/two/
Latest.
The pmafm utility is completely described in the pmafm(1) man page, and provides the interactive
commands (single commands may also be executed from the command line) for the following services:
• Checking the integrity of the archives in the folio.
• Displaying information about the component archives.
• Executing PCP tools with their source of performance metrics assigned concurrently to all of the
component archives (where the tool supports this), or serially executing the PCP tool once per
component archive.
• If the folio was created by a single PCP monitoring tool, replaying all of the archives in the folio with
that monitoring tool.
• Restricting the processing to particular archives, or the archives associated with particular hosts.

Manipulating Archive Logs with pmlogextract
The pmlogextract tool takes a number of PCP archive logs from a single host and performs the
following tasks:
• Merges the archives into a single log, while maintaining the correct time stamps for all values.
• Extracts all metric values within a temporal window that could encompass several archive logs.
• Extracts only a configurable subset of metrics from the archive logs.
See the pmlogextract(1) man page for full information on this command.

Summarizing Archive Logs with pmlogsummary
The pmlogsummary tool provides statistical summaries of archives, or specific metrics within archives,
or specific time windows of interest in a set of archives. These summaries include various averages,
minima, maxima, sample counts, histogram bins, and so on.

Archive Logging

As an example, for Linux host pluto, report on its use of anonymous huge pages - average use, maximum,
time at which maximum occured, total number of samples in the set of archives, and the units used for the
values - as shown in Example 6.2, “Using pmlogsummary to Summarize Archive Information”:

Example 6.2. Using pmlogsummary to Summarize Archive Information
pmlogsummary -MIly ${PCP_LOG_DIR}/pmlogger/pluto/20170815 mem.util.anonhugepages
Performance metrics from host pluto
commencing Thu Aug 15 00:10:12.318 2017
ending
Fri Aug 16 00:10:12.299 2017
mem.util.anonhugepages

7987742.326 8116224.000 15:02:12.300 1437 Kbyte

pminfo -t mem.util.anonhugepages
mem.util.anonhugepages [amount of memory in anonymous huge pages]
See the pmlogsummary(1) man page for detailed information about this commands many options.

Primary Logger
On each system for which PMCD is active (each PCP collector system), there is an option to have a
distinguished instance of the archive logger pmlogger (the “primary” logger) launched each time PMCD
is started. This may be used to ensure the creation of minimalist archive logs required for ongoing system
management and capacity planning in the event of failure of a system where a remote pmlogger may be
running, or because the preferred archive logger deployment is to activate pmlogger on each PCP collector
system.
Run the following command as superuser on each PCP collector system where you want to activate the
primary pmlogger:
chkconfig pmlogger on
The primary logger launches the next time the ${PCP_RC_DIR}/pmlogger start script runs. If you wish
this to happen immediately, follow up with this command:
${PCP_BINADM_DIR}/pmlogger_check -V
When it is started in this fashion, the ${PCP_PMLOGGERCONTROL_PATH} file (or one of the
${PCP_PMLOGGERCONTROL_PATH}.d files) must use the second field of one configuration
line to designate the primary logger, and usually will also use the pmlogger configuration file
${PCP_SYSCONF_DIR}/pmlogger/config.default (although the latter is not mandatory).

Using pmlc
You may tailor pmlogger dynamically with the pmlc command (if it is configured to allow access to
this functionality). Normally, the pmlogger configuration is read at startup. If you choose to modify the
config file to change the parameters under which pmlogger operates, you must stop and restart the
program for your changes to have effect. Alternatively, you may change parameters whenever required
by using the pmlc interface.
To run the pmlc tool, enter:
pmlc
By default, pmlc acts on the primary instance of pmlogger on the current host. See the pmlc(1) man page
for a description of command line options. When it is invoked, pmlc presents you with a prompt:

Archive Logging

pmlc>
You may obtain a listing of the available commands by entering a question mark (?) and pressing Enter.
You see output similar to that in Example 6.3, “Listing Available Commands ”:

Example 6.3. Listing Available Commands
show loggers [@]
display s of running pmloggers
connect _logger_id [@]
connect to designated pmlogger
status
information about connected pmlogger
query metric-list
show logging state of metrics
new volume
start a new log volume
flush
flush the log buffers to disk
log { mandatory | advisory } on _metric-list
log { mandatory | advisory } off _metric-list
log mandatory maybe _metric-list
timezone local|logger|'' change reporting timezone
help
print this help message
quit
exit from pmlc
_logger_id
is primary | | port
_metric-list is _metric-spec | { _metric-spec ... }
_metric-spec is | [ ... ]
Here is an example:
pmlc
pmlc> show loggers @babylon
The following pmloggers are running on babylon:
primary (1892)
pmlc> connect 1892 @babylon
pmlc> log advisory on 2 secs disk.dev.read
pmlc> query disk.dev
disk.dev.read
adv on nl
5 min [131073 or “disk1”]
adv on nl
5 min [131074 or “disk2”]
pmlc> quit

Note
Any changes to the set of logged metrics made via pmlc are not saved, and are lost the next time
pmlogger is started with the same configuration file. Permanent changes are made by modifying
the pmlogger configuration file(s).
Refer to the pmlc(1) and pmlogger(1) man pages for complete details.

Archive Logging Troubleshooting
The following issues concern the creation and use of logs using pmlogger.

pmlogger Cannot Write Log
Symptom:

The pmlogger utility does not start, and you see this message:
__pmLogNewFile: “foo.index” already exists, not over-written

Archive Logging

Cause:

Archive logs are considered sufficiently precious that pmlogger does not
empty or overwrite an existing set of archive log files. The log named foo
actually consists of the physical file foo.index, foo.meta, and at least
one file foo.N, where N is in the range 0, 1, 2, 3, and so on.
A message similar to the one above is produced when a new pmlogger instance
encounters one of these files already in existence.

Resolution:

Move the existing archive aside, or if you are sure, remove all of the parts of
the archive log. For example, use the following command:
rm -f foo.*
Then rerun pmlogger.

Cannot Find Log
Symptom:

The pmdumplog utility, or any tool that can read an archive log, displays this
message:
Cannot open archive mylog: No such file or directory

Cause:

An archive consists of at least three physical files. If the base name for the
archive is mylog, then the archive actually consists of the physical files
mylog.index, mylog.meta, and at least one file mylog.N, where N is
in the range 0, 1, 2, 3, and so on.
The above message is produced if one or more of the files is missing.

Resolution:

Use this command to check which files the utility is trying to open:
ls mylog.*
Turn on the internal debug flag DBG_TRACE_LOG (-D 128) to see which files
are being inspected by the pmOpenLog routine as shown in the following
example:
pmdumplog -D 128 -l mylog
Locate the missing files and move them all to the same directory, or remove
all of the files that are part of the archive, and recreate the archive log.

Primary pmlogger Cannot Start
Symptom:

The primary pmlogger cannot be started. A message like the following
appears:
pmlogger: there is already a primary pmlogger running

Cause:

There is either a primary pmlogger already running, or the previous primary
pmlogger was terminated unexpectedly before it could perform its cleanup
operations.

Resolution:

If there is already a primary pmlogger running and you wish to replace it with
a new pmlogger, use the show command in pmlc to determine the process ID
of the primary pmlogger. The process ID of the primary pmlogger appears in

Archive Logging

parentheses after the word “primary.” Send a SIGINT signal to the process
to shut it down (use either the kill command if the platform supports it, or
the pmsignal command). If the process does not exist, proceed to the manual
cleanup described in the paragraph below. If the process did exist, it should
now be possible to start the new pmlogger.
If pmlc's show command displays a process ID for a process that does not
exist, a pmlogger process was terminated before it could clean up. If it was
the primary pmlogger, the corresponding control files must be removed before
one can start a new primary pmlogger. It is a good idea to clean up any spurious
control files even if they are not for the primary pmlogger.
The control files are kept in ${PCP_TMP_DIR}/pmlogger. A control file
with the process ID of the pmlogger as its name is created when the pmlogger
is started. In addition, the primary pmlogger creates a symbolic link named
primary to its control file.
For the primary pmlogger, remove both the symbolic link and the file
(corresponding to its process ID) to which the link points. For other pmloggers,
remove just the process ID file. Do not remove any other files in the directory.
If the control file for an active pmlogger is removed, pmlc is not able to contact
it.

Identifying an Active pmlogger Process
Symptom:

You have a PCP archive log that is demonstrably growing, but do not know
the identify of the associated pmlogger process.

Cause:

The PID is not obvious from the log, or the archive name may not be obvious
from the output of the ps command.

Resolution:

If the archive basename is foo, run the following commands:
pmdumplog -l foo
Log Label (Log Format Version 1)
Performance metrics from host gonzo
commencing Wed Aug 7 00:10:09.214 1996
ending
Wed Aug 7 16:10:09.155 1996

pminfo -a foo -f pmcd.pmlogger
pmcd.pmlogger.host
inst [10728 or "10728"] value "gonzo"
pmcd.pmlogger.port
inst [10728 or "10728"] value 4331
pmcd.pmlogger.archive
inst [10728 or "10728"] value "/usr/var/adm/pcplog/gonzo/fo
All of the information describing the creator of the archive is revealed and, in
particular, the instance identifier for the PMCD metrics (10728 in the example
above) is the PID of the pmlogger instance, which may be used to control the
process via pmlc.

Illegal Label Record
Symptom:

PCP tools report:

Archive Logging

Illegal label record at start of PCP archive log file.
Cause:

The label record at the start of each of the physical archive log files has become
either corrupted or one is out of sync with the others.

Resolution:

If you believe the log may have been corrupted, this can be verified using
pmlogcheck. If corruption is limited to just the label record at the start, the
pmloglabel can be used to force the labels back in sync with each other, with
known-good values that you supply.
Refer to the pmlogcheck(1) and pmloglabel(1) man pages.

Empty Archive Log Files or pmlogger Exits Immediately
Symptom:

Archive log files are zero size, requested metrics are not being logged, or
pmlogger exits immediately with no error messages.

Cause:

Either pmlogger encountered errors in the configuration file, has not flushed
its output buffers yet, or some (or all) metrics specified in the pmlogger
configuration file have had their state changed to advisory off or mandatory
off via pmlc. It is also possible that the logging interval specified in the
pmlogger configuration file for some or all of the metrics is longer than the
period of time you have been waiting since pmlogger started.

Resolution:

If pmlogger exits immediately with no error messages, check the
pmlogger.log file in the directory pmlogger was started in for any error
messages. If pmlogger has not yet flushed its buffers, enter one of the
following commands (depending on platform support):
killall -SIGUSR1 pmlogger
${PCP_BINADM_DIR}/pmsignal -a -s USR1 pmlogger
Otherwise, use the status command for pmlc to interrogate the internal
pmlogger state of specific metrics.

Chapter 7. Performance Co-Pilot
Deployment Strategies
Table of Contents
Basic Deployment .............................................................................................................
PCP Collector Deployment .................................................................................................
Principal Server Deployment .......................................................................................
Quality of Service Measurement ..................................................................................
PCP Archive Logger Deployment ........................................................................................
Deployment Options ..................................................................................................
Resource Demands for the Deployment Options .............................................................
Operational Management ............................................................................................
Exporting PCP Archive Logs ......................................................................................
PCP Inference Engine Deployment ......................................................................................
Deployment Options ..................................................................................................
Resource Demands for the Deployment Options .............................................................
Operational Management ............................................................................................

86
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87
88
88
88
88
89
89
89
90

Performance Co-Pilot (PCP) is a coordinated suite of tools and utilities allowing you to monitor
performance and make automated judgments and initiate actions based on those judgments. PCP is
designed to be fully configurable for custom implementation and deployed to meet specific needs in a
variety of operational environments.
Because each enterprise and site is different and PCP represents a new way of managing performance
information, some discussion of deployment strategies is useful.
The most common use of performance monitoring utilities is a scenario where the PCP tools are executed
on a workstation (the PCP monitoring system), while the interesting performance data is collected on
remote systems (PCP collector systems) by a number of processes, specifically the Performance Metrics
Collection Daemon (PMCD) and the associated Performance Metrics Domain Agents (PMDAs). These
processes can execute on both the monitoring system and one or more collector systems, or only on
collector systems. However, collector systems are the real objects of performance investigations.
The material in this chapter covers the following areas:
• the section called “Basic Deployment”, presents the spectrum of deployment architectures at the highest
level.
• the section called “PCP Collector Deployment”, describes alternative deployments for PMCD and the
PMDAs.
• the section called “PCP Archive Logger Deployment”, covers alternative deployments for the pmlogger
tool.
• the section called “PCP Inference Engine Deployment”, presents the options that are available for
deploying the pmie tool.
The options shown in this chapter are merely suggestions. They are not comprehensive, and are intended to
demonstrate some possible ways of deploying the PCP tools for specific network topologies and purposes.
You are encouraged to use them as the basis for planning your own deployment, consistent with your needs.

Performance Co-Pilot
Deployment Strategies

Basic Deployment
In the simplest PCP deployment, one system is configured as both a collector and a monitor, as shown
in Figure 7.1, “PCP Deployment for a Single System”. Because some of the PCP monitor tools make
extensive use of visualization, this suggests the monitor system should be configured with a graphical
display.

Figure 7.1. PCP Deployment for a Single System

However, most PCP deployments involve at least two systems. For example, the setup shown in Figure 7.2,
“Basic PCP Deployment for Two Systems” would be representative of many common scenarios.

Figure 7.2. Basic PCP Deployment for Two Systems

But the most common site configuration would include a mixture of systems configured as PCP collectors,
as PCP monitors, and as both PCP monitors and collectors, as shown in Figure 7.3, “General PCP
Deployment for Multiple Systems ”.
With one or more PCP collector systems and one or more PCP monitor systems, there are a number
of decisions that need to be made regarding the deployment of PCP services across multiple hosts. For
example, in Figure 7.3, “General PCP Deployment for Multiple Systems ” there are several ways in which
both the inference engine (pmie) and the PCP archive logger (pmlogger) could be deployed. These options
are discussed in the following sections of this chapter.

Figure 7.3. General PCP Deployment for Multiple Systems

PCP Collector Deployment
Each PCP collector system must have an active pmcd and, typically, a number of PMDAs installed.

Principal Server Deployment
The first hosts selected as PCP collector systems are likely to provide some class of service deemed to be
critical to the information processing activities of the enterprise. These hosts include:
• Database servers
• Web servers for an Internet or Intranet presence
• NFS or other central storage server
• A video server
• A supercomputer
• An infrastructure service provider, for example, print, DNS, LDAP, gateway, firewall, router, or mail
services
• Any system running a mission-critical application

Performance Co-Pilot
Deployment Strategies
Your objective may be to improve quality of service on a system functioning as a server for many clients.
You wish to identify and repair critical performance bottlenecks and deficiencies in order to maintain
maximum performance for clients of the server.
For some of these services, the PCP base product or the PCP add-on packages provide the necessary
collector components. Others would require customized PMDA development, as described in the
companion Performance Co-Pilot Programmer's Guide.

Quality of Service Measurement
Applications and services with a client-server architecture need to monitor performance at both the server
side and the client side.
The arrangement in Figure 7.4, “PCP Deployment to Measure Client-Server Quality of Service” illustrates
one way of measuring quality of service for client-server applications.

Figure 7.4. PCP Deployment to Measure Client-Server Quality of Service

The configuration of the PCP collector components on the Application Server System is standard. The
new facility is the deployment of some PCP collector components on the Application Client System; this
uses a customized PMDA and a generalization of the ICMP “ping” tool as follows:
• The Client App is specially developed to periodically make typical requests of the App Server,
and to measure the response time for these requests (this is an application-specific “ping”).
• The PMDA on the Application Client System captures the response time measurements from the
Client App and exports these into the PCP framework.
At the PCP monitor system, the performance of the system running the App Server and the end-user
quality of service measurements from the system where the Client App is running can be monitored
concurrently.
PCP contains a number of examples of this architecture, including the shping PMDA for IP-based
services (including HTTP), and the dbping PMDA for database servers.
The source code for each of these PMDAs is readily available; users and administrators are encouraged to
adapt these agents to the needs of the local application environment.
It is possible to exploit this arrangement even further, with these methods:
• Creating new instances of the Client App and PMDA to measure service quality for your own
mission-critical services.
• Deploying the Client App and associated PCP collector components in a number of strategic hosts
allows the quality of service over the enterprise's network to be monitored. For example, service can
be monitored on the Application Server System, on the same LAN segment as the Application Server
System, on the other side of a firewall system, or out in the WAN.

PCP Archive Logger Deployment
PCP archive logs are created by the pmlogger utility, as discussed in Chapter 6, Archive Logging.
They provide a critical capability to perform retrospective performance analysis, for example, to detect

Performance Co-Pilot
Deployment Strategies
performance regressions, for problem analysis, or to support capacity planning. The following sections
discuss the options and trade-offs for pmlogger deployment.

Deployment Options
The issue is relatively simple and reduces to “On which host(s) should pmlogger be running?” The options
are these:
• Run pmlogger on each PCP collector system to capture local performance data.
• Run pmlogger on some of the PCP monitor systems to capture performance data from remote PCP
collector systems.
• As an extension of the previous option, designate one system to act as the PCP archive site to run all
pmlogger instances. This arrangement is shown in Figure 7.5, “Designated PCP Archive Site”.

Figure 7.5. Designated PCP Archive Site

Resource Demands for the Deployment Options
The pmlogger process is very lightweight in terms of computational demand; most of the (very small)
CPU cost is associated with extracting performance metrics at the PCP collector system (PMCD and the
PMDAs), which are independent of the host on which pmlogger is running.
A local pmlogger consumes disk bandwidth and disk space on the PCP collector system. A remote
pmlogger consumes disk space on the site where it is running and network bandwidth between that host
and the PCP collector host.
The archive logs typically grow at a rate of anywhere between a few kilobytes (KB) to tens of megabytes
(MB) per day, depending on how many performance metrics are logged and the choice of sampling
frequencies. There are some advantages in minimizing the number of hosts over which the disk resources
for PCP archive logs must be allocated; however, the aggregate requirement is independent of where the
pmlogger processes are running.

Operational Management
There is an initial administrative cost associated with configuring each pmlogger instance, and an ongoing
administrative investment to monitor these configurations, perform regular housekeeping (such as rotation,
compression, and culling of PCP archive log files), and execute periodic tasks to process the archives (such
as nightly performance regression checking with pmie).
Many of these tasks are handled by the supplied pmlogger administrative tools and scripts, as described
in the section called “Archive Log File Management”. However, the necessity and importance of these
tasks favor a centralized pmlogger deployment, as shown in Figure 7.5, “Designated PCP Archive Site”.

Exporting PCP Archive Logs
Collecting PCP archive logs is of little value unless the logs are processed as part of the ongoing
performance monitoring and management functions. This processing typically involves the use of the tools
on a PCP monitor system, and hence the archive logs may need to be read on a host different from the
one they were created on.

Performance Co-Pilot
Deployment Strategies
NFS mounting is obviously an option, but the PCP tools support random access and both forward and
backward temporal motion within an archive log. If an archive is to be subjected to intensive and interactive
processing, it may be more efficient to copy the files of the archive log to the PCP monitor system first.

Note
Each PCP archive log consists of at least three separate files (see the section called “Archive Log
File Management” for details). You must have concurrent access to all of these files before a PCP
tool is able to process an archive log correctly.

PCP Inference Engine Deployment
The pmie utility supports automated reasoning about system performance, as discussed in Chapter 5,
Performance Metrics Inference Engine, and plays a key role in monitoring system performance for both
real-time and retrospective analysis, with the performance data being retrieved respectively from a PCP
collector system and a PCP archive log.
The following sections discuss the options and trade-offs for pmie deployment.

Deployment Options
The issue is relatively simple and reduces to “On which host(s) should pmie be running?” You must
consider both real-time and retrospective uses, and the options are as follows:
• For real-time analysis, run pmie on each PCP collector system to monitor local system performance.
• For real-time analysis, run pmie on some of the PCP monitor systems to monitor the performance of
remote PCP collector systems.
• For retrospective analysis, run pmie on the systems where the PCP archive logs reside. The problem then
reduces to pmlogger deployment as discussed in the section called “PCP Archive Logger Deployment”.
• As an example of the “distributed management with centralized control” philosophy, designate some
system to act as the PCP Management Site to run all pmlogger and pmie instances. This arrangement
is shown in Figure 7.6, “PCP Management Site Deployment”.
One pmie instance is capable of monitoring multiple PCP collector systems; for example, to evaluate
some universal rules that apply to all hosts. At the same time a single PCP collector system may be
monitored by multiple pmie instances; for example, for site-specific and universal rule evaluation, or
to support both tactical performance management (operations) and strategic performance management
(capacity planning). Both situations are depicted in Figure 7.6, “PCP Management Site Deployment”.

Figure 7.6. PCP Management Site Deployment

Resource Demands for the Deployment Options
Depending on the complexity of the rule sets, the number of hosts being monitored, and the evaluation
frequency, pmie may consume CPU cycles significantly above the resources required to simply fetch the
values of the performance metrics. If this becomes significant, then real-time deployment of pmie away
from the PCP collector systems should be considered in order to avoid the “you're part of the problem, not
the solution” scenario in terms of CPU utilization on a heavily loaded server.

Performance Co-Pilot
Deployment Strategies

Operational Management
An initial administrative cost is associated with configuring each pmie instance, particularly in the
development of the rule sets that accurately capture and classify “good” versus “bad” performance in
your environment. These rule sets almost always involve some site-specific knowledge, particularly
in respect to the “normal” levels of activity and resource consumption. The pmieconf tool (see the
section called “Creating pmie Rules with pmieconf”) may be used to help develop localized rules based
upon parameterized templates covering many common performance scenarios. In complex environments,
customizing these rules may occur over an extended period and require considerable performance analysis
insight.
One of the functions of pmie provides for continual detection of adverse performance and the automatic
generation of alarms (visible, audible, e-mail, pager, and so on). Uncontrolled deployment of this alarm
initiating capability throughout the enterprise may cause havoc.
These considerations favor a centralized pmie deployment at a small number of PCP monitor sites, or in
a PCP Management Site as shown in Figure 7.6, “PCP Management Site Deployment”.
However, it is most likely that knowledgeable users with specific needs may find a local deployment of
pmie most useful to track some particular class of service difficulty or resource utilization. In these cases,
the alarm propagation is unlikely to be required or is confined to the system on which pmie is running.
Configuration and management of a number of pmie instances is made much easier with the scripts and
control files described in the section called “Management of pmie Processes”.

Chapter 8. Customizing and Extending
PCP Services
Table of Contents
PMDA Customization ........................................................................................................
Customizing the Summary PMDA ...............................................................................
PCP Tool Customization ....................................................................................................
Archive Logging Customization ..................................................................................
Inference Engine Customization ..................................................................................
PMNS Management ...........................................................................................................
PMNS Processing Framework .....................................................................................
PMNS Syntax ...........................................................................................................
PMDA Development .........................................................................................................
PCP Tool Development ......................................................................................................

91
91
94
94
95
96
97
97
98
98

Performance Co-Pilot (PCP) has been developed to be fully extensible. The following sections summarize
the various facilities provided to allow you to extend and customize PCP for your site:
• the section called “PMDA Customization”, describes the procedure for customizing the summary
PMDA to export derived metrics formed by aggregation of base PCP metrics from one or more collector
hosts.
• the section called “PCP Tool Customization”, describes the various options available for customizing
and extending the basic PCP tools.
• the section called “PMNS Management”, covers the concepts and tools provided for updating the PMNS
(Performance Metrics Name Space).
• the section called “PMDA Development”, details where to find further information to assist in the
development of new PMDAs to extend the range of performance metrics available through the PCP
infrastructure.
• the section called “PCP Tool Development”, outlines how new tools may be developed to process
performance data from the PCP infrastructure.

PMDA Customization
The generic procedures for installing and activating the optional PMDAs have been described in the section
called “Managing Optional PMDAs”. In some cases, these procedures prompt the user for information
based upon the local system or network configuration, application deployment, or processing profile to
customize the PMDA and hence the performance metrics it exports.
The summary PMDA is a special case that warrants further discussion.

Customizing the Summary PMDA
The summary PMDA exports performance metrics derived from performance metrics made available by
other PMDAs. It is described completely in the pmdasummary(1) man page.

Customizing and
Extending PCP Services
The summary PMDA consists of two processes:
pmie process

Periodically samples the base metrics and compute values for the derived
metrics. This dedicated instance of the PCP pmie inference engine is
launched with special command line arguments by the main process. See
the section called “Introduction to pmie”, for a complete discussion of the
pmie feature set.

main process

Reads and buffers the values computed by the pmie process and makes them
available to the Performance Metrics Collection Daemon (PMCD).

All of the metrics exported by the summary PMDA have a singular instance and the values are
instantaneous; the exported value is the correct value as of the last time the corresponding expression was
evaluated by the pmie process.
The summary PMDA resides in the ${PCP_PMDAS_DIR}/summary directory and may be installed
with a default configuration by following the steps described in the section called “PMDA Installation on
a PCP Collector Host”.
Alternatively, you may customize the summary PMDA to export your own derived performance metrics
by following the steps in Procedure 8.1, “Customizing the Summary PMDA”:

Procedure 8.1. Customizing the Summary PMDA
1.

Check that the symbolic constant SYSSUMMARY is defined in the ${PCP_VAR_DIR}/pmns/
stdpmid file. If it is not, perform the postinstall update of this file, as superuser:
cd ${PCP_VAR_DIR}/pmns ./Make.stdpmid

Choose Performance Metric Name Space (PMNS) names for the new metrics. These must begin with
summary and follow the rules described in the pmns(5) man page. For example, you might use
summary.fs.cache_write and summary.fs.cache_hit.

Edit the pmns file in the ${PCP_PMDAS_DIR}/summary directory to add the new metric names
in the format described in the pmns(5) man page. You must choose a unique performance metric
identifier (PMID) for each metric. In the pmns file, these appear as SYSSUMMARY:0:x. The value
of x is arbitrary in the range 0 to 1023 and unique in this file. Refer to the section called “PMNS
Management”, for a further explanation of the rules governing PMNS updates.
For example:
summary {
cpu
disk
netif
fs
}
summary.fs {
cache_write
cache_hit
}

/*new*/

SYSSUMMARY:0:10
SYSSUMMARY:0:11

Use the local test PMNS root and validate that the PMNS changes are correct.
For example, enter this command:
92

Customizing and
Extending PCP Services
pminfo -n root -m summary.fs
You see output similar to the following:
summary.fs.cache_write PMID: 27.0.10
summary.fs.cache_hit PMID: 27.0.11
5.

Edit the ${PCP_PMDAS_DIR}/summary/expr.pmie file to add new pmie expressions. If the
name to the left of the assignment operator (=) is one of the PMNS names, then the pmie expression
to the right will be evaluated and returned by the summary PMDA. The expression must return a
numeric value. Additional description of the pmie expression syntax may be found in the section
called “Specification Language for pmie”.
For example, consider this expression:
// filesystem buffer cache hit percentages
prefix = "kernel.all.io";
// macro, not exported
summary.fs.cache_write =
100 - 100 * $prefix.bwrite / $prefix.lwrite;
summary.fs.cache_hit =
100 - 100 * $prefix.bread / $prefix.lread;

Run pmie in debug mode to verify that the expressions are being evaluated correctly, and the values
make sense.
For example, enter this command:
pmie -t 2sec -v expr.pmie
You see output similar to the following:
summary.fs.cache_write:
?
summary.fs.cache_hit:
?
summary.fs.cache_write: 45.83
summary.fs.cache_hit:
83.2
summary.fs.cache_write: 39.22
summary.fs.cache_hit: 84.51

Install the new PMDA.
From the ${PCP_PMDAS_DIR}/summary directory, use this command:
./Install
You see the following output:
Interval between summary expression evaluation (seconds)? [10] 10
Updating the Performance Metrics Name Space...
Installing pmchart view(s) ...
Terminate PMDA if already installed ...
Installing files ..
Updating the PMCD control file, and notifying PMCD ...
Wait 15 seconds for the agent to initialize ...
Check summary metrics have appeared ... 8 metrics and 8 values

Check the metrics.

Customizing and
Extending PCP Services
For example, enter this command:
pmval -t 5sec -s 8 summary.fs.cache_write
You see a response similar to the following:
metric:
summary.fs.cache_write
host:
localhost
semantics: instantaneous value
units:
none
samples:
8
interval: 5.00 sec
63.60132158590308
62.71878646441073
62.71878646441073
58.73968492123031
58.73968492123031
65.33822758259046
65.33822758259046
72.6099706744868
Note that the values are being sampled here by pmval every 5 seconds, but pmie is passing only new
values to the summary PMDA every 10 seconds. Both rates could be changed to suit the dynamics
of your new metrics.
9.

You may now create pmchart views, pmie rules, and pmlogger configurations to monitor and
archive your new performance metrics.

PCP Tool Customization
Performance Co-Pilot (PCP) has been designed and implemented with a philosophy that embraces the
notion of toolkits and encourages extensibility.
In most cases, the PCP tools provide orthogonal services, based on external configuration files. It is the
creation of new and modified configuration files that enables PCP users to customize tools quickly and
meet the needs of the local environment, in many cases allowing personal preferences to be established
for individual users on the same PCP monitor system.
The material in this section is intended to act as a checklist of pointers to detailed documentation found
elsewhere in this guide, in the man pages, and in the files that are made available as part of the PCP
installation.

Archive Logging Customization
The PCP archive logger is presented in Chapter 6, Archive Logging, and documented in the pmlogger(1)
man page.
The following global files and directories influence the behavior of pmlogger:
Enable/disable state for the primary logger
facility using this command:

${PCP_SYSCONF_DIR}/pmlogger

chkconfig pmlogger on

Customizing and
Extending PCP Services
${PCP_SYSCONF_DIR}/pmlogger/
config.default

The default pmlogger configuration file that
is used for the primary logger when this
facility is enabled.

${PCP_VAR_DIR}/config/pmlogconf/tools

Every PCP tool with a fixed group
of
performance
metrics
contributes
a pmlogconf configuration file that
includes each of the performance
metrics
used
in
the
tool,
for
example, ${PCP_VAR_DIR}/config/
pmlogconf/pmstat for pmstat.

${PCP_PMLOGGERCONTROL_PATH} or
${PCP_PMLOGGERCONTROL_PATH}.d files

Defines which PCP collector hosts require
pmlogger to be launched on the local host,
where the configuration file comes from,
where the archive log files should be created,
and pmlogger startup options.
These control files support the starting and
stopping of multiple pmlogger instances that
monitor local or remote hosts.

/etc/cron.d/pcp-pmlogger or
${PCP_VAR_DIR}/config/pmlogger/crontab

Default crontab entries that may be
merged with the crontab entries for the
pcp user to schedule the periodic execution
of the archive log management scripts, for
example, pmlogger_daily.

${PCP_LOG_DIR}/pmlogger/somehost

The default behavior of the archive log
management scripts create archive log files
for the host somehost in this directory.

${PCP_LOG_DIR}/pmlogger/somehost/
Latest

A PCP archive folio for the most recent
archive for the host somehost. This folio is
created and maintained by the cron-driven
periodic archive log management scripts,
for example, pmlogger_check. Archive
folios may be processed with the pmafm tool.

Inference Engine Customization
The PCP inference engine is presented in Chapter 5, Performance Metrics Inference Engine, and
documented in the pmie(1) man page.
The following global files and directories influence the behavior of pmie:
Controls the pmie daemon facility. Enable
using this command:

${PCP_SYSCONF_DIR}/pmie

chkconfig pmie on
${PCP_SYSCONF_DIR}/pmie/config.default

The pmie configuration file that is used for
monitoring the local host when the pmie
daemon facility is enabled in the default

Customizing and
Extending PCP Services
configuration. This file is created using
pmieconf the first time the daemon facility is
activated.
${PCP_PMIECONTROL_PATH} and
${PCP_PMIECONTROL_PATH}.d files

Defines which PCP collector hosts require a
daemon pmie to be monitoring from the local
host, where the configuration files comes
from, where the pmie log file should be
created, and pmie startup options.
These control files support the starting and
stopping of multiple pmie instances that are
each monitoring one or more hosts.

${PCP_VAR_DIR}/config/pmieconf/*/*

Each pmieconf rule definition can be found
below one of these subdirectories.

/etc/cron.d/pcp-pmie or ${PCP_VAR_DIR}/
config/pmie/crontab

Default crontab entries that may be
merged with the crontab entries for the
pcp user to schedule the periodic execution
of the pmie_check and pmie_daily scripts,
for verifying that pmie instances are running
and logs rotated.

${PCP_LOG_DIR}/pmie/somehost

The
default
behavior
of
the
${PCP_RC_DIR}/pmie startup scripts
create pmie log files for the host somehost
in this directory.

pmie_check and pmie_daily

These commands are similar to the
pmlogger support scripts, pmlogger_check
and pmlogger_daily.

${PCP_TMP_DIR}/pmie

The statistics that pmie gathers are
maintained in binary data structure files.
These files can be found in the
${PCP_TMP_DIR}/pmie directory.

pmcd.pmie metrics

The PMCD PMDA exports information about
executing pmie processes and their progress
in terms of rule evaluations and action
execution rates.
If pmie is running on a system with a
PCP collector deployment, the pmcd PMDA
exports these metrics via the pmcd.pmie
group of metrics.

PMNS Management
This section describes the syntax, semantics, and processing framework for the external specification
of a Performance Metrics Name Space (PMNS) as it might be loaded by the PMAPI routine
pmLoadNameSpace; see the pmLoadNameSpace(3) man page. This is usually done only by pmcd,
except in rare circumstances such as the section called “Customizing the Summary PMDA”.
96

Customizing and
Extending PCP Services
The PMNS specification is a simple text source file that can be edited easily. For reasons of efficiency,
a binary format is also supported; the utility pmnscomp translates the ASCII source format into binary
format; see the pmnscomp(1) man page.

PMNS Processing Framework
The PMNS specification is initially passed through pmcpp(1). This means the following facilities may
be used in the specification:
• C-style comments
• #include directives
• #define directives and macro substitution
• Conditional processing with #ifdef, #ifndef, #endif, and #undef
When pmcpp(1) is executed, the standard include directories are the current directory and
${PCP_VAR_DIR}/pmns, where some standard macros and default specifications may be found.

PMNS Syntax
Every PMNS is tree structured. The paths to the leaf nodes are the performance metric names. The general
syntax for a non-leaf node in PMNS is as follows:
pathname {
name
...
}

[pmid]

Here pathname is the full pathname from the root of the PMNS to this non-leaf node, with each
component in the path separated by a period. The root node for the PMNS has the special name root, but
the prefix string root. must be omitted from all other pathnames.
For example, refer to the PMNS shown in Figure 8.1, “Small Performance Metrics Name Space
(PMNS)”. The correct pathname for the rightmost non-leaf node is cpu.utilization, not
root.cpu.utilization.

Figure 8.1. Small Performance Metrics Name Space (PMNS)

Each component in the pathname must begin with an alphabetic character and be followed by zero or
more alphanumeric characters or the underscore (_) character. For alphabetic characters in a component,
uppercase and lowercase are significant.
Non-leaf nodes in the PMNS may be defined in any order desired. The descendent nodes are defined by
the set of names, relative to the pathname of their parent non-leaf node. For descendent nodes, leaf nodes
have a pmid specification, but non-leaf nodes do not.
The syntax for the pmid specification was chosen to help manage the allocation of Performance Metric
IDs (PMIDs) across disjoint and autonomous domains of administration and implementation. Each pmid
consists of three integers separated by colons, for example, 14:27:11. This is intended to mirror the
implementation hierarchy of performance metrics. The first integer identifies the domain in which the
performance metric lies. Within a domain, related metrics are often grouped into clusters. The second
integer identifies the cluster, and the third integer, the metric within the cluster.

Customizing and
Extending PCP Services
The PMNS specification for Figure 8.1, “Small Performance Metrics Name Space (PMNS)” is shown in
Example 8.1, “PMNS Specification”:

Example 8.1. PMNS Specification
/*
* PMNS Specification
*/
#define KERNEL 1
root {
network
cpu
}
#define NETWORK 26
network {
interrupts
KERNEL:NETWORK:1
packets
}
network.packets {
in
KERNEL:NETWORK:35
out
KERNEL:NETWORK:36
}
#define CPU 10
cpu {
syscalls
KERNEL:CPU:10
utilization
}
#define USER 20
#define SYSTEM 21
#define IDLE 22
cpu.utilization {
user
KERNEL:CPU:USER
sys
KERNEL:CPU:SYSTEM
idle
KERNEL:CPU:IDLE
}
For complete documentation of the PMNS and associated utilities, see the pmns(5), pmnsadd(1),
pmnsdel(1) and pmnsmerge(1) man pages.

PMDA Development
Performance Co-Pilot (PCP) is designed to be extensible at the collector site.
Application developers are encouraged to create new PMDAs to export performance metrics from the
applications and service layers that are particularly relevant to a specific site, application suite, or
processing environment.
These PMDAs use the routines of the libpcp_pmda library, which is discussed in detail in the
Performance Co-Pilot Programmer's Guide.

PCP Tool Development
Performance Co-Pilot (PCP) is designed to be extensible at the monitor site.

Customizing and
Extending PCP Services
Application developers are encouraged to create new PCP client applications to monitor or display
performance metrics in a manner that is particularly relevant to a specific site, application suite, or
processing environment.
Client applications use the routines of the PMAPI (performance metrics application programming
interface) described in the Performance Co-Pilot Programmer's Guide. At the time of writing, native
PMAPI interfaces are available for the C, C++ and Python languages.

Appendix A. Acronyms
Table A.1, “Performance Co-Pilot Acronyms and Their Meanings ” provides a list of the acronyms used
in the Performance Co-Pilot (PCP) documentation, help cards, man pages, and user interface.

Table A.1. Performance Co-Pilot Acronyms and Their Meanings
Acronym

Meaning

API

Application Programming Interface

DBMS

Database Management System

DNS

Domain Name Service

DSO

Dynamic Shared Object

I/O

Input/Output

IPC

Interprocess Communication

PCP

Performance Co-Pilot

PDU

Protocol data unit

PMAPI

Performance Metrics Application Programming Interface

PMCD

Performance Metrics Collection Daemon

PMD

Performance Metrics Domain

PMDA

Performance Metrics Domain Agent

PMID

Performance Metric Identifier

PMNS

Performance Metrics Name Space

TCP/IP

Transmission Control Protocol/Internet Protocol

100

Index
*_inst operator Arithmetic Aggregation
*_sample operator Arithmetic Aggregation
2D tools Monitoring System Performance
64-bit IEEE format Descriptions for Performance Metrics
pmGetConfig function PCP Environment Variables
acronyms Acronyms
active pmlogger process Identifying an Active pmlogger
Process
adaptation Dynamic Adaptation to Change
application programs Application and Agent
Development Sources of Performance Metrics and Their
Domains
archive logs
administration Archive Log Administration
analysis Logging and Retrospective Analysis
capacity planning Using Archive Logs for Capacity
Planning
collection time Current Metric Context
contents PCP Archive Contents
creation Collecting, Transporting, and Archiving
Performance Information
customization Automated Operational Support
Archive Logging Customization
export Exporting PCP Archive Logs
fetching metrics Fetching Metrics from an Archive
Log
file management Archive Log File Management
folios PCP Archive Folios
physical filenames Fetching Metrics from an Archive
Log
PMAPI Archive Logs and the PMAPI
retrospective analysis Retrospective Analysis Using
Archive Logs
troubleshooting Archive Logging Troubleshooting
usage Archive Logging
arithmetic aggregation Arithmetic Aggregation
arithmetic expressions pmie Arithmetic Expressions
audience Empowering the PCP User
audits Automated Operational Support
automated operational support Automated Operational
Support
avg_host operator Arithmetic Aggregation
basename conventions Basename Conventions
Boolean expressions Boolean Expressions
capacity planning Using Archive Logs for Capacity
Planning
caveats Caveats and Notes on pmie
centralized archive logging Automated Operational
Support
coverage Metric Coverage
chkhelp tool Application and Agent Development

client-server architecture PCP Distributed Operation
collection time Current Metric Context
collector hosts Distributed Collection Collector and
Monitor Roles PMDA Installation on a PCP Collector
Host
comments Comments
common directories Common Directories and File
Locations
component software Overview of Component Software
conceptual foundations Conceptual Foundations
configuring PCP Installing and Configuring Performance
Co-Pilot
conventions Common Conventions and Arguments
cookbook Cookbook for Archive Logging
count_host operator Arithmetic Aggregation
cron scripts Introduction to Archive Logging
Administering PCP Archive Logs Using cron Scripts
customization
archive logs Archive Logging Customization
inference engine Inference Engine Customization
PCP services Customizing and Extending PCP
Services
data collection tools Collecting, Transporting, and
Archiving Performance Information
dbpmda tool Application and Agent Development
debugging tools Operational and Infrastructure Support
deployment strategies Performance Co-Pilot Deployment
Strategies
diagnostic tools Operational and Infrastructure Support
DISPLAY variable pmie Rule Expressions
distributed collection Distributed Collection
domains Unification of Performance Metric Domains
DSO Acronyms
duration Performance Monitor Reporting Frequency and
Duration
dynamic adaptation Dynamic Adaptation to Change
environ man page Timezone Options
environment variables PCP Environment Variables
error detection pmie Error Detection
${PCP_PMLOGGERCONTROL_PATH} file Primary
Logger
${PCP_DIR}/etc/pcp.conf file Common Directories and
File Locations PCP Environment Variables
${PCP_DIR}/etc/pcp.env file Common Directories and
File Locations PCP Environment Variables
${PCP_RC_DIR}/pmcd file Common Directories and
File Locations
evaluation frequency Setting Evaluation Frequency
extensibility PCP Extensibility Customizing and
Extending PCP Services
external equipment Sources of Performance Metrics and
Their Domains
fetching metrics Fetching Metrics from Another Host
Fetching Metrics from an Archive Log

101

Index

file locations Common Directories and File Locations
firewalls Running PCP Tools through a Firewall
flush command Coordination between pmlogger and
PCP tools
folios PCP Archive Folios
functional domains Sources of Performance Metrics and
Their Domains
glossary Acronyms
illegal label record Illegal Label Record
inference engine Inference Engine Customization
infrastructure support tools Operational and Infrastructure
Support
installing PCP Installing and Configuring Performance
Co-Pilot
intrinsic operators pmie Intrinsic Operators
I/O Acronyms
IPC Acronyms
kill command Primary pmlogger Cannot Start
layered software services Sources of Performance Metrics
and Their Domains
lexical elements Lexical Elements
libpcp_mmv library Product Extensibility
libpcp_pmda library Product Extensibility
log volumes Log Volumes
logging (see archive logs)
logical constants Logical Constants
logical expressions pmie Logical Expressions
macros Macros
man command
usage Monitoring System Performance
max_host operator Arithmetic Aggregation
metadata Descriptions for Performance Metrics
metric domains Unification of Performance Metric
Domains
metric wraparound Performance Metrics Wraparound
min_host operator Arithmetic Aggregation
mkaf tool Collecting, Transporting, and Archiving
Performance Information
Introduction to Archive
Logging
monitor configuration Product Structure
monitor hosts Collector and Monitor Roles
monitoring system performance Monitoring System
Performance
naming scheme Uniform Naming and Access to
Performance Metrics
netstat command PMCD Does Not Start
network routers and bridges Sources of Performance
Metrics and Their Domains
network transportation tools Collecting, Transporting,
and Archiving Performance Information
newhelp tool Application and Agent Development
Mail servers Sources of Performance Metrics and Their
Domains
objectives Objectives

operational support tools Operational and Infrastructure
Support
operators Quantification Operators
overview Introduction to Performance Co-Pilot
pcp-atop tool
brief description Performance Monitoring and
Visualization
pmcd.options file The pmcd.options File
PCP
acronym Acronyms
archive logger deployment PCP Archive Logger
Deployment
collector deployment PCP Collector Deployment
configuring and installing Installing and Configuring
Performance Co-Pilot
conventions Common Conventions and Arguments
distributed operation PCP Distributed Operation
environment variables PCP Environment Variables
extensibility PCP Extensibility Product Extensibility
features Introduction to Performance Co-Pilot
log file option Fetching Metrics from an Archive Log
naming conventions Common Conventions and
Arguments
pmie capabilities Introduction to pmie
pmie tool pmie use of PCP services
tool customization PCP Tool Customization
tool development PCP Tool Development
tool summaries Performance Monitoring and
Visualization Collecting, Transporting, and Archiving
Performance Information
Operational and
Infrastructure Support Application and Agent
Development
pcp tool Operational and Infrastructure Support
Operational and Infrastructure Support
PCP Tutorials and Case Studies
pminfo command The pminfo Command
pmval command The pmval Command
PCP_COUNTER_WRAP variable PCP Environment
Variables Performance Metric Wraparound Performance
Metrics Wraparound
PCP_STDERR variable PCP Environment Variables
PCPIntro command PMCD Does Not Start Performance
Monitor Reporting Frequency and Duration
PDU The pmcd.options File Acronyms
Performance Co-Pilot (see PCP)
Performance Metric Identifier (see PMID)
performance metric wraparound Performance Metric
Wraparound Performance Metrics Wraparound
performance metrics
concept Performance Metrics
descriptions Descriptions for Performance Metrics
methods Sources of Performance Metrics and Their
Domains

102

Index

missing and incomplete values Missing and
Incomplete Values for Performance Metrics
PMNS Performance Metrics Name Space
retrospective sources Retrospective Sources of
Performance Metrics
sources Sources of Performance Metrics and Their
Domains
Performance Metrics Application Programming Interface
(see PMAPI)
Performance Metrics Collection Daemon (see PMCD)
Performance Metrics Domain (see PMD)
Performance Metrics Domain Agent (see PMDA)
Performance Metrics Inference Engine (see pmie tool)
Performance Metrics Name Space (see PMNS)
performance monitoring Performance Monitoring and
Visualization Monitoring System Performance
performance visualization tools Using Archive Logs with
Performance Tools
PM_INDOM_NULL pmie and the Performance Metrics
Collection System
pmafm tool
archive folios Introduction to Archive Logging
brief description Collecting, Transporting, and
Archiving Performance Information
interactive commands PCP Archive Folios
PMAPI
acronym Acronyms
archive logs Archive Logs and the PMAPI
brief description Application and Agent Development
naming metrics Performance Metrics
pmie capabilities Introduction to pmie
PMCD
acronym Acronyms
brief description Collecting, Transporting, and
Archiving Performance Information
collector host pmie Metric Expressions
configuration files PMCD Options and Configuration
Files
diagnostics and error messages PMCD Diagnostics
and Error Messages
distributed
collection
Distributed
Collection
Distributed Collection
maintenance Performance Metrics Collection Daemon
(PMCD)
monitoring utilities Performance Co-Pilot Deployment
Strategies
not starting PMCD Does Not Start
PMCD_CONNECT_TIMEOUT
variable
PCP
Environment Variables
PMCD_PORT variable PCP Environment Variables
PMCD_LOCAL variable PCP Environment Variables
PMCD_RECONNECT_TIMEOUT variable PCP
Environment Variables

PMCD_REQUEST_TIMEOUT
variable
PCP
Environment Variables
remote connection Cannot Connect to Remote PMCD
starting and stopping Starting and Stopping the PMCD
TCP/IP firewall Running PCP Tools through a
Firewall
${PCP_PMCDCONF_PATH}
file
Common
Directories and File Locations
pmcd tool (see PMCD)
PMCD_CONNECT_TIMEOUT
variable
Cannot
Connect to Remote PMCD PCP Environment Variables
PMCD_PORT variable Running PCP Tools through
a Firewall PMCD Does Not Start PCP Environment
Variables
PMCD_LOCAL variable Cannot Connect to Remote
PMCD PCP Environment Variables
PMCD_RECONNECT_TIMEOUT
variable
PCP
Environment Variables
PMCD_REQUEST_TIMEOUT
variable
PCP
Environment Variables
pmcd_wait tool Collecting, Transporting, and Archiving
Performance Information
pmcd.conf file The pmcd.conf File Controlling Access
to PMCD with pmcd.conf
pmchart tool
brief description Performance Monitoring and
Visualization
fetching metrics Fetching Metrics from Another Host
man example Monitoring System Performance
record mode PCP Archive Folios
remote PMCD Cannot Connect to Remote PMCD
short-term executions Directory Organization for
Archive Log Files
pmclient tool Application and Agent Development
Application and Agent Development
pcp-collectl tool
brief description Performance Monitoring and
Visualization
record mode PCP Archive Folios
pmconfirm command
error messages PCP Environment Variables
visible alarm Introduction to pmie
PMD PMDA Installation on a PCP Collector Host
Acronyms
PMDA
acronym Acronyms
collectors Collector and Monitor Roles
customizing Customizing the Summary PMDA
development PMDA Development
installation PMDA Installation on a PCP Collector
Host
instance names pmie Metric Expressions
libraries PCP Extensibility
managing optional agents Managing Optional PMDAs

103

Index

monitoring utilities Performance Co-Pilot Deployment
Strategies
removal PMDA Removal on a PCP Collector Host
unification Unification of Performance Metric
Domains
pmdaapache tool Collecting, Transporting, and Archiving
Performance Information
pmdacisco tool Collecting, Transporting, and Archiving
Performance Information
pmdaelasticsearch tool Collecting, Transporting, and
Archiving Performance Information
pmdagfs2 tool Collecting, Transporting, and Archiving
Performance Information
pmdagluster tool Collecting, Transporting, and Archiving
Performance Information
pmdainfiniband tool Collecting, Transporting, and
Archiving Performance Information
pmdakvm tool Collecting, Transporting, and Archiving
Performance Information
pmdalustrecomm tool Collecting, Transporting, and
Archiving Performance Information
pmdamailq tool Collecting, Transporting, and Archiving
Performance Information
pmdamemcache tool Collecting, Transporting, and
Archiving Performance Information
pmdammv tool Collecting, Transporting, and Archiving
Performance Information
pmdamysql tool Collecting, Transporting, and Archiving
Performance Information
pmdanamed tool Collecting, Transporting, and Archiving
Performance Information
pmdanginx tool Collecting, Transporting, and Archiving
Performance Information
pmdapostfix tool Collecting, Transporting, and Archiving
Performance Information
pmdapostgresql tool Collecting, Transporting, and
Archiving Performance Information
pmdaproc tool Collecting, Transporting, and Archiving
Performance Information
pmdarsyslog tool Collecting, Transporting, and
Archiving Performance Information
pmdasamba tool Collecting, Transporting, and Archiving
Performance Information
pmdasendmail tool Collecting, Transporting, and
Archiving Performance Information
pmdasnmp tool Collecting, Transporting, and Archiving
Performance Information
pmdasummary tool Collecting, Transporting, and
Archiving Performance Information
pmdasystemd tool Collecting, Transporting, and
Archiving Performance Information
pmdavmware tool Collecting, Transporting, and
Archiving Performance Information

pmdaweblog tool Collecting, Transporting, and
Archiving Performance Information
pmdaxfs tool Collecting, Transporting, and Archiving
Performance Information
pmdbg facility Operational and Infrastructure Support
pmdumplog tool
archive log contents PCP Archive Contents
brief description Collecting, Transporting, and
Archiving Performance Information
troubleshooting Cannot Find Log
pmrep tool
brief description Performance Monitoring and
Visualization
description The pmrep Command
pmerr tool Operational and Infrastructure Support
pmgenmap tool Application and Agent Development
pmhostname tool Operational and Infrastructure Support
PMID
acronym Acronyms
description Sources of Performance Metrics and Their
Domains Performance Metrics Name Space
PMNS names Customizing the Summary PMDA
printing The pminfo Command
pmie tool
%-token pmie Rule Expressions
arithmetic aggregation Arithmetic Aggregation
arithmetic expressions pmie Arithmetic Expressions
automated reasoning Introduction to pmie
basic examples Basic pmie Usage
brief description Performance Monitoring and
Visualization Operational and Infrastructure Support
customization Introduction to pmie
developing rules Developing and Debugging pmie
Rules
error detection pmie Error Detection
examples Simple pmie Usage Complex pmie
Examples
fetching metrics Fetching Metrics from Another Host
global files and directories Global Files and
Directories
instance names pmie Instance Names
intrinsic operators pmie Intrinsic Operators
language Introduction to pmie Specification Language
for pmie
logical expressions pmie Logical Expressions
metric expressions pmie Metric Expressions
performance metrics inference engine Performance
Metrics Inference Engine
pmieconf rules Performance Monitoring and
Visualization Creating pmie Rules with pmieconf
procedures Creating pmie Rules with pmieconf
Management of pmie Processes
rate conversion pmie Rate Conversion
rate operator The rate Operator

104

Index

real examples pmie Examples
remote PMCD Cannot Connect to Remote PMCD
sample intervals pmie Sample Intervals
setting evaluation frequency Setting Evaluation
Frequency
syntax Basic pmie Syntax
transitional operators Transitional Operators
pmevent tool
brief description Performance Monitoring and
Visualization
pmieconf tool
brief description Performance Monitoring and
Visualization
customization Introduction to pmie
rules Creating pmie Rules with pmieconf
pminfo tool
brief description Performance Monitoring and
Visualization
description The pminfo Command
displaying the PMNS Performance Metrics Name
Space
PCP Tutorials and Case Studies The pminfo
Command
pmie arguments pmie and the Performance Metrics
Collection System
pmstat tool
brief description Performance Monitoring and
Visualization
description The pmstat Command
pmlc tool
brief description Collecting, Transporting, and
Archiving Performance Information
description Using pmlc
dynamic adjustment Introduction to Archive Logging
flush command Coordination between pmlogger and
PCP tools
PMLOGGER_PORT variable PCP Environment
Variables
PMLOGGER_LOCAL variable PCP Environment
Variables
show command Primary pmlogger Cannot Start
SIGHUP signal Log Volumes
TCP/IP firewall Running PCP Tools through a
Firewall
pmlock tool Operational and Infrastructure Support
pmlogcheck tool Collecting, Transporting, and Archiving
Performance Information
pmlogconf tool Collecting, Transporting, and Archiving
Performance Information
pmlogextract tool Collecting, Transporting, and
Archiving Performance Information
Manipulating
Archive Logs with pmlogextract
pmlogger tool PCP Environment Variables pmie Rule
Expressions

archive logs Fetching Metrics from an Archive Log
Introduction to Archive Logging
brief description Collecting, Transporting, and
Archiving Performance Information
configuration Configuration of pmlogger Using pmlc
cookbook tasks Cookbook for Archive Logging
current metric context Current Metric Context
folios PCP Archive Folios
PCP tool coordination Coordination between
pmlogger and PCP tools
pmlc control Introduction to Archive Logging
primary instance Primary Logger
remote PMCD Cannot Connect to Remote PMCD
TCP/IP firewall Running PCP Tools through a
Firewall
troubleshooting Archive Logging Troubleshooting
pmlogger_check script Operational and Infrastructure
Support Administering PCP Archive Logs Using cron
Scripts
pmlogger_daily script Operational and Infrastructure
Support Administering PCP Archive Logs Using cron
Scripts
pmlogger_merge script Operational and Infrastructure
Support Administering PCP Archive Logs Using cron
Scripts
PMLOGGER_PORT variable Running PCP Tools
through a Firewall PCP Environment Variables
PMLOGGER_LOCAL variable PCP Environment
Variables
pmlogsummary tool Performance Monitoring and
Visualization
Summarizing Archive Logs with
pmlogsummary
pmnewlog tool Operational and Infrastructure Support
PMNS
acronym Acronyms
brief description Performance Metrics
defined names Uniform Naming and Access to
Performance Metrics
description Performance Metrics Name Space
management PMNS Management
metric expressions pmie Metric Expressions
names Customizing the Summary PMDA
PMNS Alternate Performance Metric Name Spaces
syntax PMNS Syntax
troubleshooting Performance Metrics Name Space
PMPROXY_PORT variable PCP Environment Variables
PMPROXY_LOCAL variable PCP Environment
Variables
pmnsadd tool Operational and Infrastructure Support
pmnsdel tool Operational and Infrastructure Support
pmprintf tool PCP Environment Variables
pmprobe tool Performance Monitoring and Visualization
pmrun tool Common Conventions and Arguments
pmsnap tool

105

Index

brief description Operational and Infrastructure
Support
script usage Administering PCP Archive Logs Using
cron Scripts
pmproxy tool
brief description Performance Monitoring and
Visualization
pmproxy port PCP Environment Variables
pmproxy local PCP Environment Variables
TCP/IP firewall Running PCP Tools through a
Firewall
pmstore tool
brief description Operational and Infrastructure
Support
description The pmstore Command
setting metric values Monitoring System Performance
pmtrace tool Collecting, Transporting, and Archiving
Performance Information
pmval tool
brief description Performance Monitoring and
Visualization
description The pmval Command
pmwebd tool Collecting, Transporting, and Archiving
Performance Information
primary archive Primary Logger
primary logger Primary Logger
protocol data units (see PDU)
quantification operators Quantification Operators
rate conversion pmie Rate Conversion
rate operator The rate Operator
relational expressions Relational Expressions
reporting frequency Performance Monitor Reporting
Frequency and Duration
retrospective analysis Retrospective Analysis Using
Archive Logs
roles
collector Collector and Monitor Roles Product
Structure
monitor Collector and Monitor Roles Product
Structure
rule expressions pmie Rule Expressions
sample intervals pmie Sample Intervals
kernel data structures Sources of Performance Metrics
and Their Domains
scripts Operational and Infrastructure Support
Administering PCP Archive Logs Using cron Scripts
service management Quality of Service Measurement
set-valued performance metrics Set-Valued Performance
Metrics
show command Primary pmlogger Cannot Start
SIGHUP signal PMCD Not Reconfiguring after SIGHUP
Log Volumes
SIGINT signal Primary pmlogger Cannot Start

SIGUSR1 signal Coordination between pmlogger and
PCP tools
single-valued performance metrics Single-Valued
Performance Metrics
PROXY protocol Running PCP Tools through a Firewall
software Overview of Component Software
subsystems Product Structure
sum_host operator Arithmetic Aggregation
syntax PMNS Syntax
syslog function Introduction to pmie pmie Rule
Expressions
system log file Introduction to pmie pmie Rule
Expressions
target usage PCP Target Usage
TCP/IP
acronym Acronyms
collector and monitor hosts Running PCP Tools
through a Firewall
remote PMCD Cannot Connect to Remote PMCD
sockets PCP Environment Variables
text-based tools Monitoring System Performance
time dilation Time Dilation and Time Skew
time duration Time Duration and Control
time window options Time Window Options
time-stamped message pmie Rule Expressions
timezone options Timezone Options
tool customization PCP Tool Customization
tool development PCP Tool Development
tool options General PCP Tool Options Performance
Metrics Inference Engine
transient problems Transient Problems with Performance
Metric Values
transitional operators Transitional Operators
troubleshooting
archive logging Archive Logging Troubleshooting
general utilities Cannot Connect to Remote PMCD
kernel metrics Kernel Metrics and the PMCD
PMCD Troubleshooting Kernel Metrics and the
PMCD
uniform naming Uniform Naming and Access to
Performance Metrics
units Units
user interface components Common Conventions and
Arguments
${PCP_BINADM_DIR}/pmcd file Common Directories
and File Locations
${PCP_LOG_DIR}/NOTICES file Introduction to pmie
${PCP_LOGDIR}/pmcd/pmcd.log file PMCD Does Not
Start
${PCP_PMCDOPTIONS_PATH}
file
Common
Directories and File Locations
${PCP_PMCDCONF_PATH} filePMDA Installation on
a PCP Collector Host PMCD Not Reconfiguring after
SIGHUP Common Directories and File Locations

106

Index

${PCP_SYSCONF_DIR}/pmlogger/config.default file
Primary Logger
${PCP_PMLOGGERCONTROL_PATH}
file
Administering PCP Archive Logs Using cron Scripts
Directory Organization for Archive Log Files
${PCP_DEMOS_DIR} pmie Examples
${PCP_VAR_DIR}/pmns/stdpmid
file
PMDA
Installation on a PCP Collector Host
${PCP_TMP_DIR}/pmlogger files Primary pmlogger
Cannot Start
window options Time Window Options

107

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