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<H1 ALIGN=CENTER STYLE="margin-top: 0.48cm; margin-bottom: 0.32cm">Analysis of Linux Containers</H1>
 
<TABLE WIDTH="15%" BORDER=0 CELLPADDING=5 CELLSPACING=10 ALIGN=RIGHT>
	<TR><TD BGCOLOR="#e2e2e2">
<PRE><IMG SRC="images/system-search.png" ALT="" WIDTH=16 HEIGHT=16 BORDER=0>Tools
podman
docker
lxc-info
lxc-ls
pmcd
pmdalinux
pmdaproc
pmdaroot
pminfo
pmprobe</PRE></TD></TR>
</TABLE>
Container engines like Docker, LXC, Rocket and others build on
two Linux kernel facilities - cgroups and namespaces.
In order to understand the performance characteristics of containerized
environments, we need some background kernel knowledge to see how these
concepts affect both the system itself, and system-level analysis tools
like PCP.
This tutorial aims to build or refresh your knowledge in these areas,
while at the same time showing you how to extract performance data from
individual containers using the PCP tools.
For an explanation of Performance Co-Pilot terms and acronyms, consult 
the <A HREF="glossary.html">PCP glossary</A>.
 
<UL>
 <LI>
 <A HREF="#started">Getting Started</A> 
 <LI>
 <A HREF="#cgroups">Control Groups</A> 
 <LI>
 <A HREF="#namespaces">Namespaces</A> 
 <LI>
 <A HREF="#details">Containers and PCP</A>
 <UL>
 <LI>Core Extensions
 <LI>Elevated Privileges
 <LI>Container-specific Metric Values
 <LI>Performance Metric Domain Agents
 <LI>Web and Graphical Tools
 </UL>
</UL>

<TABLE WIDTH="100%" BORDER=0 CELLPADDING=0 CELLSPACING=0 BGCOLOR="#e2e2e2">
 <TR><TD WIDTH="100%" BGCOLOR="#081c59"><A NAME="overview">Getting Started</A></TD></TR>
</TABLE>
Creating and administering containers is the job of a container runtime
engine, and each operates differently.
If you don't have some handy already, create and start one or two containers
for experimentation - the steps involved are widely documented, and differ
differ between engines, so we will skip over them here.

<UL>
 <LI>Using <A HREF="https://docker.io/">Docker</A>, the docker ps -a command can then be used to observe running containers.
 <LI>Under <A HREF="https://github.com/containers/libpod/blob/master/README.md">libpod</A>, podman ps -a is the equivalent command.
 <LI>With <A HREF="https://linuxcontainers.org/">LXC</A>, the lxc-ls and lxc-info commands are used for this purpose.
</UL>
Once these commands are correctly reporting running containers, we
are in a position to begin analysing those containers with PCP tools.

<TABLE WIDTH="100%" BORDER=0 CELLPADDING=10 CELLSPACING=20>
	<TR><TD BGCOLOR="#e2e2e2" WIDTH="70%"> <IMG SRC="images/stepfwd_on.png" ALT="" WIDTH=16 HEIGHT=16 BORDER=0>&nbsp;&nbsp;&nbsp;Check local PCP collector installation (requires the pcp-verify utility): 
<PRE>$ pcp verify --containers</PRE>
</TD></TR>
</TABLE>
<TABLE WIDTH="100%" BORDER=0 CELLPADDING=10 CELLSPACING=20>
	<TR><TD BGCOLOR="#e2e2e2" WIDTH="70%"> <IMG SRC="images/stepfwd_on.png" ALT="" WIDTH=16 HEIGHT=16 BORDER=0>&nbsp;&nbsp;&nbsp;Request networking metrics for a host and then a container running on the host: 
<PRE>$ pminfo --fetch containers.name containers.state.running

containers.name
 inst [0 or "f4d3b90bea15..."] value "sharp_feynman"
 inst [1 or "d43eda0a7e7d..."] value "cranky_colden"
 inst [2 or "252b56e79da5..."] value "desperate_turing"

containers.state.running
    inst [0 or "f4d3b90bea15..."] value 1
    inst [1 or "d43eda0a7e7d..."] value 0
    inst [2 or "252b56e79da5..."] value 1

$ pmprobe -I network.interface.up
network.interface.up 5 "p2p1" "wlp2s0" "lo" "docker0" "veth2234780"

$ pmprobe -I --container sharp_feynman network.interface.up
network.interface.up 2 "lo" "eth0"

$ pmprobe -I --container f4d3b90bea15 network.interface.up
network.interface.up 2 "lo" "eth0"</PRE>
</TD></TR>
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Note: these commands all query the same pmcd process
- from the host running the container engine. In other words, there
is no need to install any PCP software inside the monitored containers.

<TABLE WIDTH="100%" BORDER=0 CELLPADDING=0 CELLSPACING=0 BGCOLOR="#e2e2e2">
 <TR><TD WIDTH="100%" BGCOLOR="#081c59"><A NAME="cgroups">Control Groups</A></TD></TR>
</TABLE>
Control Groups are a Linux kernel mechanism for aggregating
or partitioning sets of tasks, and their children, into hierarchical
groups with specialized behaviour.
This is the underlying technology used for controlling the set of
processes within each container.

Recall that the concept of a &quot;container&quot; is a user-space
construct only, and it is the role of the container engine to ensure
the kernel cgroup hierarchies are constructed and managed appropriately
for the containers it provides.

A cgroup subsystem is kernel code that makes use of the task
grouping facilities provided by cgroups to treat groups of tasks in
particular ways. A subsystem is typically a "resource controller" that
schedules a resource or applies per-cgroup limits. Examples of cgroup
subsystems used by container engines include the virtual memory subsystem
(memory), the processor accounting subsystem (cpuacct),
the block accounting cgroup (blkio), and several others.

Within the scope of individual cgroup subsystems, hierarchies
can be created, managed and shaped in terms of the tasks within them.
A hierarchy is a set of cgroups arranged in a tree, such that
every task in the system is in exactly one of the cgroups in the
hierarchy, and a set of subsystems; each subsystem has
system-specific state attached to each cgroup in the hierarchy.

Each hierarchy has an instance of the cgroup virtual filesystem
associated with it.

<TABLE WIDTH="100%" BORDER=0 CELLPADDING=10 CELLSPACING=20>
	<TR><TD BGCOLOR="#e2e2e2" WIDTH="70%"> <IMG SRC="images/stepfwd_on.png" ALT="" WIDTH=16 HEIGHT=16 BORDER=0>&nbsp;&nbsp;&nbsp;These can be interrogated by querying the PCP cgroup.subsys and cgroup.mounts metrics. 
<PRE>$ pminfo --fetch cgroup.subsys.num_cgroups

cgroup.mounts.subsys
    inst [0 or "/sys/fs/cgroup/systemd"] value "?"
    inst [1 or "/sys/fs/cgroup/cpuset"] value "cpuset"
    inst [2 or "/sys/fs/cgroup/cpu,cpuacct"] value "cpu,cpuacct"
    inst [3 or "/sys/fs/cgroup/memory"] value "memory"
    inst [4 or "/sys/fs/cgroup/devices"] value "devices"
    inst [5 or "/sys/fs/cgroup/freezer"] value "freezer"
    inst [6 or "/sys/fs/cgroup/net_cls,net_prio"] value "net_cls,net_prio"
    inst [7 or "/sys/fs/cgroup/blkio"] value "blkio"
    inst [8 or "/sys/fs/cgroup/perf_event"] value "perf_event"
    inst [9 or "/sys/fs/cgroup/hugetlb"] value "hugetlb"

cgroup.subsys.num_cgroups
 inst [0 or "cpuset"] value 1
 inst [1 or "cpu"] value 77
 inst [2 or "cpuacct"] value 77
 inst [3 or "memory"] value 3
 inst [4 or "devices"] value 3
 inst [5 or "freezer"] value 3
 inst [6 or "net_cls"] value 1
 inst [7 or "blkio"] value 77
 inst [8 or "perf_event"] value 1
 inst [9 or "net_prio"] value 1
 inst [10 or "hugetlb"] value 1</PRE>
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Userspace code (i.e. container engines like Docker and LXC) can
create and destroy cgroups by name in an instance of the cgroup
virtual file system, specify and query to which cgroup a task is
assigned, and list the task PIDs assigned to a cgroup.
Those creations and assignments only affect the hierarchy associated
with that instance of the cgroup file system.

<TABLE WIDTH="100%" BORDER=0 CELLPADDING=0 CELLSPACING=0 BGCOLOR="#e2e2e2">
 <TR><TD WIDTH="100%" BGCOLOR="#081c59"><A NAME="namespaces">Namespaces</A></TD></TR>
</TABLE>
Completely distinct to cgroups, at least within the kernel, is the
concept of namespaces.
Namespaces allow different processes to have differing views of several
aspects of the kernel, such as the hostname (UTS namespace), network
interfaces (NET namespace), process identifiers (PID namespace), mounted
filesystems (MNT namespace) and so on.

When processes share a namespace, they share the same view of a resource.
For example, objects created in one IPC namespace are visible to all other
processes that are members of that namespace, but are not visible to
processes having another IPC namespace.
So for our purposes, all processes running in one container can thus have
a different view to the IPC resources visible to a process running on the
host or a different container.

Returning to the first networking example in this tutorial, we can see
how namespaces become important from a performance tooling point of view.
For network metrics within a container, we want to be able to report values
for the set of network interfaces visible within that container, instead of
the set from the host itself.

Finally, it is important to note that namespaces are not a complete
abstraction, in that many aspects of the underlying host remain visible
from within the container. This affects performance tools in that the
values exported for some metrics can be adjusted and fine-tuned relative
to the container, while others cannot.

<TABLE WIDTH="100%" BORDER=0 CELLPADDING=0 CELLSPACING=0 BGCOLOR="#e2e2e2">
 <TR><TD WIDTH="100%" BGCOLOR="#081c59"><A NAME="details">Containers and PCP</A></TD></TR>
</TABLE>
Core Extensions
All connections made to the PCP metrics collector daemon (pmcd)
are made using the PCP protocol, which is TCP/IP based and thus
(importantly for containers) connection-oriented.
Each individual monitoring tool has a unique connection to pmcd
and can request values for a specific, custom set of metrics. This includes
being able to request metric values related to a specific, named container.
Note that PCP differs to the design of several other monitoring systems
in this regard, which write or send out a specified set of system-wide
values, on a set interval.

From a user point of view, this boils down to being able to specify a
container via the interface (whether command line or graphical) of the
PCP monitoring tools and to have that container name transfered to the
PCP collector system. This allows for filtering and fine-tuning of the
metric values it returns, such that the values are specific to the named
container.

Elevated Privileges
Support for containers was first added in the 3.10.2 version of PCP
(released in January 2015).
This version includes the pmdaroot daemon - a critical component
of the container support, it must be enabled in order to monitor containers.

It performs privileged operations on behalf of other PCP agents and plays
a pivotal role in informing the other agents about various attributes of the
active containers that it discovers on the PCP collector system.

Verify that there is a pmdaroot line in /etc/pcp/pmcd/pmcd.conf
and that the pcp command reports that it is running.

Container-specific Metric Values
With that core functionality in place, several kernel agents have been
taught to customize the metric values they report when the monitoring of a
named container has been requested.
These include the network, filesys, ipc, and other metrics in
pmdalinux, as well as the per-process and cgroup metrics in
pmdaproc.

<TABLE WIDTH="100%" BORDER=0 CELLPADDING=10 CELLSPACING=20>
	<TR><TD BGCOLOR="#e2e2e2" WIDTH="70%"> <IMG SRC="images/stepfwd_on.png" ALT="" WIDTH=16 HEIGHT=16 BORDER=0>&nbsp;&nbsp;&nbsp;Requesting container-specific process and control group metrics:
 <PRE>$ pminfo -t --fetch --container sharp_feynman cgroup.memory.stat.cache proc.psinfo.rss pmcd.hostname

cgroup.memory.stat.cache [Number of bytes of page cache memory]
    inst [2 or "/system.slice/docker-f4d3b90bea15..."] value 9695232

proc.psinfo.rss [resident set size (i.e. physical memory) of the process]
    inst [21967 or "021967 dd if=/dev/random of=/tmp/bits count=200k"] value 676
    inst [27996 or "027996 /bin/bash"] value 2964

pmcd.hostname [local hostname]
 value "f4d3b90bea15"</PRE>
</TD></TR>
</TABLE>

Performance Metric Domain Agents
As the underlying container technologies have matured, instrumentation
has been added for analysis.
For example, podman and docker have APIs to extract operational
metrics, and these are available from pmdapodman and pmdadocker.


Additionally, components of container infrastructure usually expose metrics
via a /metrics HTTP endpoint in the OpenMetrics (Prometheus) format.
These metrics can be observed using PCP tools via pmdaprometheus.

Upcoming versions of PCP will extend the initial work done for container
analysis in several directions, particularly on the monitoring tool side.

Web and Graphical Tools
<TABLE WIDTH="100%" BORDER=0 CELLPADDING=0 CELLSPACING=0 STYLE="page-break-before: always">
 <TR><TD WIDTH=500> <IMG ALIGN=MIDDLE SRC="images/pmchart_add_host_container.png" ALT="" BORDER=0></TD>
 <TD>In the PCP strip chart utility pmchart, connections to containers can be established using the "Add Host" dialog, as shown to the left.
	This can be accessed via the "New Chart" or "Open View" menu entries.
	<UL>
 <LI>Specify the name of the PCP Collector system where pmcd is running.
 <LI>Press the "Advanced" push button to enable additional connection attributes to be specified.
 <LI>Select the "Container" check box, and enter a container name.
 <LI>Press "OK" to establish a connection to the container on host -
 this functions in much the same was as the pminfo examples
 from earlier in this tutorial.
	</UL>
	</TD>
 </TR>
</TABLE>
<TABLE WIDTH="100%" BORDER=0 CELLPADDING=0 CELLSPACING=0 STYLE="page-break-before: always">
	<TR><TD>PCP container metric charts using <A HREF="http://getvector.io/">Vector</A></TD></TR>
	<TR><TD WIDTH="100%"> <IMG ALIGN=MIDDLE SRC="images/vector-containers.png" ALT="" BORDER=0></TD></TR>
</TABLE>

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	<TD WIDTH="50%"><A HREF="https://pcp.io/">PCP Site</A> Copyright &copy; 2012-2018 <A HREF="https://www.redhat.com/">Red Hat</A></TD></TR>
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