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Application memory sizing

Important

Azure Red Hat OpenShift 3.11 will be retired 30 June 2022. Support for creation of new Azure Red Hat OpenShift 3.11 clusters continues through 30 November 2020. Following retirement, remaining Azure Red Hat OpenShift 3.11 clusters will be shut down to prevent security vulnerabilities.

Follow this guide to create an Azure Red Hat OpenShift 4 cluster. If you have specific questions, please contact us

Overview

This page is intended to provide guidance to application developers using Azure Red Hat OpenShift on:

  1. Determining the memory and risk requirements of a containerized application component and configuring the container memory parameters to suit those requirements.

  2. Configuring containerized application runtimes (for example, OpenJDK) to adhere optimally to the configured container memory parameters.

  3. Diagnosing and resolving memory-related error conditions associated with running in a container.

Background

It is recommended to read fully the overview of how Azure Red Hat OpenShift manages Compute Resources before proceeding.

For the purposes of sizing application memory, the key points are:

  • For each kind of resource (memory, cpu, storage), Azure Red Hat OpenShift allows optional request and limit values to be placed on each container in a pod. For the purposes of this page, we are solely interested in memory requests and memory limits.

  • Memory request

    • The memory request value, if specified, influences the Azure Red Hat OpenShift scheduler. The scheduler considers the memory request when scheduling a container to a node, then fences off the requested memory on the chosen node for the use of the container.

    • If a node’s memory is exhausted, Azure Red Hat OpenShift prioritizes evicting its containers whose memory usage most exceeds their memory request. In serious cases of memory exhaustion, the node OOM killer may select and kill a process in a container based on a similar metric.

  • Memory limit

    • The memory limit value, if specified, provides a hard limit on the memory that can be allocated across all the processes in a container.

    • If the memory allocated by all of the processes in a container exceeds the memory limit, the node OOM killer will immediately select and kill a process in the container.

    • If both memory request and limit are specified, the memory limit value must be greater than or equal to the memory request.

  • Administration

    • The cluster administrator may assign quota against the memory request value, limit value, both, or neither.

    • The cluster administrator may assign default values for the memory request value, limit value, both, or neither.

    • The cluster administrator may override the memory request values that a developer specifies, in order to manage cluster overcommit. This occurs on OpenShift Online, for example.

Strategy

The steps for sizing application memory on Azure Red Hat OpenShift are as follows:

  1. Determine expected container memory usage

    Determine expected mean and peak container memory usage, empirically if necessary (for example, by separate load testing). Remember to consider all the processes that may potentially run in parallel in the container: for example, does the main application spawn any ancillary scripts?

  2. Determine risk appetite

    Determine risk appetite for eviction. If the risk appetite is low, the container should request memory according to the expected peak usage plus a percentage safety margin. If the risk appetite is higher, it may be more appropriate to request memory according to the expected mean usage.

  3. Set container memory request

    Set container memory request based on the above. The more accurately the request represents the application memory usage, the better. If the request is too high, cluster and quota usage will be inefficient. If the request is too low, the chances of application eviction increase.

  4. Set container memory limit, if required

    Set container memory limit, if required. Setting a limit has the effect of immediately killing a container process if the combined memory usage of all processes in the container exceeds the limit, and is therefore a mixed blessing. On the one hand, it may make unanticipated excess memory usage obvious early ("fail fast"); on the other hand it also terminates processes abruptly.

    Note that some Azure Red Hat OpenShift clusters may require a limit value to be set; some may override the request based on the limit; and some application images rely on a limit value being set as this is easier to detect than a request value.

    If the memory limit is set, it should not be set to less than the expected peak container memory usage plus a percentage safety margin.

  5. Ensure application is tuned

    Ensure application is tuned with respect to configured request and limit values, if appropriate. This step is particularly relevant to applications which pool memory, such as the JVM. The rest of this page discusses this.

Sizing OpenJDK on Azure Red Hat OpenShift

The default OpenJDK settings unfortunately do not work well with containerized environments, with the result that as a rule, some additional Java memory settings must always be provided whenever running the OpenJDK in a container.

The JVM memory layout is complex, version dependent, and describing it in detail is beyond the scope of this documentation. However, as a starting point for running OpenJDK in a container, at least the following three memory-related tasks are key:

  1. Overriding the JVM maximum heap size.

  2. Encouraging the JVM to release unused memory to the operating system, if appropriate.

  3. Ensuring all JVM processes within a container are appropriately configured.

Optimally tuning JVM workloads for running in a container is beyond the scope of this documentation, and may involve setting multiple additional JVM options.

Overriding the JVM Maximum Heap Size

For many Java workloads, the JVM heap is the largest single consumer of memory. Currently, the OpenJDK defaults to allowing up to 1/4 (1/-XX:MaxRAMFraction) of the compute node’s memory to be used for the heap, regardless of whether the OpenJDK is running in a container or not. It is therefore essential to override this behaviour, especially if a container memory limit is also set.

There are at least two ways the above can be achieved:

  1. If the container memory limit is set and the experimental options are supported by the JVM, set -XX:+UnlockExperimentalVMOptions -XX:+UseCGroupMemoryLimitForHeap.

    This sets -XX:MaxRAM to the container memory limit, and the maximum heap size (-XX:MaxHeapSize / -Xmx) to 1/-XX:MaxRAMFraction (1/4 by default).

  2. Directly override one of -XX:MaxRAM, -XX:MaxHeapSize or -Xmx.

    This option involves hard-coding a value, but has the advantage of allowing a safety margin to be calculated.

Encouraging the JVM to Release Unused Memory to the Operating System

By default, the OpenJDK does not aggressively return unused memory to the operating system. This may be appropriate for many containerized Java workloads, but notable exceptions include workloads where additional active processes co-exist with a JVM within a container, whether those additional processes are native, additional JVMs, or a combination of the two.

The Azure Red Hat OpenShift Jenkins maven slave image uses the following JVM arguments to encourage the JVM to release unused memory to the operating system: -XX:+UseParallelGC -XX:MinHeapFreeRatio=5 -XX:MaxHeapFreeRatio=10 -XX:GCTimeRatio=4 -XX:AdaptiveSizePolicyWeight=90. These arguments are intended to return heap memory to the operating system whenever allocated memory exceeds 110% of in-use memory (-XX:MaxHeapFreeRatio), spending up to 20% of CPU time in the garbage collector (-XX:GCTimeRatio). At no time will the application heap allocation be less than the initial heap allocation (overridden by -XX:InitialHeapSize / -Xms). Detailed additional information is available Tuning Java’s footprint in OpenShift (Part 1), Tuning Java’s footprint in OpenShift (Part 2), and at OpenJDK and Containers.

Ensuring All JVM Processes Within a Container Are Appropriately Configured

In the case that multiple JVMs run in the same container, it is essential to ensure that they are all configured appropriately. For many workloads it will be necessary to grant each JVM a percentage memory budget, leaving a perhaps substantial additional safety margin.

Many Java tools use different environment variables (JAVA_OPTS, GRADLE_OPTS, MAVEN_OPTS, and so on) to configure their JVMs and it can be challenging to ensure that the right settings are being passed to the right JVM.

The JAVA_TOOL_OPTIONS environment variable is always respected by the OpenJDK, and values specified in JAVA_TOOL_OPTIONS will be overridden by other options specified on the JVM command line. By default, the Azure Red Hat OpenShift Jenkins maven slave image sets JAVA_TOOL_OPTIONS="-XX:+UnlockExperimentalVMOptions -XX:+UseCGroupMemoryLimitForHeap -Dsun.zip.disableMemoryMapping=true" to ensure that these options are used by default for all JVM workloads run in the slave image. This does not guarantee that additional options are not required, but is intended to be a helpful starting point.

Finding the Memory Request and Limit From Within a Pod

An application wishing to dynamically discover its memory request and limit from within a pod should use the Downward API. The following snippet shows how this is done.

apiVersion: v1
kind: Pod
metadata:
  name: test
spec:
  containers:
  - name: test
    image: fedora:latest
    command:
    - sleep
    - "3600"
    env:
    - name: MEMORY_REQUEST
      valueFrom:
        resourceFieldRef:
          containerName: test
          resource: requests.memory
    - name: MEMORY_LIMIT
      valueFrom:
        resourceFieldRef:
          containerName: test
          resource: limits.memory
    resources:
      requests:
        memory: 384Mi
      limits:
        memory: 512Mi
# oc rsh test
$ env | grep MEMORY | sort
MEMORY_LIMIT=536870912
MEMORY_REQUEST=402653184

The memory limit value can also be read from inside the container by the /sys/fs/cgroup/memory/memory.limit_in_bytes file.

Diagnosing an OOM Kill

Azure Red Hat OpenShift may kill a process in a container if the total memory usage of all the processes in the container exceeds the memory limit, or in serious cases of node memory exhaustion.

When a process is OOM killed, this may or may not result in the container exiting immediately. If the container PID 1 process receives the SIGKILL, the container will exit immediately. Otherwise, the container behavior is dependent on the behavior of the other processes.

If the container does not exit immediately, an OOM kill is detectable as follows:

  1. A container process exited with code 137, indicating it received a SIGKILL signal

  2. The oom_kill counter in /sys/fs/cgroup/memory/memory.oom_control is incremented

$ grep '^oom_kill ' /sys/fs/cgroup/memory/memory.oom_control
oom_kill 0
$ sed -e '' </dev/zero  # provoke an OOM kill
Killed
$ echo $?
137
$ grep '^oom_kill ' /sys/fs/cgroup/memory/memory.oom_control
oom_kill 1

If one or more processes in a pod are OOM killed, when the pod subsequently exits, whether immediately or not, it will have phase Failed and reason OOMKilled. An OOM killed pod may be restarted depending on the value of restartPolicy. If not restarted, controllers such as the ReplicationController will notice the pod’s failed status and create a new pod to replace the old one.

If not restarted, the pod status is as follows:

$ oc get pod test
NAME      READY     STATUS      RESTARTS   AGE
test      0/1       OOMKilled   0          1m

$ oc get pod test -o yaml
...
status:
  containerStatuses:
  - name: test
    ready: false
    restartCount: 0
    state:
      terminated:
        exitCode: 137
        reason: OOMKilled
  phase: Failed

If restarted, its status is as follows:

$ oc get pod test
NAME      READY     STATUS    RESTARTS   AGE
test      1/1       Running   1          1m

$ oc get pod test -o yaml
...
status:
  containerStatuses:
  - name: test
    ready: true
    restartCount: 1
    lastState:
      terminated:
        exitCode: 137
        reason: OOMKilled
    state:
      running:
  phase: Running

Diagnosing an Evicted Pod

Azure Red Hat OpenShift may evict a pod from its node when the node’s memory is exhausted. Depending on the extent of memory exhaustion, the eviction may or may not be graceful. Graceful eviction implies the main process (PID 1) of each container receiving a SIGTERM signal, then some time later a SIGKILL signal if the process hasn’t exited already. Non-graceful eviction implies the main process of each container immediately receiving a SIGKILL signal.

An evicted pod will have phase Failed and reason Evicted. It will not be restarted, regardless of the value of restartPolicy. However, controllers such as the ReplicationController will notice the pod’s failed status and create a new pod to replace the old one.

$ oc get pod test
NAME      READY     STATUS    RESTARTS   AGE
test      0/1       Evicted   0          1m

$ oc get pod test -o yaml
...
status:
  message: 'Pod The node was low on resource: [MemoryPressure].'
  phase: Failed
  reason: Evicted