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Setting compute resource quota for OpenShift Pipelines | Managing performance and resource use | Red Hat OpenShift Pipelines 1.15
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A ResourceQuota object in Red Hat OpenShift Pipelines controls the total resource consumption per namespace. You can use it to limit the quantity of objects created in a namespace, based on the type of the object. In addition, you can specify a compute resource quota to restrict the total amount of compute resources consumed in a namespace.

However, you might want to limit the amount of compute resources consumed by pods resulting from a pipeline run, rather than setting quotas for the entire namespace. Currently, Red Hat OpenShift Pipelines does not enable you to directly specify the compute resource quota for a pipeline.

Alternative approaches for limiting compute resource consumption in OpenShift Pipelines

To attain some degree of control over the usage of compute resources by a pipeline, consider the following alternative approaches:

  • Set resource requests and limits for each step in a task.

    Example: Set resource requests and limits for each step in a task.
    ...
    spec:
      steps:
        - name: step-with-limts
          computeResources:
            requests:
              memory: 1Gi
              cpu: 500m
            limits:
              memory: 2Gi
              cpu: 800m
    ...
  • Set resource limits by specifying values for the LimitRange object. For more information on LimitRange, refer to Restrict resource consumption with limit ranges.

  • Reduce pipeline resource consumption.

  • Set and manage resource quotas per project.

  • Ideally, the compute resource quota for a pipeline should be same as the total amount of compute resources consumed by the concurrently running pods in a pipeline run. However, the pods running the tasks consume compute resources based on the use case. For example, a Maven build task might require different compute resources for different applications that it builds. As a result, you cannot predetermine the compute resource quotas for tasks in a generic pipeline. For greater predictability and control over usage of compute resources, use customized pipelines for different applications.

When using Red Hat OpenShift Pipelines in a namespace configured with a ResourceQuota object, the pods resulting from task runs and pipeline runs might fail with an error, such as: failed quota: <quota name> must specify cpu, memory.

To avoid this error, do any one of the following:

  • (Recommended) Specify a limit range for the namespace.

  • Explicitly define requests and limits for all containers.

For more information, refer to the issue and the resolution.

If your use case is not addressed by these approaches, you can implement a workaround by using a resource quota for a priority class.

Specifying pipelines resource quota using priority class

A PriorityClass object maps priority class names to the integer values that indicates their relative priorities. Higher values increase the priority of a class. After you create a priority class, you can create pods that specify the priority class name in their specifications. In addition, you can control a pod’s consumption of system resources based on the pod’s priority.

Specifying resource quota for a pipeline is similar to setting a resource quota for the subset of pods created by a pipeline run. The following steps provide an example of the workaround by specifying resource quota based on priority class.

Procedure
  1. Create a priority class for a pipeline.

    Example: Priority class for a pipeline
    apiVersion: scheduling.k8s.io/v1
    kind: PriorityClass
    metadata:
      name: pipeline1-pc
    value: 1000000
    description: "Priority class for pipeline1"
  2. Create a resource quota for a pipeline.

    Example: Resource quota for a pipeline
    apiVersion: v1
    kind: ResourceQuota
    metadata:
      name: pipeline1-rq
    spec:
      hard:
        cpu: "1000"
        memory: 200Gi
        pods: "10"
      scopeSelector:
        matchExpressions:
        - operator : In
          scopeName: PriorityClass
          values: ["pipeline1-pc"]
  3. Verify the resource quota usage for the pipeline.

    Example: Verify resource quota usage for the pipeline
    $ oc describe quota
    Sample output
    Name:       pipeline1-rq
    Namespace:  default
    Resource    Used  Hard
    --------    ----  ----
    cpu         0     1k
    memory      0     200Gi
    pods        0     10

    Because pods are not running, the quota is unused.

  4. Create the pipelines and tasks.

    Example: YAML for the pipeline
    apiVersion: tekton.dev/v1
    kind: Pipeline
    metadata:
      name: maven-build
    spec:
      params:
      - name: GIT_URL
      workspaces:
      - name: local-maven-repo
      - name: source
      tasks:
      - name: git-clone
        taskRef:
          resolver: cluster
          params:
          - name: kind
            value: task
          - name: name
            value: git-clone
          - name: namespace
            value: openshift-pipelines
        workspaces:
        - name: output
          workspace: source
        params:
        - name: URL
          value: $(params.GIT_URL)
      - name: build
        taskRef:
          name: mvn
        runAfter: ["git-clone"]
        params:
        - name: GOALS
          value: ["package"]
        workspaces:
        - name: maven-repo
          workspace: local-maven-repo
        - name: source
          workspace: source
      - name: int-test
        taskRef:
          name: mvn
        runAfter: ["build"]
        params:
        - name: GOALS
          value: ["verify"]
        workspaces:
        - name: maven-repo
          workspace: local-maven-repo
        - name: source
          workspace: source
      - name: gen-report
        taskRef:
          name: mvn
        runAfter: ["build"]
        params:
        - name: GOALS
          value: ["site"]
        workspaces:
        - name: maven-repo
          workspace: local-maven-repo
        - name: source
          workspace: source
    Example: YAML for a task in the pipeline
    apiVersion: tekton.dev/v1
    kind: Task
    metadata:
      name: mvn
    spec:
      workspaces:
      - name: maven-repo
      - name: source
      params:
      - name: GOALS
        description: The Maven goals to run
        type: array
        default: ["package"]
      steps:
        - name: mvn
          image: gcr.io/cloud-builders/mvn
          workingDir: $(workspaces.source.path)
          command: ["/usr/bin/mvn"]
          args:
            - -Dmaven.repo.local=$(workspaces.maven-repo.path)
            - "$(params.GOALS)"
  5. Create and start the pipeline run.

    Example: YAML for a pipeline run
    apiVersion: tekton.dev/v1
    kind: PipelineRun
    metadata:
      generateName: petclinic-run-
    spec:
      pipelineRef:
        name: maven-build
      params:
      - name: GIT_URL
        value: https://github.com/spring-projects/spring-petclinic
      taskRunTemplate:
        podTemplate:
          priorityClassName: pipeline1-pc
      workspaces:
      - name: local-maven-repo
        emptyDir: {}
      - name: source
        volumeClaimTemplate:
          spec:
            accessModes:
              - ReadWriteOnce
            resources:
              requests:
                storage: 200M

    The pipeline run might fail with an error: failed quota: <quota name> must specify cpu, memory.

    To avoid this error, set a limit range for the namespace, where the defaults from the LimitRange object apply to pods created during the build process.

    For more information about setting limit ranges, refer to Restrict resource consumption with limit ranges in the Additional resources section.

  6. After the pods are created, verify the resource quota usage for the pipeline run.

    Example: Verify resource quota usage for the pipeline
    $ oc describe quota
    Sample output
    Name:       pipeline1-rq
    Namespace:  default
    Resource    Used  Hard
    --------    ----  ----
    cpu         500m  1k
    memory      10Gi  200Gi
    pods        1     10

    The output indicates that you can manage the combined resource quota for all concurrent running pods belonging to a priority class, by specifying the resource quota per priority class.