...
spec:
steps:
- name: step-with-limts
resources:
requests:
memory: 1Gi
cpu: 500m
limits:
memory: 2Gi
cpu: 800m
...
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.
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.
...
spec:
steps:
- name: step-with-limts
resources:
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.
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 To avoid this error, do any one of the following:
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.
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.
Create a priority class for a pipeline.
apiVersion: scheduling.k8s.io/v1
kind: PriorityClass
metadata:
name: pipeline1-pc
value: 1000000
description: "Priority class for pipeline1"
Create a 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"]
Verify the resource quota usage for the pipeline.
$ oc describe quota
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.
Create the pipelines and tasks.
apiVersion: tekton.dev/v1alpha1
kind: Pipeline
metadata:
name: maven-build
spec:
workspaces:
- name: local-maven-repo
resources:
- name: app-git
type: git
tasks:
- name: build
taskRef:
name: mvn
resources:
inputs:
- name: source
resource: app-git
params:
- name: GOALS
value: ["package"]
workspaces:
- name: maven-repo
workspace: local-maven-repo
- name: int-test
taskRef:
name: mvn
runAfter: ["build"]
resources:
inputs:
- name: source
resource: app-git
params:
- name: GOALS
value: ["verify"]
workspaces:
- name: maven-repo
workspace: local-maven-repo
- name: gen-report
taskRef:
name: mvn
runAfter: ["build"]
resources:
inputs:
- name: source
resource: app-git
params:
- name: GOALS
value: ["site"]
workspaces:
- name: maven-repo
workspace: local-maven-repo
apiVersion: tekton.dev/v1alpha1
kind: Task
metadata:
name: mvn
spec:
workspaces:
- name: maven-repo
inputs:
params:
- name: GOALS
description: The Maven goals to run
type: array
default: ["package"]
resources:
- name: source
type: git
steps:
- name: mvn
image: gcr.io/cloud-builders/mvn
workingDir: /workspace/source
command: ["/usr/bin/mvn"]
args:
- -Dmaven.repo.local=$(workspaces.maven-repo.path)
- "$(inputs.params.GOALS)"
priorityClassName: pipeline1-pc
|
Ensure that all tasks in the pipeline belongs to the same priority class. |
Create and start the pipeline run.
apiVersion: tekton.dev/v1alpha1
kind: PipelineRun
metadata:
generateName: petclinic-run-
spec:
pipelineRef:
name: maven-build
resources:
- name: app-git
resourceSpec:
type: git
params:
- name: url
value: https://github.com/spring-projects/spring-petclinic
After the pods are created, verify the resource quota usage for the pipeline run.
$ oc describe quota
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.