...
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/v1beta1
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/v1beta1
kind: Task
metadata:
name: mvn
spec:
workspaces:
- name: maven-repo
resources:
inputs:
- name: source
type: git
params:
- name: GOALS
description: The Maven goals to run
type: array
default: ["package"]
steps:
- name: mvn
image: gcr.io/cloud-builders/mvn
workingDir: /workspace/source
command: ["/usr/bin/mvn"]
args:
- -Dmaven.repo.local=$(workspaces.maven-repo.path)
- "$(params.GOALS)"
Create and start the pipeline run.
apiVersion: tekton.dev/v1beta1
kind: PipelineRun
metadata:
generateName: petclinic-run-
spec:
pipelineRef:
name: maven-build
podTemplate:
priorityClassName: pipeline1-pc
workspaces:
- name: local-maven-repo
emptyDir: {}
resources:
- name: app-git
resourceSpec:
type: git
params:
- name: url
value: https://github.com/spring-projects/spring-petclinic
The pipeline run might fail with an error: To avoid this error, set a limit range for the namespace, where the defaults from the For more information about setting limit ranges, refer to Restrict resource consumption with limit ranges in the Additional resources section. |
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.