Configuring Resource Quotas for Pipeline Components

Overview

Configure resource quotas related to the Pipeline component.

Use Cases

Adjust the resource quotas for the Pipeline component
Set default resource quotas for init-containers and containers created by TaskRun

Prerequisites

The Tekton Operator component must be installed
TektonConfig resources must have been automatically created in the environment
The document on Adjusting Optional Configuration Items for Subcomponents should be read

Resource Configuration Guidelines

Before configuring resource quotas:

Assess your cluster's available resources and capacity
Consider your workload characteristics and performance requirements
Start with conservative values and adjust based on monitoring data
Test configurations in non-production environments first

Steps

Step 1

Edit the TektonConfig resource

$ kubectl edit tektonconfigs.operator.tekton.dev config

Step 2

WARNING

Modifying the configuration may trigger a rolling update of the component Pods, which could lead to temporary service unavailability. Please execute this at an appropriate time.

Example of modifying the spec.pipeline.options.deployments configuration:

apiVersion: operator.tekton.dev/v1alpha1
kind: TektonConfig
metadata:
  name: config
spec:
  pipeline:
    options:
      disabled: false

      configMaps:
        config-defaults:
          data:
            # Add default container resource quotas
            # Adjust the values below according to your cluster's resource capacity and workload requirements
            default-container-resource-requirements: |
              place-scripts: # updates resource requirements of a 'place-scripts' container
                requests:
                  memory: "<MEMORY_REQUEST>"  # e.g., "128Mi"
                  cpu: "<CPU_REQUEST>"        # e.g., "250m"
                limits:
                  memory: "<MEMORY_LIMIT>"    # e.g., "512Mi"
                  cpu: "<CPU_LIMIT>"          # e.g., "500m"

              prepare: # updates resource requirements of a 'prepare' container
                requests:
                  memory: "<MEMORY_REQUEST>"  # e.g., "128Mi"
                  cpu: "<CPU_REQUEST>"        # e.g., "250m"
                limits:
                  memory: "<MEMORY_LIMIT>"    # e.g., "256Mi"
                  cpu: "<CPU_LIMIT>"          # e.g., "500m"

              working-dir-initializer: # updates resource requirements of a 'working-dir-initializer' container
                requests:
                  memory: "<MEMORY_REQUEST>"  # e.g., "128Mi"
                  cpu: "<CPU_REQUEST>"        # e.g., "250m"
                limits:
                  memory: "<MEMORY_LIMIT>"    # e.g., "512Mi"
                  cpu: "<CPU_LIMIT>"          # e.g., "500m"

              prefix-scripts: # updates resource requirements of containers which starts with 'scripts-'
                requests:
                  memory: "<MEMORY_REQUEST>"  # e.g., "128Mi"
                  cpu: "<CPU_REQUEST>"        # e.g., "250m"
                limits:
                  memory: "<MEMORY_LIMIT>"    # e.g., "512Mi"
                  cpu: "<CPU_LIMIT>"          # e.g., "500m"

              prefix-sidecar-scripts: # updates resource requirements of containers which starts with 'sidecar-scripts-'
                requests:
                  memory: "<MEMORY_REQUEST>"  # e.g., "128Mi"
                  cpu: "<CPU_REQUEST>"        # e.g., "250m"
                limits:
                  memory: "<MEMORY_LIMIT>"    # e.g., "512Mi"
                  cpu: "<CPU_LIMIT>"          # e.g., "500m"

              sidecar-tekton-log-results: # updates resource requirements of a 'sidecar-tekton-log-results' container
                requests:
                  memory: "<MEMORY_REQUEST>"  # e.g., "128Mi"
                  cpu: "<CPU_REQUEST>"        # e.g., "100m"
                limits:
                  memory: "<MEMORY_LIMIT>"    # e.g., "256Mi"
                  cpu: "<CPU_LIMIT>"          # e.g., "250m"

      deployments:
        # Adjust the resource values below according to your cluster's capacity and performance requirements
        tekton-pipelines-controller:
          spec:
            replicas: <REPLICA_COUNT>  # e.g., 1
            template:
              spec:
                containers:
                  - name: tekton-pipelines-controller
                    resources:
                      requests:
                        cpu: <CPU_REQUEST>        # e.g., "500m"
                        memory: <MEMORY_REQUEST>  # e.g., "512Mi"
                      limits:
                        cpu: <CPU_LIMIT>          # e.g., "1"
                        memory: <MEMORY_LIMIT>    # e.g., "1Gi"

        tekton-pipelines-remote-resolvers:
          spec:
            replicas: <REPLICA_COUNT>  # e.g., 1
            template:
              spec:
                containers:
                  - name: controller
                    resources:
                      requests:
                        cpu: <CPU_REQUEST>        # e.g., "200m"
                        memory: <MEMORY_REQUEST>  # e.g., "256Mi"
                      limits:
                        cpu: <CPU_LIMIT>          # e.g., "500m"
                        memory: <MEMORY_LIMIT>    # e.g., "512Mi"

        tekton-pipelines-webhook:
          spec:
            replicas: <REPLICA_COUNT>  # e.g., 1
            template:
              spec:
                containers:
                  - name: webhook
                    resources:
                      requests:
                        cpu: <CPU_REQUEST>        # e.g., "500m"
                        memory: <MEMORY_REQUEST>  # e.g., "256Mi"
                      limits:
                        cpu: <CPU_LIMIT>          # e.g., "1"
                        memory: <MEMORY_LIMIT>    # e.g., "500Mi"

        tekton-events-controller:
          spec:
            replicas: <REPLICA_COUNT>  # e.g., 1
            template:
              spec:
                containers:
                  - name: tekton-events-controller
                    resources:
                      requests:
                        cpu: <CPU_REQUEST>        # e.g., "100m"
                        memory: <MEMORY_REQUEST>  # e.g., "100Mi"
                      limits:
                        cpu: <CPU_LIMIT>          # e.g., "200m"
                        memory: <MEMORY_LIMIT>    # e.g., "256Mi"

Step 3

Submit the configuration and wait for the Pods to update.

$ kubectl get pods -n tekton-pipelines -w

NAME                                                    READY   STATUS    RESTARTS   AGE
tekton-pipelines-controller-648d87488b-fq9bc            1/1     Running   0          2m21s
tekton-pipelines-remote-resolvers-79554f5959-cbm6x      1/1     Running   0          2m21s
tekton-pipelines-webhook-5cd9847998-864zf               1/1     Running   0          2m20s
tekton-events-controller-5c97b7554c-m59m6               1/1     Running   0          2m21s

Operation Result

You can see that the resource quota configurations for the Pipeline related components are effective.

$ kubectl get deployments.apps -n tekton-pipelines tekton-pipelines-controller tekton-pipelines-remote-resolvers tekton-pipelines-webhook tekton-events-controller -o yaml | grep 'resources:' -A 6

          resources:
            limits:
              cpu: "1"
              memory: 1Gi
            requests:
              cpu: 500m
              memory: 512Mi
--
          resources:
            limits:
              cpu: 500m
              memory: 512Mi
            requests:
              cpu: 200m
              memory: 256Mi
--
          resources:
            limits:
              cpu: "2"
              memory: 500Mi
            requests:
              cpu: "1"
              memory: 256Mi
--
          resources:
            limits:
              cpu: 200m
              memory: 256Mi
            requests:
              cpu: 100m
              memory: 100Mi

Verifying `Pod` Resource Quota Configuration

Create a `TaskRun`

$ cat <<'EOF' | kubectl create -f -
apiVersion: tekton.dev/v1
kind: TaskRun
metadata:
  name: hello
  namespace: default
spec:
  taskSpec:
    steps:
      - name: hello
        image: alpine
        command: ["echo", "hello"]
EOF

Wait for the `TaskRun` to Complete

$ kubectl get taskruns.tekton.dev -n default hello

NAME    SUCCEEDED   REASON      STARTTIME   COMPLETIONTIME
hello   True        Succeeded   2m41s       2m28s

View the `Pod` Resource Quota Configuration

$ kubectl get pods -n default hello-hello-pod -o yaml

apiVersion: v1
kind: Pod
metadata:
  name: hello-pod
  namespace: default
spec:
  containers:
    - image: alpine
      name: step-hello
      resources: {}
  initContainers:
    - name: prepare
      resources:
        limits:
          cpu: 100m
          memory: 256Mi
        requests:
          cpu: 50m
          memory: 64Mi

You can see that the resource quota for the initContainers container prepare in the Pod matches the resource quotas configured in the config-defaults ConfigMap.

References

Configuring Resource Quotas for Pipeline Components

Overview

Configure resource quotas related to the Pipeline component.

Use Cases

Adjust the resource quotas for the Pipeline component
Set default resource quotas for init-containers and containers created by TaskRun

Prerequisites

The Tekton Operator component must be installed
TektonConfig resources must have been automatically created in the environment
The document on Adjusting Optional Configuration Items for Subcomponents should be read

Resource Configuration Guidelines

Before configuring resource quotas:

Assess your cluster's available resources and capacity
Consider your workload characteristics and performance requirements
Start with conservative values and adjust based on monitoring data
Test configurations in non-production environments first

Steps

Step 1

Edit the TektonConfig resource

$ kubectl edit tektonconfigs.operator.tekton.dev config

Step 2

WARNING

Modifying the configuration may trigger a rolling update of the component Pods, which could lead to temporary service unavailability. Please execute this at an appropriate time.

Example of modifying the spec.pipeline.options.deployments configuration:

apiVersion: operator.tekton.dev/v1alpha1
kind: TektonConfig
metadata:
  name: config
spec:
  pipeline:
    options:
      disabled: false

      configMaps:
        config-defaults:
          data:
            # Add default container resource quotas
            # Adjust the values below according to your cluster's resource capacity and workload requirements
            default-container-resource-requirements: |
              place-scripts: # updates resource requirements of a 'place-scripts' container
                requests:
                  memory: "<MEMORY_REQUEST>"  # e.g., "128Mi"
                  cpu: "<CPU_REQUEST>"        # e.g., "250m"
                limits:
                  memory: "<MEMORY_LIMIT>"    # e.g., "512Mi"
                  cpu: "<CPU_LIMIT>"          # e.g., "500m"

              prepare: # updates resource requirements of a 'prepare' container
                requests:
                  memory: "<MEMORY_REQUEST>"  # e.g., "128Mi"
                  cpu: "<CPU_REQUEST>"        # e.g., "250m"
                limits:
                  memory: "<MEMORY_LIMIT>"    # e.g., "256Mi"
                  cpu: "<CPU_LIMIT>"          # e.g., "500m"

              working-dir-initializer: # updates resource requirements of a 'working-dir-initializer' container
                requests:
                  memory: "<MEMORY_REQUEST>"  # e.g., "128Mi"
                  cpu: "<CPU_REQUEST>"        # e.g., "250m"
                limits:
                  memory: "<MEMORY_LIMIT>"    # e.g., "512Mi"
                  cpu: "<CPU_LIMIT>"          # e.g., "500m"

              prefix-scripts: # updates resource requirements of containers which starts with 'scripts-'
                requests:
                  memory: "<MEMORY_REQUEST>"  # e.g., "128Mi"
                  cpu: "<CPU_REQUEST>"        # e.g., "250m"
                limits:
                  memory: "<MEMORY_LIMIT>"    # e.g., "512Mi"
                  cpu: "<CPU_LIMIT>"          # e.g., "500m"

              prefix-sidecar-scripts: # updates resource requirements of containers which starts with 'sidecar-scripts-'
                requests:
                  memory: "<MEMORY_REQUEST>"  # e.g., "128Mi"
                  cpu: "<CPU_REQUEST>"        # e.g., "250m"
                limits:
                  memory: "<MEMORY_LIMIT>"    # e.g., "512Mi"
                  cpu: "<CPU_LIMIT>"          # e.g., "500m"

              sidecar-tekton-log-results: # updates resource requirements of a 'sidecar-tekton-log-results' container
                requests:
                  memory: "<MEMORY_REQUEST>"  # e.g., "128Mi"
                  cpu: "<CPU_REQUEST>"        # e.g., "100m"
                limits:
                  memory: "<MEMORY_LIMIT>"    # e.g., "256Mi"
                  cpu: "<CPU_LIMIT>"          # e.g., "250m"

      deployments:
        # Adjust the resource values below according to your cluster's capacity and performance requirements
        tekton-pipelines-controller:
          spec:
            replicas: <REPLICA_COUNT>  # e.g., 1
            template:
              spec:
                containers:
                  - name: tekton-pipelines-controller
                    resources:
                      requests:
                        cpu: <CPU_REQUEST>        # e.g., "500m"
                        memory: <MEMORY_REQUEST>  # e.g., "512Mi"
                      limits:
                        cpu: <CPU_LIMIT>          # e.g., "1"
                        memory: <MEMORY_LIMIT>    # e.g., "1Gi"

        tekton-pipelines-remote-resolvers:
          spec:
            replicas: <REPLICA_COUNT>  # e.g., 1
            template:
              spec:
                containers:
                  - name: controller
                    resources:
                      requests:
                        cpu: <CPU_REQUEST>        # e.g., "200m"
                        memory: <MEMORY_REQUEST>  # e.g., "256Mi"
                      limits:
                        cpu: <CPU_LIMIT>          # e.g., "500m"
                        memory: <MEMORY_LIMIT>    # e.g., "512Mi"

        tekton-pipelines-webhook:
          spec:
            replicas: <REPLICA_COUNT>  # e.g., 1
            template:
              spec:
                containers:
                  - name: webhook
                    resources:
                      requests:
                        cpu: <CPU_REQUEST>        # e.g., "500m"
                        memory: <MEMORY_REQUEST>  # e.g., "256Mi"
                      limits:
                        cpu: <CPU_LIMIT>          # e.g., "1"
                        memory: <MEMORY_LIMIT>    # e.g., "500Mi"

        tekton-events-controller:
          spec:
            replicas: <REPLICA_COUNT>  # e.g., 1
            template:
              spec:
                containers:
                  - name: tekton-events-controller
                    resources:
                      requests:
                        cpu: <CPU_REQUEST>        # e.g., "100m"
                        memory: <MEMORY_REQUEST>  # e.g., "100Mi"
                      limits:
                        cpu: <CPU_LIMIT>          # e.g., "200m"
                        memory: <MEMORY_LIMIT>    # e.g., "256Mi"

Step 3

Submit the configuration and wait for the Pods to update.

$ kubectl get pods -n tekton-pipelines -w

NAME                                                    READY   STATUS    RESTARTS   AGE
tekton-pipelines-controller-648d87488b-fq9bc            1/1     Running   0          2m21s
tekton-pipelines-remote-resolvers-79554f5959-cbm6x      1/1     Running   0          2m21s
tekton-pipelines-webhook-5cd9847998-864zf               1/1     Running   0          2m20s
tekton-events-controller-5c97b7554c-m59m6               1/1     Running   0          2m21s

Operation Result

You can see that the resource quota configurations for the Pipeline related components are effective.

$ kubectl get deployments.apps -n tekton-pipelines tekton-pipelines-controller tekton-pipelines-remote-resolvers tekton-pipelines-webhook tekton-events-controller -o yaml | grep 'resources:' -A 6

          resources:
            limits:
              cpu: "1"
              memory: 1Gi
            requests:
              cpu: 500m
              memory: 512Mi
--
          resources:
            limits:
              cpu: 500m
              memory: 512Mi
            requests:
              cpu: 200m
              memory: 256Mi
--
          resources:
            limits:
              cpu: "2"
              memory: 500Mi
            requests:
              cpu: "1"
              memory: 256Mi
--
          resources:
            limits:
              cpu: 200m
              memory: 256Mi
            requests:
              cpu: 100m
              memory: 100Mi

Verifying `Pod` Resource Quota Configuration

Create a `TaskRun`

$ cat <<'EOF' | kubectl create -f -
apiVersion: tekton.dev/v1
kind: TaskRun
metadata:
  name: hello
  namespace: default
spec:
  taskSpec:
    steps:
      - name: hello
        image: alpine
        command: ["echo", "hello"]
EOF

Wait for the `TaskRun` to Complete

$ kubectl get taskruns.tekton.dev -n default hello

NAME    SUCCEEDED   REASON      STARTTIME   COMPLETIONTIME
hello   True        Succeeded   2m41s       2m28s

View the `Pod` Resource Quota Configuration

$ kubectl get pods -n default hello-hello-pod -o yaml

apiVersion: v1
kind: Pod
metadata:
  name: hello-pod
  namespace: default
spec:
  containers:
    - image: alpine
      name: step-hello
      resources: {}
  initContainers:
    - name: prepare
      resources:
        limits:
          cpu: 100m
          memory: 256Mi
        requests:
          cpu: 50m
          memory: 64Mi

You can see that the resource quota for the initContainers container prepare in the Pod matches the resource quotas configured in the config-defaults ConfigMap.

Pipelines

Triggers

Operator

Results

Configuring Resource Quotas for Pipeline Components

TOC

Overview

Use Cases

Prerequisites

Resource Configuration Guidelines

Steps

Step 1

Step 2

Step 3

Operation Result

Verifying `Pod` Resource Quota Configuration

Create a `TaskRun`

Wait for the `TaskRun` to Complete

View the `Pod` Resource Quota Configuration

References

Configuring Resource Quotas for Pipeline Components

TOC

Overview

Use Cases

Prerequisites

Resource Configuration Guidelines

Steps

Step 1

Step 2

Step 3

Operation Result

Verifying `Pod` Resource Quota Configuration

Create a `TaskRun`

Wait for the `TaskRun` to Complete

View the `Pod` Resource Quota Configuration

References

Pipelines

Triggers

Operator

Results

#Configuring Resource Quotas for Pipeline Components

#TOC

#Overview

#Use Cases

#Prerequisites

#Resource Configuration Guidelines

#Steps

#Step 1

#Step 2

#Step 3

#Operation Result

#Verifying Pod Resource Quota Configuration

#Create a TaskRun

#Wait for the TaskRun to Complete

#View the Pod Resource Quota Configuration

#References

#Configuring Resource Quotas for Pipeline Components

#TOC

#Overview

#Use Cases

#Prerequisites

#Resource Configuration Guidelines

#Steps

#Step 1

#Step 2

#Step 3

#Operation Result

#Verifying Pod Resource Quota Configuration

#Create a TaskRun

#Wait for the TaskRun to Complete

#View the Pod Resource Quota Configuration

#References

Configuring Resource Quotas for Pipeline Components

TOC

Overview

Use Cases

Prerequisites

Resource Configuration Guidelines

Steps

Step 1

Step 2

Step 3

Operation Result

Verifying `Pod` Resource Quota Configuration

Create a `TaskRun`

Wait for the `TaskRun` to Complete

View the `Pod` Resource Quota Configuration

References

Configuring Resource Quotas for Pipeline Components

TOC

Overview

Use Cases

Prerequisites

Resource Configuration Guidelines

Steps

Step 1

Step 2

Step 3

Operation Result

Verifying `Pod` Resource Quota Configuration

Create a `TaskRun`

Wait for the `TaskRun` to Complete

View the `Pod` Resource Quota Configuration

References