Overview

A PipelineRun allows you to instantiate and execute a Pipeline on-cluster. A Pipeline specifies one or more Tasks in the desired order of execution. A PipelineRun executes the Tasks in the Pipeline in the order they are specified until all Tasks have executed successfully or a failure occurs.

Note: A PipelineRun automatically creates corresponding TaskRuns for every Task in your Pipeline .

The Status field tracks the current state of a PipelineRun , and can be used to monitor progress. This field contains the status of every TaskRun , as well as the full PipelineSpec used to instantiate this PipelineRun , for full auditability.

Configuring a PipelineRun

A PipelineRun definition supports the following fields:

Specifying the target Pipeline

You must specify the target Pipeline that you want the PipelineRun to execute, either by referencing an existing Pipeline definition, or embedding a Pipeline definition directly in the PipelineRun .

To specify the target Pipeline by reference, use the pipelineRef field:

spec:
  pipelineRef:
    name: mypipeline

To embed a Pipeline definition in the PipelineRun , use the pipelineSpec field:

spec:
  pipelineSpec:
    tasks:
      - name: task1
        taskRef:
          name: mytask

The Pipeline in the pipelineSpec example example displays morning and evening greetings. Once you create and execute it, you can check the logs for its Pods :

kubectl logs $(kubectl get pods -o name | grep pipelinerun-echo-greetings-echo-good-morning)
Good Morning, Bob!
kubectl logs $(kubectl get pods -o name | grep pipelinerun-echo-greetings-echo-good-night)
Good Night, Bob!

You can also embed a Task definition the embedded Pipeline definition:

spec:
  pipelineSpec:
    tasks:
      - name: task1
        taskSpec:
          steps: ...

In the taskSpec in pipelineSpec example it’s Tasks all the way down!

You can also specify labels and annotations with taskSpec which are propagated to each taskRun and then to the respective pods. These labels can be used to identify and filter pods for further actions (such as collecting pod metrics, and cleaning up completed pod with certain labels, etc) even being part of one single Pipeline.

spec:
  pipelineSpec:
    tasks:
      - name: task1
        taskSpec:
          metadata:
            labels:
              pipeline-sdk-type: kfp
        # ...
      - name: task2
        taskSpec:
          metadata:
            labels:
              pipeline-sdk-type: tfx
        # ...

Tekton Bundles

A Tekton Bundle is an OCI artifact that contains Tekton resources like Tasks which can be referenced within a taskRef .

You can reference a Tekton bundle in a TaskRef in both v1 and v1beta1 using remote resolution . The example syntax shown below for v1 uses remote resolution.

In v1beta1 , you can also reference a Tekton bundle using OCI bundle syntax, which has been deprecated in favor of remote resolution. The example shown below for v1beta1 uses OCI bundle syntax, and requires enabling enable-tekton-oci-bundles: "true" feature flag.

The syntax and caveats are similar to using Tekton Bundles for Task references in Pipelines or TaskRuns .

Tekton Bundles may be constructed with any toolsets that produce valid OCI image artifacts so long as the artifact adheres to the contract .

Remote Pipelines

( beta feature )

A pipelineRef field may specify a Pipeline in a remote location such as git. Support for specific types of remote will depend on the Resolvers your cluster’s operator has installed. For more information including a tutorial, please check resolution docs . The below example demonstrates referencing a Pipeline in git:

spec:
  pipelineRef:
    resolver: git
    params:
    - name: url
      value: https://github.com/tektoncd/catalog.git
    - name: revision
      value: abc123
    - name: pathInRepo
      value: /pipeline/buildpacks/0.1/buildpacks.yaml

Specifying Task-level ComputeResources

( alpha only )

Task-level compute resources can be configured in PipelineRun.TaskRunSpecs.ComputeResources or TaskRun.ComputeResources .

apiVersion: tekton.dev/v1 # or tekton.dev/v1beta1
kind: Pipeline
metadata:
  name: pipeline
spec:
  tasks:
    - name: task
apiVersion: tekton.dev/v1 # or tekton.dev/v1beta1
kind: PipelineRun
metadata:
  name: pipelinerun 
spec:
  pipelineRef:
    name: pipeline
  taskRunSpecs:
    - pipelineTaskName: task
      computeResources:
        requests:
          cpu: 2

Further details and examples could be found in Compute Resources in Tekton .

Specifying Parameters

(See also Specifying Parameters in Tasks )

You can specify Parameters that you want to pass to the Pipeline during execution, including different values of the same parameter for different Tasks in the Pipeline .

Note: You must specify all the Parameters that the Pipeline expects. Parameters that have default values specified in Pipeline are not required to be provided by PipelineRun.

For example:

spec:
  params:
    - name: pl-param-x
      value: "100"
    - name: pl-param-y
      value: "500"

You can pass in extra Parameters if needed depending on your use cases. An example use case is when your CI system autogenerates PipelineRuns and it has Parameters it wants to provide to all PipelineRuns . Because you can pass in extra Parameters , you don’t have to go through the complexity of checking each Pipeline and providing only the required params.

Propagated Parameters

When using an inlined spec, parameters from the parent PipelineRun will be propagated to any inlined specs without needing to be explicitly defined. This allows authors to simplify specs by automatically propagating top-level parameters down to other inlined resources.

apiVersion: tekton.dev/v1 # or tekton.dev/v1beta1
kind: PipelineRun
metadata:
  generateName: pr-echo-
spec:
  params:
    - name: HELLO
      value: "Hello World!"
    - name: BYE
      value: "Bye World!"
  pipelineSpec:
    tasks:
      - name: echo-hello
        taskSpec:
          steps:
            - name: echo
              image: ubuntu
              script: |
                #!/usr/bin/env bash
                echo "$(params.HELLO)"                
      - name: echo-bye
        taskSpec:
          steps:
            - name: echo
              image: ubuntu
              script: |
                #!/usr/bin/env bash
                echo "$(params.BYE)"                

On executing the pipeline run, the parameters will be interpolated during resolution. The specifications are not mutated before storage and so it remains the same. The status is updated.

apiVersion: tekton.dev/v1 # or tekton.dev/v1beta1
kind: PipelineRun
metadata:
  




    
name: pr-echo-szzs9
spec:
  params:
  - name: HELLO
    value: Hello World!
  - name: BYE
    value: Bye World!
  pipelineSpec:
    tasks:
    - name: echo-hello
      taskSpec:
        steps:
        - image: ubuntu
          name: echo
          script: |
            #!/usr/bin/env bash
            echo "$(params.HELLO)"            
    - name: echo-bye
      taskSpec:
        steps:
        - image: ubuntu
          name: echo
          script: |
            #!/usr/bin/env bash
            echo "$(params.BYE)"            
status:
  conditions:
  - lastTransitionTime: "2022-04-07T12:34:58Z"
    message: 'Tasks Completed: 2 (Failed: 0, Canceled 0), Skipped: 0'
    reason: Succeeded
    status: "True"
    type: Succeeded
  pipelineSpec:
  childReferences:
  - name: pr-echo-szzs9-echo-hello
    pipelineTaskName: echo-hello
    kind: TaskRun
  - name: pr-echo-szzs9-echo-bye
    pipelineTaskName: echo-bye
    kind: TaskRun

Scope and Precedence

When Parameters names conflict, the inner scope would take precedence as shown in this example:

apiVersion: tekton.dev/v1 # or tekton.dev/v1beta1
kind: PipelineRun
metadata:
  generateName: pr-echo-
spec:
  params:
  - name: HELLO
    value: "Hello World!"
  - name: BYE
    value: "Bye World!"
  pipelineSpec:
    tasks:
      - name: echo-hello
        params:
        - name: HELLO
          value: "Sasa World!"
        taskSpec:
          params:
            - name: HELLO
              type: string
          steps:
            - name: echo
              image: ubuntu
              script: |
                #!/usr/bin/env bash
                echo "$(params.HELLO)"                

resolves to

# Successful execution of the above PipelineRun
apiVersion: tekton.dev/v1 # or tekton.dev/v1beta1
kind: PipelineRun
metadata:
  name: pr-echo-szzs9
spec:
status:
  conditions:
    - lastTransitionTime: "2022-04-07T12:34:58Z"
      message: 'Tasks Completed: 2 (Failed: 0, Canceled 0), Skipped: 0'
      reason: Succeeded
      status: "True"
      type: Succeeded
  childReferences:
  - name: pr-echo-szzs9-echo-hello
    pipelineTaskName: echo-hello
    kind: TaskRun

Default Values

When Parameter specifications have default values, the Parameter value provided at runtime would take precedence to give users control, as shown in this example:

apiVersion: tekton.dev/v1 # or tekton.dev/v1beta1
kind: PipelineRun
metadata:
  




    
generateName: pr-echo-
spec:
  params:
  - name: HELLO
    value: "Hello World!"
  - name: BYE
    value: "Bye World!"
  pipelineSpec:
    tasks:
      - name: echo-hello
        taskSpec:
          params:
          - name: HELLO
            type: string
            default: "Sasa World!"
          steps:
            - name: echo
              image: ubuntu
              script: |
                #!/usr/bin/env bash
                echo "$(params.HELLO)"                

resolves to

# Successful execution of the above PipelineRun
apiVersion: tekton.dev/v1 # or tekton.dev/v1beta1
kind: PipelineRun
metadata:
  name: pr-echo-szzs9
spec:
status:
  conditions:
    - lastTransitionTime: "2022-04-07T12:34:58Z"
      message: 'Tasks Completed: 2 (Failed: 0, Canceled 0), Skipped: 0'
      reason: Succeeded
      status: "True"
      type: Succeeded
  childReferences:
  - name: pr-echo-szzs9-echo-hello
    pipelineTaskName: echo-hello
    kind: TaskRun

Referenced Resources

When a PipelineRun definition has referenced specifications but does not explicitly pass Parameters, the PipelineRun will be created but the execution will fail because of missing Parameters.

# Invalid PipelineRun attempting to propagate Parameters to referenced Tasks
apiVersion: tekton.dev/v1 # or tekton.dev/v1beta1
kind: PipelineRun
metadata:
  generateName: pr-echo-
spec:
  params:
  - name: HELLO
    value: "Hello World!"
  - name: BYE
    value: "Bye World!"
  pipelineSpec:
    tasks:
      - name: echo-hello
        taskRef:
          name: echo-hello
      - name: echo-bye
        taskRef:
          name: echo-bye
apiVersion: tekton.dev/v1 # or tekton.dev/v1beta1
kind: Task
metadata:
  name: echo-hello
spec:
  steps:
    - name: echo
      image: ubuntu
      script: |
        #!/usr/bin/env bash
        echo "$(params.HELLO)"        
apiVersion: tekton.dev/v1 # or tekton.dev/v1beta1
kind: Task
metadata:
  name: echo-bye
spec:
  steps:
    - name: echo
      image: ubuntu
      script: |
        #!/usr/bin/env bash
        echo "$(params.BYE)"        

Fails as follows:

# Failed execution of the above PipelineRun
apiVersion: tekton.dev/v1 # or tekton.dev/v1beta1
kind: PipelineRun
metadata:
  name: pr-echo-24lmf
spec:
  params:
  - name: HELLO
    value




    
: Hello World!
  - name: BYE
    value: Bye World!
  pipelineSpec:
    tasks:
    - name: echo-hello
      taskRef:
        kind: Task
        name: echo-hello
    - name: echo-bye
      taskRef:
        kind: Task
        name: echo-bye
status:
  conditions:
  - lastTransitionTime: "2022-04-07T20:24:51Z"
    message: 'invalid input params for task echo-hello: missing values for
              these params which have no default values: [HELLO]'
    reason: PipelineValidationFailed
    status: "False"
    type: Succeeded

Object Parameters

( alpha only )

When using an inlined spec, object parameters from the parent PipelineRun will also be propagated to any inlined specs without needing to be explicitly defined. This allows authors to simplify specs by automatically propagating top-level parameters down to other inlined resources. When propagating object parameters, scope and precedence also holds as shown below.

apiVersion: tekton.dev/v1 # or tekton.dev/v1beta1 
kind: PipelineRun              
metadata:
  generateName: pipelinerun-object-param-result 
spec:
  params:
    - name: gitrepo            
      value:                   
        url: abc.com           
        commit: sha123         
  pipelineSpec:                
    tasks:                     
      - name: task1            
        params:                
          - name: gitrepo      
            value:
              branch: main     
              url: xyz.com     
        taskSpec:
          steps:
            - name: write-result            
              image: bash      
              args: [          
                "echo",        
                "--url=$(params.gitrepo.url)",  
                "--commit=$(params.gitrepo.commit)",
                "--branch=$(params.gitrepo.branch)",

resolves to

apiVersion: tekton.dev/v1 # or tekton.dev/v1beta1
kind: PipelineRun
metadata:
  name: pipelinerun-object-param-resultpxp59
spec:
  params:
  - name: gitrepo
    value:
      commit: sha123
      url: abc.com
  pipelineSpec:
    tasks:
    - name: task1
      params:
      - name: gitrepo
        value:
          branch: main
          url: xyz.com
      taskSpec:
        metadata: {}
        spec: null
        steps:
        - args:
          - echo
          - --url=$(params.gitrepo.url)
          - --commit=$(params.gitrepo.commit)
          - --branch=$(params.gitrepo.branch)
          image: bash
          name: write-result   
status:
  completionTime: "2022-09-08T17:22:01Z"
  conditions:
  - lastTransitionTime: "2022-09-08T17:22:01Z"
    message: 'Tasks Completed: 1 (Failed: 0, Cancelled 0), Skipped: 0'
    reason: Succeeded
    status: "True"
    type: Succeeded
  pipelineSpec:
    tasks:
    




    
- name: task1
      params:
      - name: gitrepo
        value:
          branch: main
          url: xyz.com
      taskSpec:
        metadata: {}
        spec: null
        steps:
        - args:
          - echo
          - --url=xyz.com
          - --commit=sha123
          - --branch=main
          image: bash
          name: write-result
  startTime: "2022-09-08T17:21:57Z"
  childReferences:
  - name: pipelinerun-object-param-resultpxp59-task1
    pipelineTaskName: task1
    kind: TaskRun
	taskSpec:
          steps:
          - args:
            - echo
            - --url=xyz.com
            - --commit=sha123
            - --branch=main
            image: bash
            name: write-result

Specifying custom ServiceAccount credentials

You can execute the Pipeline in your PipelineRun with a specific set of credentials by specifying a ServiceAccount object name in the serviceAccountName field in your PipelineRun definition. If you do not explicitly specify this, the TaskRuns created by your PipelineRun will execute with the credentials specified in the configmap-defaults ConfigMap . If this default is not specified, the TaskRuns will execute with the default service account set for the target namespace .

For more information, see ServiceAccount .

Custom tasks may or may not use a service account name. Consult the documentation of the custom task that you are using to determine whether it supports a service account name.

Mapping ServiceAccount credentials to Tasks

If you require more granularity in specifying execution credentials, use the taskRunSpecs[].taskServiceAccountName field to map a specific serviceAccountName value to a specific Task in the Pipeline . This overrides the global serviceAccountName you may have set for the Pipeline as described in the previous section.

For example, if you specify these mappings:

then test-task will execute using the sa-1 account while build-task will execute with sa-for-build .

Specifying a Pod template

You can specify a Pod template configuration that will serve as the configuration starting point for the Pod in which the container images specified in your Tasks will execute. This allows you to customize the Pod configuration specifically for each TaskRun .

In the following example, the Task defines a volumeMount object named my-cache . The PipelineRun provisions this object for the Task using a persistentVolumeClaim and executes it as user 1001.

Custom tasks may or may not use a pod template. Consult the documentation of the custom task that you are using to determine whether it supports a pod template.

Specifying taskRunSpecs

Specifies a list of PipelineTaskRunSpec which contains TaskServiceAccountName , TaskPodTemplate and PipelineTaskName . Mapping the specs to the corresponding Task based upon the TaskName a PipelineTask will run with the configured TaskServiceAccountName and TaskPodTemplate overwriting the pipeline wide ServiceAccountName and podTemplate configuration, for example:

If used with this Pipeline , build-task will use the task specific PodTemplate (where nodeSelector has disktype equal to ssd ). PipelineTaskRunSpec may also contain StepSpecs and SidecarSpecs ; see Overriding Task Steps and Sidecars for more information.

The optional annotations and labels can be added under a Metadata field as for a specific running context.

Rendering needed secrets with Vault:

spec:
  pipelineRef:
    name: pipeline-name
  taskRunSpecs:
    - pipelineTaskName: task-name
      metadata: 
        annotations:
          vault.hashicorp.com/agent-inject-secret-foo: "/path/to/foo"
          vault.hashicorp.com/role: role-name

Updating labels applied in a runtime context:

spec:
  pipelineRef:
    name: pipeline-name
  taskRunSpecs:
    - pipelineTaskName: task-name
      metadata: 
        labels:
          app: cloudevent

If a metadata key is present in different levels, the value that will be used in the PipelineRun is determined using this precedence order: PipelineRun.spec.taskRunSpec.metadata > PipelineRun.metadata > Pipeline.spec.tasks.taskSpec.metadata .

Specifying Workspaces

If your Pipeline specifies one or more Workspaces , you must map those Workspaces to the corresponding physical volumes in your PipelineRun definition. For example, you can map a PersistentVolumeClaim volume to a Workspace as follows:

workspaces:
  - name: myworkspace # must match workspace name in Task
    persistentVolumeClaim:
      claimName: mypvc # this PVC must already exist
    subPath: my-subdir

workspaces[].subPath can be an absolute value or can reference pipelineRun context variables, such as, $(context.pipelineRun.name) or $(context.pipelineRun.uid) .

For more information, see the following topics:

Custom tasks may or may not use workspaces. Consult the documentation of the custom task that you are using to determine whether it supports workspaces.

Propagated Workspaces

When using an embedded spec, workspaces from the parent PipelineRun will be propagated to any inlined specs without needing to be explicitly defined. This allows authors to simplify specs by automatically propagating top-level workspaces down to other inlined resources. Workspace substutions will only be made for commands , args and script fields of steps , stepTemplates , and sidecars .

# Inline specifications of a PipelineRun
apiVersion: tekton.dev/v1 # or tekton.dev/v1beta1
kind: PipelineRun
metadata:
  generateName: recipe-time-
spec:
  workspaces:
    - name: shared-data
      volumeClaimTemplate:
        spec:
          accessModes:
            - ReadWriteOnce
          resources:
            requests:
              storage: 16Mi
          volumeMode: Filesystem
  pipelineSpec:
    #workspaces:
    #  - name: shared-data
    tasks:
    - name: fetch-secure-data
      # workspaces:
      #   - name: shared-data 
      taskSpec:
        # workspaces:
        #   - name: shared-data 
        steps:
        - name: fetch-and-write-secure
          image: ubuntu
          script: |
                        echo hi >> $(workspaces.shared-data.path)/recipe.txt
    - name: print-the-recipe
      # workspaces:
      #   - name: shared-data 
      runAfter:
        - fetch-secure-data
      taskSpec:
        # workspaces:
        #   - name: shared-data 
        steps:
        - name: print-secrets
          image: ubuntu
          script: cat $(workspaces.shared-data.path)/recipe.txt

On executing the pipeline run, the workspaces will be interpolated during resolution.

# Successful execution of the above PipelineRun
apiVersion: tekton.dev/v1 # or tekton.dev/v1beta1
kind: PipelineRun
metadata:
  generateName: recipe-time-
spec:
  pipelineSpec:
status:
  completionTime: "2022-06-02T18:17:02Z"
  conditions:
  - lastTransitionTime: "2022-06-02T18:17:02Z"
    message: 'Tasks Completed: 2 (Failed: 0, Canceled 0), Skipped: 0'
    reason: Succeeded
    status: "True"
    type: Succeeded
  pipelineSpec:
  childReferences:
  - name: recipe-time-lslt9-fetch-secure-data
    pipelineTaskName: fetch-secure-data
    kind: TaskRun
  - name: recipe-time-lslt9-print-the-recipe
    pipelineTaskName: print-the-recipe
    kind: TaskRun

Workspace Referenced Resources

Workspaces cannot be propagated to referenced specifications. For example, the following Pipeline will fail when executed because the workspaces defined in the PipelineRun cannot be propagated to the referenced Pipeline.

# PipelineRun attempting to propagate Workspaces to referenced Tasks
apiVersion: v1
kind: PersistentVolumeClaim
metadata:
  name: shared-task-storage
spec:
  resources:
    requests:
      storage: 16Mi
  volumeMode: Filesystem
  accessModes:
    - ReadWriteOnce
apiVersion: tekton.dev/v1 # or tekton.dev/v1beta1
kind: Pipeline
metadata:
  name: fetch-and-print-recipe





    
spec:
  tasks:
  - name: fetch-the-recipe
    taskRef:
      name: fetch-secure-data
  - name: print-the-recipe
    taskRef:
      name: print-data
    runAfter:
      - fetch-the-recipe
apiVersion: tekton.dev/v1 # or tekton.dev/v1beta1
kind: PipelineRun
metadata:
  generateName: recipe-time-
spec:
  pipelineRef:
    name: fetch-and-print-recipe
  workspaces:
  - name: shared-data
    persistentVolumeClaim:
      claimName: shared-task-storage

Upon execution, this will cause failures:

# Failed execution of the above PipelineRun
apiVersion: tekton.dev/v1 # or tekton.dev/v1beta1
kind: PipelineRun
metadata:
  generateName: recipe-time-
spec:
  pipelineRef:
    name: fetch-and-print-recipe
  workspaces:
  - name: shared-data
    persistentVolumeClaim:
      claimName: shared-task-storage
status:
  completionTime: "2022-06-02T19:02:58Z"
  conditions:
  - lastTransitionTime: "2022-06-02T19:02:58Z"
    message: 'Tasks Completed: 1 (Failed: 1, Canceled 0), Skipped: 1'
    reason: Failed
    status: "False"
    type: Succeeded
  pipelineSpec:
  childReferences:
  - name: recipe-time-v5scg-fetch-the-recipe
    pipelineTaskName: fetch-the-recipe
    kind: TaskRun

Referenced TaskRuns within Embedded PipelineRuns

As mentioned in the Workspace Referenced Resources , workspaces can only be propagated from PipelineRuns to embedded Pipeline specs, not Pipeline references. Similarly, workspaces can only be propagated from a Pipeline to embedded Task specs, not referenced Tasks. For example:

# PipelineRun attempting to propagate Workspaces to referenced Tasks
apiVersion: tekton.dev/v1 # or tekton.dev/v1beta1
kind: Task
metadata:
  name: fetch-secure-data
spec:
  workspaces: # If Referenced, Workspaces need to be explicitly declared
  - name: shared-data
  steps:
  - name: fetch-and-write
    image: ubuntu
    script: |
            echo $(workspaces.shared-data.path)      
apiVersion: tekton.dev/v1 # or tekton.dev/v1beta1
kind: PipelineRun
metadata:
  generateName: recipe-time-
spec:
  workspaces:
  - name: shared-data
    persistentVolumeClaim:
      claimName: shared-task-storage
  pipelineSpec:
    # workspaces: # Since this is embedded specs, Workspaces don’t need to be declared
    #    ...
    tasks:
    - name: fetch-the-recipe
      workspaces: # If referencing resources, Workspaces need to be explicitly declared
      - name: shared-data
      taskRef: # Referencing a resource
        name: fetch-secure-data
    - name: print-the-recipe
      # workspaces: # Since this is embedded specs, Workspaces don’t need to be declared
      #    ...
      taskSpec:
        # workspaces: # Since this is embedded specs, Workspaces don’t need to be declared
        #    ...
        steps:
        - name: 




    
print-secrets
          image: ubuntu
          script: cat $(workspaces.shared-data.path)/recipe.txt
      runAfter:
        - fetch-the-recipe

The above pipelinerun successfully resolves to:

# Successful execution of the above PipelineRun
apiVersion: tekton.dev/v1 # or tekton.dev/v1beta1
kind: PipelineRun
metadata:
  generateName: recipe-time-
spec:
  pipelineSpec:
  workspaces:
  - name: shared-data
    persistentVolumeClaim:
      claimName: shared-task-storage
status:
  completionTime: "2022-06-09T18:42:14Z"
  conditions:
  - lastTransitionTime: "2022-06-09T18:42:14Z"
    message: 'Tasks Completed: 2 (Failed: 0, Cancelled 0), Skipped: 0'
    reason: Succeeded
    status: "True"
    type: Succeeded
  pipelineSpec:
  childReferences:
  - name: recipe-time-pj6l7-fetch-the-recipe
    pipelineTaskName: fetch-the-recipe
    kind: TaskRun
  - name: recipe-time-pj6l7-print-the-recipe
    pipelineTaskName: print-the-recipe
    kind: TaskRun

Specifying LimitRange values

In order to only consume the bare minimum amount of resources needed to execute one Step at a time from the invoked Task , Tekton will request the compute values for CPU, memory, and ephemeral storage for each Step based on the LimitRange object(s), if present. Any Request or Limit specified by the user (on Task for example) will be left unchanged.

For more information, see the LimitRange support in Pipeline .

Configuring a failure timeout

You can use the timeouts field to set the PipelineRun's desired timeout value in minutes. There are three sub-fields:

For example:

timeouts:
  pipeline: "0h0m60s"
  tasks: "0h0m40s"
  finally: "0h0m20s"

All three sub-fields are optional, and will be automatically processed according to the following constraint:

Each timeout field is a duration conforming to Go’s ParseDuration format. For example, valid values are 1h30m , 1h , 1m , and 60s .

If any of the sub-fields are set to “0”, there is no timeout for that section of the PipelineRun, meaning that it will run until it completes successfully or encounters an error. To set timeouts.tasks or timeouts.finally to “0”, you must also set timeouts.pipeline to “0”.

The global default timeout is set to 60 minutes when you first install Tekton. You can set a different global default timeout value using the default-timeout-minutes field in config/config-defaults.yaml .

Example timeouts usages are as follows:

Combination 1: Set the timeout for the entire pipeline and reserve a portion of it for tasks .

kind: PipelineRun
spec:
  timeouts:
    pipeline: "0h4m0s"
    tasks: "0h1m0s"

Combination 2: Set the timeout for the entire pipeline and reserve a portion of it for finally .

kind: PipelineRun
spec:
  timeouts:
    pipeline: "0h4m0s"
    finally: "0h3m0s"

Combination 3: Set only a tasks timeout, with no timeout for the entire pipeline .

kind: PipelineRun
spec:
  timeouts:
    pipeline: "0"  # No timeout
    tasks: "0h3m0s"

Combination : Set only a finally timeout, with no timeout for the entire pipeline .

kind: PipelineRun
spec:
  timeouts:
    pipeline: "0"  # No timeout
    finally: "0h3m0s"

You can also use the Deprecated timeout field to set the PipelineRun's desired timeout value in minutes. If you do not specify this value in the PipelineRun , the global default timeout value applies. If you set the timeout to 0, the PipelineRun fails immediately upon encountering an error.

⚠️ ** timeout is deprecated and will be removed in future versions. Consider using timeouts instead.

PipelineRun status

The status field

Your PipelineRun ’s status field can contain the following fields:

Monitoring execution status

As your PipelineRun executes, its status field accumulates information on the execution of each TaskRun as well as the PipelineRun as a whole. This information includes the name of the pipeline Task associated to a TaskRun , the complete status of the TaskRun and details about whenExpressions that may be associated to a TaskRun .

The following example shows an extract from the status field of a PipelineRun that has executed successfully:

completionTime: "2020-05-04T02:19:14Z"
conditions:
  - lastTransitionTime: "2020-05-04T02:19:14Z"
    message: "Tasks Completed: 4, Skipped: 0"
    reason: Succeeded
    status: "True"
    type: Succeeded
startTime: "2020-05-04T02:00:11Z"
childReferences:
- name: triggers-release-nightly-frwmw-build
  pipelineTaskName: build
  kind: TaskRun

The following tables shows how to read the overall status of a PipelineRun . Completion time is set once a PipelineRun reaches status True or False :

When a PipelineRun changes status, events are triggered accordingly.

When a PipelineRun has Tasks that were skipped , the reason for skipping the task will be listed in the Skipped Tasks section of the status of the PipelineRun .

When a PipelineRun has Tasks with when expressions :

Conditions:
  Last Transition Time:  2020-08-27T15:07:34Z
  Message:               Tasks Completed: 1 (Failed: 0, Cancelled 0), Skipped: 1
  Reason:                Completed
  Status:                True
  Type:                  Succeeded
Skipped Tasks:
  Name:       skip-this-task
  Reason:     When Expressions evaluated to false
  When Expressions:
    Input:     foo
    Operator:  in
    Values:
    Input:     foo
    Operator:  notin
    Values:
ChildReferences:
- Name: pipelinerun-to-skip-task-run-this-task
  Pipeline Task Name:  run-this-task
  Kind: TaskRun

The name of the TaskRuns and Runs owned by a PipelineRun are univocally associated to the owning resource. If a PipelineRun resource is deleted and created with the same name, the child TaskRuns will be created with the same name as before. The base format of the name is <pipelinerun-name>-<pipelinetask-name> . If the PipelineTask has a Matrix , the name will have an int suffix with format <pipelinerun-name>-<pipelinetask-name>-<combination-id> . The name may vary according the logic of kmeta.ChildName .

Some examples:

Cancelling a PipelineRun

To cancel a PipelineRun that’s currently executing, update its definition to mark it as “Cancelled”. When you do so, the spawned TaskRuns are also marked as cancelled, all associated Pods are deleted, and their Retries are not executed. Pending finally tasks are not scheduled.

For example:

apiVersion: tekton.dev/v1 # or tekton.dev/v1beta1
kind: PipelineRun
metadata:
  name: go-example-git
spec:
  # […]
  status: "Cancelled"

Gracefully cancelling a PipelineRun

To gracefully cancel a PipelineRun that’s currently executing, update its definition to mark it as “CancelledRunFinally”. When you do so, the spawned TaskRuns are also marked as cancelled, all associated Pods are deleted, and their Retries are not executed. finally tasks are scheduled normally.

For example:

apiVersion: tekton.dev/v1 # or tekton.dev/v1beta1
kind: PipelineRun
metadata:
  name: go-example-git
spec:
  # […]
  status: "CancelledRunFinally"

Gracefully stopping a PipelineRun

To gracefully stop a PipelineRun that’s currently executing, update its definition to mark it as “StoppedRunFinally”. When you do so, the spawned TaskRuns are completed normally, including executing their retries , but no new non- finally task is scheduled. finally tasks are executed afterwards. For example:

apiVersion: tekton.dev/v1 # or tekton.dev/v1beta1
kind: PipelineRun
metadata:
  name: go-example-git
spec:
  # […]
  status: "StoppedRunFinally"

Pending PipelineRuns

A PipelineRun can be created as a “pending” PipelineRun meaning that it will not actually be started until the pending status is cleared.

Note that a PipelineRun can only be marked “pending” before it has started, this setting is invalid after the PipelineRun has been started.

To mark a PipelineRun as pending, set .spec.status to PipelineRunPending when creating it:

apiVersion: tekton.dev/v1 # or tekton.dev/v1beta1
kind: PipelineRun
metadata:
  name: go-example-git
spec:
  # […]
  status: "PipelineRunPending"

To start the PipelineRun, clear the .spec.status field. Alternatively, update the value to Cancelled to cancel it.

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