Github action to upload and run a Kubeflow pipeline to KubeFlow workspace.

This repository has been archived due to lack of engineering investment, but may still be useful. Also see equivalent Azure DevOps Marketplace Task and Kubemlops repository.

The following is an example of uploading a new pipeline, creating a new experiment, and running/monitoring the new pipeline on that experiment with this action:

on: [push]

jobs:
  kubeflow_upload_job:
    runs-on: ubuntu-latest
    name: Kubeflow Upload and Run Pipeline
    steps:
    - name: Checkout task
      uses: actions/checkout@master

    - name: Kubeflow Upload and Run Step
      id: upload_run
      uses: kaizentm/kubeflow-pipeline-github-action@master
      with:
        kubeflowEndpoint: '${{ secrets.KUBEFLOW_ENDPOINT }}'
        bearerToken: '${{ secrets.TOKEN }}'
        kubeflowPipelineTask: 'uploadNew'
        pipelineFilePath: 'action/code/tests/pipeline.py.tar.gz'
        newPipelineName: 'testPipeline'
        existingPipelineName: ''
        versionName: ''

        runName: 'testRun'
        pipeline: 'testPipeline'
        useDefaultVersion: 'true'
        pipelineVersion: ''
        pipelineParams: '{"name":"Var1", "value":"Val1"}, {"name":"Var2", "value":"Val2"}'
        runDescription: ''
        waitForRunToFinish: 'true'
        experiment: 'createNewExperiment'
        experimentName: 'testExperiment'
        experimentDescription: ''

The following is an example of uploading a new pipeline version and running the pipeline with the new version:

on: [push]

jobs:
  kubeflow_upload_job:
    runs-on: ubuntu-latest
    name: Kubeflow Upload and Run Pipeline
    steps:
    - name: Checkout task
      uses: actions/checkout@master

    - name: Kubeflow Upload and Run Step
      id: upload_run
      uses: kaizentm/kubeflow-pipeline-github-action@master
      with:
        kubeflowEndpoint: '${{ secrets.KUBEFLOW_ENDPOINT }}'
        bearerToken: '${{ secrets.TOKEN }}'
        kubeflowPipelineTask: 'uploadNewVersion'
        pipelineFilePath: 'action/code/tests/pipeline.py.tar.gz'
        newPipelineName: ''
        existingPipelineName: 'testPipeline'
        versionName: 'newVersion'

        runName: 'testRun'
        pipeline: 'testPipeline'
        useDefaultVersion: 'false'
        pipelineVersion: 'newVersion'
        pipelineParams: '{"name":"Var1", "value":"Val1"}, {"name":"Var2", "value":"Val2"}'
        runDescription: ''
        waitForRunToFinish: 'false'
        experiment: 'useExistingExperiment'
        experimentName: 'testExperiment'
        experimentDescription: ''

• kubeflowEndpoint: Kubeflow API endpoint base URL format http://yourURL/.
• bearerToken: Bearer token to of secured Kubeflow API. Read more on how to handle Creating and storing encrypted secrets on Github.
• kubeflowPipelineTask: Input either 'uploadNew' to upload a new pipeline or 'uploadNewVersion' to upload a new pipeline version.
• pipelineFilePath: The path compiled pipeline (*.tar.gz). Maximum allowed file size is 32MB.
• newPipelineName: Unique name for the new pipeline.
• existingPipelineName: Name of existing pipeline when creating new version.
• versionName: Unique name for the new pipeline version.
• pipeline: Unique name of the Kubeflow pipeline to create run.
• useDefaultVersion: If true, this will use the default version of the Kubeflow pipeline provided the pipeline name. Either input 'true' or 'false'.
• pipelineVersion: Unique name of the specific pipeline version to be used for creating run.
• runName: The name of your new run. Does not have to be unique.
• pipelineParams: Kubeflow pipeline parameters in JSON key value format, without the square brackets {"name":"n1", "value":"v1"}, {"name":"n2", "value":"v2"}.
• description: This input is optional. Provides a description for your run.
• waitForRunToFinish: If true, will wait for new run to complete. It will update the status every 15 seconds. Either input 'true' or 'false'.
• experiment: Input either 'createNewExperiment' to create a new experiment or 'useExistingExperiment' to use an existing experiment.
• experimentName: The name of the experiment you would like your run to use. If the experiment field is set to create a new experiment, this name will need to be unique.
• experimentDescription: The optional description of a new experiment. Does not apply to existing experiments.

• kf_pipeline_id: Id of the pipeline being used to create run.
• kf_pipeline_version_id: Id of the pipeline version being used to create run.
• kf_experiment_id: Id of the experiment being used.
• kf_run_id: Id of the new run.
• kf_run_status: The end status of the run. Only available if you choose to wait for the run to complete.