Kubeflow Pipelines Deploy Action

GitHub Actions for deploying Kubeflow Pipelines on Google Cloud Platform (GCP).

Usage

Use Case

This action is intended for developers who manage CI/CD with GitHub Actions. If you handle it with GCP service, see also: CI/CD workflow use case with GCP service

Parameters

key	value	default	required	description
kubeflow_url	url string		True	The endpoint where your Kubeflow UI is running.
pipeline_file_path	path/to/pipeline.py		True	The full path to pipeline.py file. This must be relative to the root of the GitHub repository where the Action is triggered.
pipeline_function_name	function name string		True	The name of the pipeline, this name will be the name of the pipeline in the Kubeflow UI.
pipeline_parameters_path	path/to/parameters.yaml		True	The full path to parameters.yml which contains pipeline parameters.
pipeline_namespace	namespace string		False	The namespace in which the pipeline should run.
experiment_name	any string	'Default'	False	The name of the experiment name within which the kubeflow experiment should run.
run_pipeline	True or False	False	False	The flag of running the pipeline. If true, your pipeline will run after uploading.
recurring_cron_expression	True or False	False	False	CRON string for scheduling recurring pipelines
client_id	any string		False	The IAP client id, which was specified when the kubeflow deployment where setup using IAP.

The pipeline also must have the GitHub SHA as a parameter, as shown below:

from kfp import dsl
def path_csv_pipeline(github_sha: str): # Required parameter for versioning artifacts
    # Define component
    ...

    # pipeline
    @dsl.pipeline
    def pipeline(n_cols: int = 5, n_rows: int = 3):
        # Define your pipeline
        ...
        # End of pipeline
    
    return pipeline

Example Usage and Workflow

The following example code is from here (example/example_pipeline.py).

Define Pipeline

Your pipeline must be defined inside any function. The following example uses @func_to_container_op to declare a component, but it can be defined in any format (self built component.yaml, official component file from Kubeflow, etc.).

def path_csv_pipeline(github_sha: str): # Required parameter for versioning artifacts
    """Making arbitrary Dataframe with specified columns and rows"""

    @func_to_container_op
    def make_csv(n_cols: int, n_rows: int, output_csv_path: OutputPath("CSV")):
        ...

    @func_to_container_op
    def read_csv(input_csv_path: InputPath("CSV")):
        ...

    # pipeline
    @dsl.pipeline(
        name="Sample pipeline", description="Make a csv file and read it."
    )
    def pipeline(n_cols: int = 5, n_rows: int = 3):
        make_csv_task = make_csv(n_cols, n_rows)
        read_csv(input_csv=make_csv_task.outputs["output_csv"])

    return pipeline

Define Workflow for Run only once

name: Compile, Deploy and Run on Kubeflow
on:
  pull_request:
    branches:
      - 'master'
    types: [opened, synchronize, closed]

jobs:
  build:
    runs-on: ubuntu-latest

    steps:
    - name: Checkout files in repo
      uses: actions/checkout@v2

    - name: Submit a pipeline
      uses: f6wbl6/kubeflow-pipelines-deploy-action@master
      env:
        SA_EMAIL: ${{ secrets.SA_EMAIL }} # required: Service Account E-mail
        GOOGLE_APPLICATION_CREDENTIALS_JSON: ${{ secrets.GCP_CREDENTIALS }} # required: JSON contents of service account credentials
        GITHUB_SHA: ${{ github.sha }} # required
      with:
        KUBEFLOW_URL: ${{ secrets.KUBEFLOW_URL }} # required
        PIPELINE_FILE_PATH: "example/example_pipeline.py" # required
        PIPELINE_FUNCTION_NAME: "path_csv_pipeline" # required
        PIPELINE_PARAMETERS_PATH: "example/parameters.yaml" # required
        CLIENT_ID: ${{ secrets.CLIENT_ID }}
        RUN_PIPELINE: True # Run pipeline if set as "True"

Define Workflow for Recurring Run (Periodical Execution)

A cron string should be configured. See here for an example configuration: Cron Expressions

...

    - name: Submit a pipeline
      uses: f6wbl6/kubeflow-pipelines-deploy-action@master
      env:
        SA_EMAIL: ${{ secrets.SA_EMAIL }} # required
        GOOGLE_APPLICATION_CREDENTIALS_JSON: ${{ secrets.GCP_CREDENTIALS }} # required
        GITHUB_SHA: ${{ github.sha }} # required
      with:
        KUBEFLOW_URL: ${{ secrets.KUBEFLOW_URL }} # required
        PIPELINE_FILE_PATH: "example/example_pipeline.py" # required
        PIPELINE_FUNCTION_NAME: "path_csv_pipeline" # required
        PIPELINE_PARAMETERS_PATH: "example/parameters.yaml" # required
        CLIENT_ID: ${{ secrets.CLIENT_ID }}
        RUN_PIPELINE: True # Run pipeline if set as "True"
        RECURRING_CRON_EXPRESSION: "0 0 8 * * ?" # Run daily at 8:00 on GKE time zone

Acknowledgment

This action is forked from NikeNano's kubeflow-github-action. Thanks!