CD/CD for the ml-pipeline that builds all the pipeline modules and pushes them to the private PyPI registry. From where Airflow will install the latest versions and use them in the next run. workflow (iusztinpaul/energy-forecasting)

The CD/CD for the ml-pipeline that builds all the pipeline modules and pushes them to the private PyPI registry. From where Airflow will install the latest versions and use them in the next run. workflow from iusztinpaul/energy-forecasting, explained and optimized by Latchkey.

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Source: iusztinpaul/energy-forecasting.github/workflows/ci_cd_ml_pipeline.ymlLicense MITView source

What it does

This is the CD/CD for the ml-pipeline that builds all the pipeline modules and pushes them to the private PyPI registry. From where Airflow will install the latest versions and use them in the next run. workflow from the iusztinpaul/energy-forecasting repository, a real project running GitHub Actions. It is shown here with attribution under its MIT license.

Below, Latchkey shows a faster, safer version produced by its optimization engine.

The workflow

workflow (.yml)

name: CD/CD for the ml-pipeline that builds all the pipeline modules and pushes them to the private PyPI registry. From where Airflow will install the latest versions and use them in the next run.

on:
  push:
    paths-ignore:
      - 'app-api/'
      - 'app-frontend/'
      - '**/*.yml'
      - '**/*.md'
    branches: [ "main" ]
    
env:
  CLOUDSDK_CORE_PROJECT: '${{ vars.CLOUDSDK_CORE_PROJECT }}'
  USER: '${{ vars.USER }}'
  INSTANCE_NAME: '${{ vars.ML_PIPELINE_INSTANCE_NAME }}'
  ZONE: '${{ vars.ZONE }}'

jobs:
  ci_cd:
    runs-on: ubuntu-latest
    steps:
      - uses: 'actions/checkout@v3'

      - id: 'auth'
        uses: 'google-github-actions/auth@v0'
        with:
          credentials_json: '${{ secrets.GCP_CREDENTIALS }}'
      - id: 'compute-ssh'
        uses: 'google-github-actions/ssh-compute@v0'
        with:
          project_id: '${{ env.CLOUDSDK_CORE_PROJECT }}'
          user: '${{ env.USER }}'
          instance_name: '${{ env.INSTANCE_NAME }}'
          zone: '${{ env.ZONE }}'
          ssh_private_key: '${{ secrets.GCP_SSH_PRIVATE_KEY }}'
          command: >
            cd ~/energy-forecasting && 
            git pull && 
            sh deploy/ml-pipeline.sh

The same workflow, on Latchkey

Removes redundant runs and caps runaway jobs. Added and changed lines are highlighted.

name: CD/CD for the ml-pipeline that builds all the pipeline modules and pushes them to the private PyPI registry. From where Airflow will install the latest versions and use them in the next run.
 
on:
  push:
    paths-ignore:
      - 'app-api/'
      - 'app-frontend/'
      - '**/*.yml'
      - '**/*.md'
    branches: [ "main" ]
    
env:
  CLOUDSDK_CORE_PROJECT: '${{ vars.CLOUDSDK_CORE_PROJECT }}'
  USER: '${{ vars.USER }}'
  INSTANCE_NAME: '${{ vars.ML_PIPELINE_INSTANCE_NAME }}'
  ZONE: '${{ vars.ZONE }}'
 
concurrency:
  group: ${{ github.workflow }}-${{ github.ref }}
  cancel-in-progress: true
 
jobs:
  ci_cd:
    timeout-minutes: 30
    runs-on: latchkey-small
    steps:
      - uses: 'actions/checkout@v3'
 
      - id: 'auth'
        uses: 'google-github-actions/auth@v0'
        with:
          credentials_json: '${{ secrets.GCP_CREDENTIALS }}'
      - id: 'compute-ssh'
        uses: 'google-github-actions/ssh-compute@v0'
        with:
          project_id: '${{ env.CLOUDSDK_CORE_PROJECT }}'
          user: '${{ env.USER }}'
          instance_name: '${{ env.INSTANCE_NAME }}'
          zone: '${{ env.ZONE }}'
          ssh_private_key: '${{ secrets.GCP_SSH_PRIVATE_KEY }}'
          command: >
            cd ~/energy-forecasting && 
            git pull && 
            sh deploy/ml-pipeline.sh

What changed

Run on Latchkey managed runners with one line (runs-on), which apply the fixes below automatically and self-heal transient failures. This example uses latchkey-small; pick the runner size that fits the job.
Cancel superseded runs when a branch or PR gets a newer push.
Add a job timeout so a hung step cannot burn hours of runner time.

This workflow runs 1 job per trigger. On Latchkey the same minutes cost up to 58% less than GitHub-hosted, with zero queue time.