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PROFESSIONAL-MACHINE-LEARNING-ENGINEER · Question #177

You developed a Vertex AI ML pipeline that consists of preprocessing and training steps and each set of steps runs on a separate custom Docker image. Your organization uses GitHub and GitHub Actions…

The correct answer is C. Trigger GitHub Actions to run the tests, build custom Docker images, push the images to Artifact. To automate a Vertex AI ML retraining workflow with GitHub Actions as CI/CD, you should configure GitHub Actions to run tests, build custom Docker images, and push them directly to Artifact Registry.

Submitted by neha2k· Apr 18, 2026ML pipeline operationalization

Question

You developed a Vertex AI ML pipeline that consists of preprocessing and training steps and each set of steps runs on a separate custom Docker image. Your organization uses GitHub and GitHub Actions as CI/CD to run unit and integration tests. You need to automate the model retraining workflow so that it can be initiated both manually and when a new version of the code is merged in the main branch. You want to minimize the steps required to build the workflow while also allowing for maximum flexibility. How should you configure the CI/CD workflow?

Options

  • ATrigger a Cloud Build workflow to run tests, build custom Docker images, push the images to
  • BTrigger GitHub Actions to run the tests, launch a job on Cloud Run to build custom Docker
  • CTrigger GitHub Actions to run the tests, build custom Docker images, push the images to Artifact
  • DTrigger GitHub Actions to run the tests, launch a Cloud Build workflow to build custom Docker

How the community answered

(48 responses)
  • A
    4% (2)
  • B
    10% (5)
  • C
    79% (38)
  • D
    6% (3)

Why each option

To automate a Vertex AI ML retraining workflow with GitHub Actions as CI/CD, you should configure GitHub Actions to run tests, build custom Docker images, and push them directly to Artifact Registry.

ATrigger a Cloud Build workflow to run tests, build custom Docker images, push the images to

Triggering a Cloud Build workflow from GitHub Actions for all steps introduces an unnecessary orchestration layer, as GitHub Actions is capable of managing these tasks directly, making it less minimal.

BTrigger GitHub Actions to run the tests, launch a job on Cloud Run to build custom Docker

Cloud Run is a serverless platform for running containers, not primarily designed for building Docker images within a CI/CD pipeline, making it an unsuitable and inefficient choice for this specific task.

CTrigger GitHub Actions to run the tests, build custom Docker images, push the images to ArtifactCorrect

Since GitHub Actions is already the chosen CI/CD platform for running tests, extending it to directly build custom Docker images and push them to Artifact Registry within the same workflow minimizes complexity and external dependencies. This approach aligns with maximum flexibility by keeping all steps within a single, integrated CI/CD system.

DTrigger GitHub Actions to run the tests, launch a Cloud Build workflow to build custom Docker

While triggering Cloud Build for image building from GitHub Actions is a valid pattern, building images directly within GitHub Actions is often simpler and more flexible, especially when aiming to minimize steps, by avoiding an external build service.

Concept tested: CI/CD for ML pipelines on GCP; GitHub Actions

Source: https://docs.github.com/en/actions/automating-builds-and-tests/building-and-testing-docker

Topics

#CI/CD#ML Pipelines#Docker#GitHub Actions

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