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PROFESSIONAL-MACHINE-LEARNING-ENGINEER · Question #191

You recently deployed a pipeline in Vertex AI Pipelines that trains and pushes a model to a Vertex AI endpoint to serve real-time traffic. You need to continue experimenting and iterating on your…

The correct answer is C. Set up a CI/CD pipeline that builds and tests your source code and then deploys built artifacts into. To ensure reliable and quick deployment of new Vertex AI Pipelines using Cloud Build, implement a CI/CD pipeline that includes building, testing, and then deploying artifacts to production, ensuring quality before release.

Submitted by suresh_in· Apr 18, 2026ML pipeline operationalization

Question

You recently deployed a pipeline in Vertex AI Pipelines that trains and pushes a model to a Vertex AI endpoint to serve real-time traffic. You need to continue experimenting and iterating on your pipeline to improve model performance. You plan to use Cloud Build for CI/CD You want to quickly and easily deploy new pipelines into production, and you want to minimize the chance that the new pipeline implementations will break in production. What should you do?

Options

  • ASet up a CI/CD pipeline that builds and tests your source code. If the tests are successful, use the
  • BSet up a CI/CD pipeline that builds your source code and then deploys built artifacts into a pre-
  • CSet up a CI/CD pipeline that builds and tests your source code and then deploys built artifacts into
  • DSet up a CI/CD pipeline that builds and tests your source code and then deploys built artifacts into

How the community answered

(35 responses)
  • A
    9% (3)
  • B
    14% (5)
  • C
    74% (26)
  • D
    3% (1)

Why each option

To ensure reliable and quick deployment of new Vertex AI Pipelines using Cloud Build, implement a CI/CD pipeline that includes building, testing, and then deploying artifacts to production, ensuring quality before release.

ASet up a CI/CD pipeline that builds and tests your source code. If the tests are successful, use the

This option is incomplete as it doesn't specify the deployment of the *pipeline* artifacts after building and testing.

BSet up a CI/CD pipeline that builds your source code and then deploys built artifacts into a pre-

Deploying to a pre-production environment without explicit testing in the CI/CD flow does not fully minimize the chance of new pipeline implementations breaking in production.

CSet up a CI/CD pipeline that builds and tests your source code and then deploys built artifacts intoCorrect

A robust CI/CD pipeline for ML with Vertex AI Pipelines should include building the pipeline definition, comprehensive testing (e.g., unit/integration tests), and then deploying the validated pipeline artifacts to production to minimize errors and prevent broken pipelines.

DSet up a CI/CD pipeline that builds and tests your source code and then deploys built artifacts into

This option lacks the emphasis on comprehensive testing *before* deploying to production, which is key to minimizing breaks.

Concept tested: CI/CD for Vertex AI Pipelines with testing

Source: https://cloud.google.com/vertex-ai/docs/pipelines/build-pipeline

Topics

#CI/CD#MLOps#Vertex AI Pipelines#Staged Deployment

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