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Answer: Trigger GitHub Actions to run the tests, launch a Cloud Build workflow to build custom Docker images, push the images to Artifact Registry, and launch the pipeline in Vertex AI Pipelines.
The correct answer is D. This option leverages GitHub Actions for running tests and to initiate the workflow upon code merges. Cloud Build is specifically designed for building container images in Google Cloud and offers better resource management and scalability compared to Cloud Run, which is primarily designed for running stateless containers. By using Cloud Build to handle the building and pushing of Docker images, you can ensure a more robust and scalable solution for container image building. This configuration allows for independent scaling of test execution in GitHub Actions and image building in Cloud Build, providing the flexibility you need while minimizing the steps required to build the workflow.
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You are tasked with maintaining a machine learning workflow for your organization, which involves a Vertex AI ML pipeline. This pipeline includes preprocessing and training steps, each running on separate custom Docker images. Your organization uses GitHub for version control and GitHub Actions as the CI/CD tool for running unit and integration tests. There is a need to automate the model retraining process so that it can be triggered manually or automatically when a new version of the code is merged into the main branch. The goal is to configure the CI/CD workflow in a way that minimizes the steps required and offers maximum flexibility. How should you set up this CI/CD workflow?
A
Trigger a Cloud Build workflow to run tests, build custom Docker images, push the images to Artifact Registry, and launch the pipeline in Vertex AI Pipelines.
B
Trigger GitHub Actions to run the tests, launch a job on Cloud Run to build custom Docker images, push the images to Artifact Registry, and launch the pipeline in Vertex AI Pipelines.
C
Trigger GitHub Actions to run the tests, build custom Docker images, push the images to Artifact Registry, and launch the pipeline in Vertex AI Pipelines.
D
Trigger GitHub Actions to run the tests, launch a Cloud Build workflow to build custom Docker images, push the images to Artifact Registry, and launch the pipeline in Vertex AI Pipelines.
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