The question describes a scenario involving a Vertex AI ML pipeline with preprocessing and training steps, each running on a separate custom Docker image. The CI/CD system uses GitHub and GitHub Actions for unit and integration tests. The goal is to automate the model retraining workflow, triggerable manually and upon code merges to the main branch, while minimizing steps and maximizing flexibility.
Four options (A, B, C, D) are provided, each detailing a different approach to configuring the CI/CD workflow, involving combinations of GitHub Actions, Cloud Build, Artifact Registry, and Vertex AI Pipelines.
Option D is identified as the correct answer: triggering GitHub Actions for tests, then using a Cloud Build workflow to build Docker images, push them to Artifact Registry, and finally, launch the pipeline in Vertex AI Pipelines.
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?
If you often open multiple tabs and struggle to keep track of them, Tabs Reminder is the solution you need. Tabs Reminder lets you set reminders for tabs so you can close them and get notified about them later. Never lose track of important tabs again with Tabs Reminder!
Try our Chrome extension today!
Share this article with your
friends and colleagues.
Earn points from views and
referrals who sign up.
Learn more