Answer-first summary for fast verification
Answer: Set up a CI/CD pipeline that builds and tests your source code and then deploys built artifacts into a pre-production environment. After a successful pipeline run in the pre-production environment, deploy the pipeline to production.
The best practice for deploying new versions of pipelines with minimal risk of breaking production is to use a CI/CD pipeline that builds and tests your source code and then deploys the built artifacts into a pre-production environment. This allows comprehensive testing of the pipeline functionality and performance using simulated real-world data. Once the pipeline runs successfully in the pre-production environment, it can be safely deployed to production. This approach ensures that the entire pipeline workflow, including training, model pushing, and endpoint deployment, performs correctly before impacting production traffic. Rebuilding code after a successful pre-production run, as mentioned in option D, introduces unnecessary steps and potential new errors, while unit tests alone in options A and B don't provide sufficient coverage to ensure reliability.
Author: LeetQuiz Editorial Team
Ultimate access to all questions.
No comments yet.
You have successfully deployed a machine learning pipeline in Vertex AI Pipelines which trains and pushes a model to a Vertex AI endpoint for serving real-time traffic. As part of continuous improvement, you need to keep experimenting and iterating on your pipeline to enhance model performance. Additionally, you plan to utilize Cloud Build to set up a CI/CD (Continuous Integration/Continuous Deployment) process. Your main objectives are to efficiently deploy new pipeline versions into production while minimizing the risk of breaking existing functionalities in the production environment. What strategy should you adopt?
A
Set up a CI/CD pipeline that builds and tests your source code. If the tests are successful, use the Google Cloud Console to upload the built container to Artifact Registry and upload the compiled pipeline to Vertex AI Pipelines.
B
Set up a CI/CD pipeline that builds your source code and then deploys built artifacts into a pre-production environment. Run unit tests in the pre-production environment. If the tests are successful, deploy the pipeline to production.
C
Set up a CI/CD pipeline that builds and tests your source code and then deploys built artifacts into a pre-production environment. After a successful pipeline run in the pre-production environment, deploy the pipeline to production.
D
Set up a CI/CD pipeline that builds and tests your source code and then deploys built artifacts into a pre-production environment. After a successful pipeline run in the pre-production environment, rebuild the source code and deploy the artifacts to production.