Google Professional Machine Learning Engineer
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You are tasked with automating the execution of unit tests for a Kubeflow Pipeline that requires custom libraries, triggered by each new push to a development branch in Cloud Source Repositories. The solution must be cost-effective, scalable, and provide immediate feedback to developers. Which of the following approaches BEST meets these requirements? (Choose two options if option E is available)
A
Develop a custom script that triggers unit tests on Cloud Run immediately after a push to the development branch, ensuring tests are run in an isolated environment.
B
Utilize Cloud Build to automatically trigger and execute the unit tests upon each push to the development branch, leveraging its integration with Cloud Source Repositories for seamless operation.
C
Implement a Cloud Logging sink to capture repository interactions, route these logs to a Pub/Sub topic, and use a Cloud Function triggered by Pub/Sub messages to execute the unit tests, adding complexity for logging and monitoring.
D
Configure a Cloud Scheduler job that periodically checks the development branch for new pushes and executes the unit tests on Cloud Run, introducing delays in feedback.
E
Combine Cloud Build for immediate test execution upon push and Cloud Functions for additional logging and monitoring capabilities, ensuring both speed and observability.