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Answer: Implement Azure DevOps Pipelines to run automated tests defined in a separate test suite, deploying notebooks to production upon successful test completion.
Implementing Azure DevOps Pipelines allows for automation of the testing process. By defining automated tests in a separate test suite, you can ensure that the notebooks are tested for functionality and performance before deployment to production. This ensures consistency and reliability in the deployment process. Manual methods or bypassing testing phases are risky and can lead to deploying faulty notebooks to production, causing potential issues and downtime. Therefore, automating the testing and deployment process is the best practice for ensuring efficiency, reliability, and minimizing risks.
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When developing a CI/CD pipeline for deploying Databricks notebooks from development to production environments, which best practice ensures the notebooks are automatically tested for functionality and performance before deployment?
A
Manually export/import notebooks between workspaces, conducting performance testing in the production environment.
B
Implement Azure DevOps Pipelines to run automated tests defined in a separate test suite, deploying notebooks to production upon successful test completion.
C
Use Databricks Repos to manually copy notebooks between workspaces, relying on peer reviews for testing.
D
Configure Git integration with Databricks workspace, pushing changes directly to production branches without automated tests.