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?

Real Exam

Manually export/import notebooks between workspaces, conducting performance testing in the production environment.

3.5%

Implement Azure DevOps Pipelines to run automated tests defined in a separate test suite, deploying notebooks to production upon successful test completion.

92.9%

Use Databricks Repos to manually copy notebooks between workspaces, relying on peer reviews for testing.

1.2%

Configure Git integration with Databricks workspace, pushing changes directly to production branches without automated tests.

2.4%

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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?