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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?
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?
Explanation:
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.