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You're setting up a CI/CD pipeline for Databricks notebooks with Azure DevOps. Which approach guarantees automatic testing and deployment to production upon code check-in, including the ability to rollback if something goes wrong?
A
Utilize Azure DevOps Pipelines to initiate Databricks Jobs for testing notebooks upon check-in, proceed to deploy to production if tests are successful, with manual steps required for rollback.
B
Integrate Git with Databricks, employing Azure DevOps for version control and manual initiation of deployments and rollbacks.
C
Set up Azure DevOps to move notebooks to a staging area first, manually verify outcomes, and then advance to production.
D
Use Databricks Repos alongside Azure DevOps, automate testing upon each commit, and deploy via Azure Pipelines, with stored artifacts enabling rollback.
