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Explanation:

Correct Answer: D

This option stands out as the optimal strategy for implementing a CI/CD pipeline for Databricks notebooks using Azure DevOps. Here's why:

Databricks Repos: This feature provides version control for notebooks within Databricks, making it straightforward to track changes and revert them if necessary.
Automated Testing: Automating tests upon each commit ensures that all notebook modifications are validated before reaching production, minimizing risks.
Azure Pipelines for Deployment: Automating the deployment process through Azure Pipelines reduces human error and accelerates the deployment cycle.
Artifact Storage for Rollbacks: Storing deployment artifacts allows for quick rollback to previous versions in case of deployment failures, ensuring system stability and minimal downtime.

In summary, combining Databricks Repos with Azure DevOps for automated testing and deployment, plus artifact storage for rollbacks, creates a comprehensive and efficient CI/CD pipeline for Databricks notebooks.

Explanation:

Correct Answer: D

This option stands out as the optimal strategy for implementing a CI/CD pipeline for Databricks notebooks using Azure DevOps. Here's why:

Databricks Repos: This feature provides version control for notebooks within Databricks, making it straightforward to track changes and revert them if necessary.
Automated Testing: Automating tests upon each commit ensures that all notebook modifications are validated before reaching production, minimizing risks.
Azure Pipelines for Deployment: Automating the deployment process through Azure Pipelines reduces human error and accelerates the deployment cycle.
Artifact Storage for Rollbacks: Storing deployment artifacts allows for quick rollback to previous versions in case of deployment failures, ensuring system stability and minimal downtime.

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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?

Real Exam

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.

11.0%

Integrate Git with Databricks, employing Azure DevOps for version control and manual initiation of deployments and rollbacks.

6.8%

Set up Azure DevOps to move notebooks to a staging area first, manually verify outcomes, and then advance to production.

5.1%

Use Databricks Repos alongside Azure DevOps, automate testing upon each commit, and deploy via Azure Pipelines, with stored artifacts enabling rollback.

77.1%