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Answer: Use the Databricks CLI in Azure DevOps pipelines to automate notebook version control, testing, and deployment across workspaces.
Option B is the most suitable approach for implementing CI/CD with Databricks notebooks. Here‘s why: 1. **Databricks CLI**: The Databricks Command Line Interface (CLI) allows programmatic interaction with Databricks workspaces, enabling automation of version control, testing, and deployment. 2. **Azure DevOps pipelines**: These provide tools for building, testing, and deploying applications, making them ideal for integrating with the Databricks CLI to create a seamless CI/CD pipeline. 3. **Version control**: Managing versions becomes straightforward, allowing for tracking changes and collaboration. 4. **Testing**: Automated tests ensure notebooks meet quality standards before deployment, catching issues early. 5. **Deployment across workspaces**: The CLI facilitates easy deployment from development to production environments, ensuring a smooth transition. This approach combines automation, version control, testing, and deployment capabilities essential for a successful CI/CD pipeline.
Author: LeetQuiz Editorial Team
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How can you set up a CI/CD pipeline for deploying Databricks notebooks into production with automated testing and deployment?
A
Store notebooks in Azure Blob Storage, manually copying them into Databricks workspaces as needed.
B
Use the Databricks CLI in Azure DevOps pipelines to automate notebook version control, testing, and deployment across workspaces.
C
Implement a script to email notebooks to the data engineering team for manual review and deployment.
D
Manually export notebooks from a development workspace and import them into production, executing tests within the production environment.