What is the function of Databricks repos concerning version control?

Databricks repos play a significant role in facilitating version control by allowing integration with external Git providers. This functionality enables data scientists and engineers to manage their code, roadmaps, and project history efficiently. By connecting to platforms like GitHub or Bitbucket, users can leverage familiar version control workflows, such as branching, merging, and committing changes, directly within the Databricks environment.

This integration supports collaborative development, as multiple team members can work on the same codebase, track changes over time, and maintain a clear history of modifications, which is crucial for managing ML projects effectively. Version control through external Git providers enhances the ability to revert to previous code versions, resolve conflicts, and ensure that projects are consistent, reproducible, and maintainable.

The other options describe functionalities that are not aligned with the core purpose of Databricks repos in the context of version control. For instance, keeping logs of Spark jobs or providing backup copies for driver nodes is unrelated to the management of source code. Storing notebooks in a non-versioned format contradicts the idea of version control, which relies on maintaining a versioned history of changes.