Here are some things to consider:

1. Available Methods:
   Currently, Databricks provides manual options to purge notebook revision history:

   • Deleting revision history for individual notebooks.
   • Using the "Permanently purge all revision history" option accessible via Settings > Advanced, allowing bulk purging for all notebooks.
2. Testing Internal API Endpoints:
   The undocumented endpoints you mentioned:

   • {workspace_url}/dataretention/purgehistorybefore/{purge_before_ms}
   • {workspace_url}/notebook/{notebook_id}/history/clearall While you have tested these endpoints and received HTTP 200 responses, the issue seems to be that the purging is not actually executed. This behavior could be due to the experimental or deprecated status of these endpoints, making them unreliable.
3. Alternative Automation Strategies:
   Based on context from related tooling and approaches:

   • To script bulk revision purging, programmatic access through Databricks APIs (where available) remains the best option. However, for undocumented endpoints or limited API support, you might consider using workarounds such as invoking browser automation tools (like Selenium) to mimic the manual process of purging notebooks in the UI.
   • Ensure that Databricks' internal API logs or audit logs are checked for specific operation timings or errors related to purge attempts to diagnose why purging did not succeed.
4. Documentation and Guidance:
   The official Databricks documentation provides steps for manual purging but does not yet describe any backend API methods for automation. For updates on this functionality, regularly refer to the relevant Databricks documentation Purge workspace storage.