Prakash, you should look at MLFlow, software developed by Databricks and native to our platform.

I suggest you start by looking here for more information: https://docs.databricks.com/aws/en/machine-learning/mlops/mlops-workflow

Cheers, Louis.

Hi Prakash,

Great question! Databricks provides built-in tools to help with model versioning and rollback, particularly through the Model Registry and Databricks CLI.

To manage model versions programmatically, you can use the Databricks CLI, which includes a set of commands specifically for model version operations. These commands let you:

Register new model versions

Transition model stages (e.g., from "Staging" to "Production")

Delete or restore versions

Retrieve version details

This gives you precise control over model lifecycle management and makes it easier to roll back to a previous version if needed.

You can find the full list of CLI commands for working with model versions here:
https://docs.databricks.com/aws/en/dev-tools/cli/reference/model-versions-commands

Additionally, within the Databricks UI, the MLflow Model Registry lets you visually manage versions, add comments, track stage transitions, and more.

Let me know if you'd like an example workflow or script using the CLI!

Best regards,
Wiliam Rosa