Databricks releases, every cloud
- Base environments are now supported on classic compute (Beta)
Manages Python dependencies using Databricks-provided or custom environments.
- Default Python package repositories are GA for Lakeflow pipelines and classic compute
Supports private or authenticated registries as workspace defaults. Applies to UI and API created classic compute.
- Manage project environments with %uv commands
Requires environment version 5 or above. Supports serverless notebooks.
- Target an Azure capacity reservation group for classic compute
Requires VNet injection, guarantees compute capacity for constrained VM types.
- Serverless compute is now available in the Azure UK West region
Supports notebooks, jobs, pipelines, and SQL warehouses, with private connectivity.
- Schedule deferred policy enforcement for all-purpose compute
Applies on next restart or immediately, and admins can cancel scheduled enforcements.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Run the change, do not just read it. Hands-on labs in your own Databricks workspace, graded when you submit. Browse labs
- Databricks Container Services for standard compute is now available (Beta)
Requires Databricks Runtime 18.3 or later, allows custom Docker images in shared compute.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Change to use_case field in VPC endpoint API responses Coming soon
Changes from WORKSPACE_ACCESS to GENERAL_ACCESS, see API docs for details.
- Configure compute to use AWS Capacity Blocks
Replaces on-demand instances, requires AWS account setup.
Headlines, dates and product areas are Databricks' own, from the release notes published for each cloud, and every item links to the note it came from. The one-line summaries are ours. Not a Databricks product and not affiliated with Databricks, Inc.