Databricks releases, every cloud
- Base environments are now supported on classic compute (Beta)
Manages Python dependencies using Databricks-provided or custom environments.
- Git Folder Serverless is in Beta
Shares serverless compute and pyproject.toml environment across notebooks and files.
- 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.
- Organize your work with spaces
Preserves open tabs for specific folders or projects.
- Serverless compute access control is now generally available
Governs access to notebooks, jobs, and pipelines through Default Interactive and Automated Compute objects. Existing workloads run unchanged.
- Run the change, do not just read it. Hands-on labs in your own Databricks workspace, graded when you submit. Browse labs
- Web terminal on serverless GPU compute (AI Runtime) is in Public Preview
Runs shell commands, monitors GPU usage, and manages files on serverless GPU compute. Requires environment version 5 or above.
- Dedicated group clusters will soon be available by default for workspaces with the compliance security profile enabled Coming soon
Enables shared compute for groups with compliance security profile, supporting Databricks Runtime for ML and RDD APIs.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - 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) - Reorganized Spark Declarative Pipelines on Lakeflow documentation
Conceptual topics are now under Concepts.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Instance events and instance pools system tables are now available (Public Preview)
Track instance state transitions and instance pool configurations via system.compute.instance_events and system.compute.instance_pools tables.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - 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) - Compute log delivery to volumes is now GA
Delivers Spark driver, worker, and event logs to Unity Catalog volumes, recommended for log storage.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Upcoming breaking change: default behavior when deleting a Unity Catalog pipeline Coming soon
Deletes now retain associated tables by default, set cascade=true to remove them.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Databricks Documentation site table of contents tabs
Replaces static sidebar with tabbed navigation, includes 6 context tabs.
- Change to use_case field in VPC endpoint API responses Coming soon
Changes from WORKSPACE_ACCESS to GENERAL_ACCESS, see API docs for details.
- View and restore your recent workspace tab sessions
Restores up to 10 recent sessions.
- Serverless workspaces are now generally available
Come pre-configured with serverless compute and default storage.
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- Flexible node types are now generally available
Falls back to alternative instance types when specified type is unavailable, improving launch reliability.
- Configure compute to use AWS Capacity Blocks
Replaces on-demand instances, requires AWS account setup.
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