Databricks releases, every cloud
- Git Folder Serverless is in Beta
Shares serverless compute and pyproject.toml environment across notebooks and files.
- Genie Code for AI Runtime (Public Preview)
Generates distributed training code and resolves environment issues. Requires AI Runtime.
- 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.
- Protobuf tensor input for custom model serving endpoints (Public Preview)
Replaces JSON with serialized KServe v2 ModelInferRequest. Requires endpoints deployed after July 9, 2026.
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) - AI Runtime is now in Public Preview
Adds GPU support to serverless compute for deep learning workloads.
- Run the change, do not just read it. Hands-on labs in your own Databricks workspace, graded when you submit. Browse labs
- List MCP servers in Azure Databricks Marketplace (Public Preview)
Allows distribution of AI tools and connection to external data sources, requires provider listing.
- List MCP servers in Databricks Marketplace (Public Preview)
Lets users install MCP servers to connect AI agents to external data sources.
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.