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.
- 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.
- 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) - Run the change, do not just read it. Hands-on labs in your own Databricks workspace, graded when you submit. Browse labs
- 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) - 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) - 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) - Serverless compute is enabled by default
Eligible Google Cloud workspaces are affected, account admins no longer need to manually enable it.
- Flexible node types are now generally available
Falls back to alternative instance types when specified type is unavailable, improving launch reliability.
- OpenAI GPT 5 models are now generally available in Mosaic AI Model Serving
Includes GPT-5 mini and nano models.
- Improved autoscaling behavior for Mosaic AI Model Serving
Ignores brief traffic surges, scaling on sustained load increases. Reduces unnecessary concurrency scaling.
- Mosaic AI Model Serving now supports OpenAI GPT 5 models (preview)
Supports GPT-5, GPT-5 mini, and GPT-5 nano models for batch inference with AI Functions.
- Anthropic Claude Opus 4.1 now available as a Databricks-hosted foundation model
Accessible via Foundation Model APIs on a pay-per-token basis.
- Route-optimized endpoints now require route-optimized URL path for querying
Requires route-optimized URL path for querying, standard workspace URL path not supported for new endpoints.
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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.