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7 releases of 1321

Last updated 10 hours ago

Release					Date
Genie Code for AI Runtime (Public Preview) Generates distributed training code and resolves environment issues. Requires AI Runtime. #Genie Code #Machine Learning	On AWS, read it on their docs	On Azure, read it on their docs	Not on GCP	Unknown on SAP	Aug 27, 2026
Custom trace views in the MLflow trace explorer are in Beta Genie generates views based on plain language descriptions, surfacing relevant trace fields and metrics. #Gen AI #MLflow	On AWS, read it on their docs	On Azure, read it on their docs	On GCP, read it on their docs	Unknown on SAP	Aug 12, 2026
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. #Compute #Machine Learning	On AWS, read it on their docs	On Azure, read it on their docs	Not on GCP	Unknown on SAP	Jul 31, 2026
Protobuf tensor input for custom model serving endpoints (Public Preview) Replaces JSON with serialized KServe v2 ModelInferRequest. Requires endpoints deployed after July 9, 2026. #Machine Learning #Model Serving	On AWS, read it on their docs	On Azure, read it on their docs	On GCP, read it on their docs	Not on SAP	Jul 9, 2026
MLflow trace storage in Unity Catalog is now in Public Preview Stores OpenTelemetry traces, governed by Unity Catalog permissions, queryable from Databricks SQL or MLflow Python SDK. #MLflow #Unity Catalog	On AWS, read it on their docs	On Azure, read it on their docs	On GCP, read it on their docs	Not on SAP	Apr 30, 2026
AI Runtime is now in Public Preview Adds GPU support to serverless compute for deep learning workloads. #Machine Learning	On AWS, read it on their docs	On Azure, read it on their docs	Not on GCP	Not on SAP	Mar 19, 2026
Run the change, do not just read it. Hands-on labs in your own Databricks workspace, graded when you submit. Browse labs
Admins can now manage a workspace's serverless base environments (Public Preview) Defines custom environment specs for serverless notebooks, allows setting a default for new notebooks. #Notebooks #Serverless	On AWS, read it on their docs	On Azure, read it on their docs	On GCP, read it on their docs	Unknown on SAP	Aug 28, 2025

Genie Code for AI Runtime (Public Preview)
Generates distributed training code and resolves environment issues. Requires AI Runtime.

#Genie Code #Machine Learning

AWS, read it on their docs Azure, read it on their docsGCP(not on this cloud)SAP(unknown) Aug 27, 2026
Custom trace views in the MLflow trace explorer are in Beta
Genie generates views based on plain language descriptions, surfacing relevant trace fields and metrics.

#Gen AI #MLflow

AWS, read it on their docs Azure, read it on their docs GCP, read it on their docsSAP(unknown) Aug 12, 2026
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.

#Compute #Machine Learning

AWS, read it on their docs Azure, read it on their docsGCP(not on this cloud)SAP(unknown) Jul 31, 2026
Protobuf tensor input for custom model serving endpoints (Public Preview)
Replaces JSON with serialized KServe v2 ModelInferRequest. Requires endpoints deployed after July 9, 2026.

#Machine Learning #Model Serving

AWS, read it on their docs Azure, read it on their docs GCP, read it on their docsSAP(not on this cloud) Jul 9, 2026
MLflow trace storage in Unity Catalog is now in Public Preview
Stores OpenTelemetry traces, governed by Unity Catalog permissions, queryable from Databricks SQL or MLflow Python SDK.

#MLflow #Unity Catalog

AWS, read it on their docs Azure, read it on their docs GCP, read it on their docsSAP(not on this cloud) Apr 30, 2026
AI Runtime is now in Public Preview
Adds GPU support to serverless compute for deep learning workloads.

#Machine Learning

AWS, read it on their docs Azure, read it on their docsGCP(not on this cloud)SAP(not on this cloud) Mar 19, 2026
Run the change, do not just read it. Hands-on labs in your own Databricks workspace, graded when you submit. Browse labs
Admins can now manage a workspace's serverless base environments (Public Preview)
Defines custom environment specs for serverless notebooks, allows setting a default for new notebooks.

#Notebooks #Serverless

AWS, read it on their docs Azure, read it on their docs GCP, read it on their docsSAP(unknown) Aug 28, 2025

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.