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6 releases of 1331

Last updated 13 hours ago

Release					Date
Git Folder Serverless is in Beta Shares serverless compute and pyproject.toml environment across notebooks and files. #Compute #Git Folders	On AWS, read it on their docs	On Azure, read it on their docs	On GCP, read it on their docs	Unknown on SAP	Sep 2, 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
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. #Compute #Platform	On AWS, read it on their docs	On Azure, read it on their docs	On GCP, read it on their docs	Not on SAP	May 21, 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
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
Run the change, do not just read it. Hands-on labs in your own Databricks workspace, graded when you submit. Browse labs

Git Folder Serverless is in Beta
Shares serverless compute and pyproject.toml environment across notebooks and files.

#Compute #Git Folders

AWS, read it on their docs Azure, read it on their docs GCP, read it on their docsSAP(unknown) Sep 2, 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
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.

#Compute #Platform

AWS, read it on their docs Azure, read it on their docs GCP, read it on their docsSAP(not on this cloud) May 21, 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
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
Run the change, do not just read it. Hands-on labs in your own Databricks workspace, graded when you submit. Browse labs

Headlines, dates and product areas are Databricks' own, and every item links to the note it came from. The one-line summaries are ours.