Databricks releases, every cloud
- 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.
- Databricks Runtime 19 and Databricks Runtime 19 for Machine Learning are in Beta
Powered by Apache Spark 4.2.0.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Databricks Runtime 18 and Databricks Runtime 18 for Machine Learning are in Beta
Powered by Apache Spark 4.1.0, replacing separate release notes for feature versions.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - 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.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Databricks Runtime 18.2 and Databricks Runtime 18.2 ML are in Beta
Powered by Apache Spark 4.1.0.
AWS, read it on their docsAzure, read it on their docsGCP, read it on their docsSAP(not on this cloud) - Databricks Runtime 18.1 and Databricks Runtime 18.1 ML are in Beta
Powered by Apache Spark 4.1.0.
- Run the change, do not just read it. Hands-on labs in your own Databricks workspace, graded when you submit. Browse labs
- Databricks Runtime 18.0 and Databricks Runtime 18.0 ML are in Beta
Powered by Apache Spark 4.1.0, includes JDK 21 as default.
- 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.
- Databricks Runtime 17.3 LTS and Databricks Runtime 17.3 LTS ML are in Beta
Powered by Apache Spark 4.0.0, includes new configuration options.
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