What’s coming?

Learn about upcoming Databricks releases.

Legacy dashboards will reach End of Life before the end of 2025

Databricks recommends using AI/BI dashboards (formerly Lakeview dashboards). Databricks SQL dashboards are now called legacy dashboards. They will continue to receive critical bug fixes, but they won’t be updated with new features. Legacy dashboards will reach End of Life before the end of 2025. Databricks does not recommend creating new legacy dashboards.

Convert legacy dashboards using the migration tool or REST API. See Clone a legacy dashboard to an AI/BI dashboard for instructions on using the built-in migration tool. See Use Databricks APIs to manage dashboards for tutorials on creating and managing dashboards using the REST API.

Changes to access patterns for deleted queries and legacy dashboards

Databricks SQL queries and legacy dashboards will soon adopt the same trash behavior as other workspace objects. Deleted items will no longer appear in the listing pages for queries or legacy dashboards. However, they can still be accessed from the UI by navigating to a user’s Trash folder. For details on managing workspace objects using the UI, see Delete an object. To learn how to manage workspace objects using the REST API, see Workspace in the REST API reference.

The sourceIpAddress field in audit logs will no longer include a port number

Due to a bug, certain authorization and authentication audit logs include a port number in addition to the IP in the sourceIPAddress field (for example, "sourceIPAddress":"10.2.91.100:0"). The port number, which is logged as 0, does not provide any real value and is inconsistent with the rest of the Databricks audit logs. To enhance the consistency of audit logs, Databricks plans to change the format of the IP address for these audit log events. This change will gradually roll out starting in early August 2024.

If the audit log contains a sourceIpAddress of 0.0.0.0, Databricks might stop logging it.

Legacy Git integration is EOL on January 31

After January 31, 2024, Databricks will remove legacy notebook Git integrations. This feature has been in legacy status for more than two years, and a deprecation notice has been displayed in the product UI since November 2023.

For details on migrating to Databricks Git folders (formerly Repos) from legacy Git integration, see Switching to Databricks Repos from Legacy Git integration. If this removal impacts you and you need an extension, contact your Databricks account team.

External support ticket submission will soon be deprecated

Databricks is transitioning the support ticket submission experience from help.databricks.com to the help menu in the Databricks workspace. Support ticket submission via help.databricks.com will soon be deprecated. You’ll continue to view and triage your tickets at help.databricks.com.

The in-product experience, which is available if your organization has a Databricks Support contract, integrates with Databricks Assistant to help address your issues quickly without having to submit a ticket.

To access the in-product experience, click your user icon in the top bar of the workspace, and then click Contact Support or type “I need help” into the assistant.

The Contact support modal opens.

If the in-product experience is down, send requests for support with detailed information about your issue to help@databricks.com. For more information, see Get help.

JDK8 and JDK11 will be unsupported

Databricks plans to remove JDK 8 support with the next major Databricks Runtime version, when Spark 4.0 releases. Databricks plans to remove JDK 11 support with the next LTS version of Databricks Runtime 14.x.

Automatic enablement of Unity Catalog for new workspaces

Databricks has begun to enable Unity Catalog automatically for new workspaces. This removes the need for account admins to configure Unity Catalog after a workspace is created. Rollout is proceeding gradually across accounts.

sqlite-jdbc upgrade

Databricks Runtime plans to upgrade the sqlite-jdbc version from 3.8.11.2 to 3.42.0.0 in all Databricks Runtime maintenance releases. The APIs of version 3.42.0.0 are not fully compatible with 3.8.11.2. Confirm your methods and return type use version 3.42.0.0.

If you are using sqlite-jdbc in your code, check the sqlite-jdbc compatibility report.