Databricks support lifecycles

As part of Databricks’s commitment to innovation, platform and runtime features might be retired and replaced by new features. Databricks Runtime releases are also retired and replaced on a regular schedule. The following tables list retirement phases and details about corresponding support for platform features and Databricks Runtime releases.

For information about previews and release types, see Databricks preview releases.

Platform feature lifecycle

Databricks platform feature retirement phases are described in the following table:

Phase	Description	Support	Migration notes
Legacy	The feature is still available, but there is a newer, better feature or way to accomplish the tasks that this feature provides. This label is indicative of a future retirement date.	Full. Support and documentation are available.	Migration to a new replacement feature or a new way of accomplishing the task is encouraged, but not immediately necessary.
Deprecated	The feature is no longer in active development. Updates are no longer being released. The feature will soon be retired, so you need to develop a plan to stop using the feature and transition to an alternative.	Full. The feature is no longer being updated, but support and documentation are still available.	Migration to a new replacement feature or a new way of accomplishing the task is highly encouraged, because important updates are no longer being applied.
End of Support (EoS)	The feature is no longer in active development and support is officially unavailable.	None. Documentation might still exist, but it has been archived and is no longer being maintained.	Migration to a new replacement feature or a new way of accomplishing the task is urgent, because important updates are no longer being applied and support for issues that might arise is no longer available.
End of Life (EoL)	The feature has been completely removed from the Databricks product.	None	Migration to a new replacement feature or a new way of accomplishing the task is required, because the feature is no longer usable. At this point it might be very difficult to migrate.

Databricks Runtime support lifecycles

The following tables describe the stages of support and support policies for Databricks Runtime versions. Databricks releases runtimes as Beta and GA versions. Databricks supports GA versions for six months, unless the runtime version is a long-term support (LTS) version. For information on supported Databricks Runtime versions, see Databricks Runtime release notes versions and compatibility.

Workloads on unsupported Databricks Runtime versions might continue to run, but Databricks does not provide support or fixes.

Databricks Runtime LTS version lifecycle

Phase	Description
Beta	Support SLAs are not applicable. For more information, see Databricks Runtime releases.
GA, full support for LTS version	Major stability and security fixes are backported. Databricks releases LTS versions every six months and supports them for three full years. Supported LTS releases are published at Supported Databricks Runtime LTS releases.
End of Support (EoS)	If a version is unsupported: Workloads running on these versions receive no Databricks support. Fixes are not backported. It is no longer selectable using the UI when you create or update a compute resource. The end-of-support date is three years after release. Unsupported releases are published at End-of-support Databricks Runtime release notes.
End of Life (EoL)	Databricks reserves the right to completely remove a release version at any time after support ends, without prior notice.

Databricks Runtime Non-LTS version lifecycle

Phase	Description
Beta	Support SLAs are not applicable. For more information, see Databricks Runtime releases.
GA, full support	Major stability and security fixes are backported. Full support for Databricks Runtime versions lasts for six months, with the exception of long-term support (LTS) versions. Supported releases along with their end-of-support dates are published at All supported Databricks Runtime releases.
End of Support (EoS)	If a version is unsupported: Workloads running on these versions receive no Databricks support. Fixes are not backported. It is no longer selectable using the UI when you create or update a compute resource. Unsupported releases are published at End-of-support Databricks Runtime release notes.
End of Life (EoL)	Databricks reserves the right to completely remove a release version at any time after support ends, without prior notice.