Deep Learning Containers publishes containers and virtual machine images to simplify the
configuration of your machine learning (ML) workloads. These images contain the
operating system, the ML frameworks, drivers, and other libraries. We publish
new versions of images regularly to include new patches, security updates, and
features. Each image provided by Deep Learning Containers provides support for a
specific minor version of an ML framework.

This allows you time to update and test your code
when moving from one framework version to another. You should always test your
jobs and models thoroughly when switching to a new framework version, regardless
of whether it's a major or minor update.

For all services, subscribe to the [Deep Learning Containers release notes](https://docs.cloud.google.com/deep-learning-containers/docs/release-notes) page
for announcements about new version releases for your containers, images, and
frameworks.

For the list of supported framework versions, see [Choose a container image](https://docs.cloud.google.com/deep-learning-containers/docs/choosing-container#deciding).

## Shared responsibility

Securing your workloads on Deep Learning Containers is a shared responsibility. While
Deep Learning Containers regularly publishes new versions of images to address
security vulnerabilities, you are responsible for tasks such as the following:

- Manually upgrading to the latest version.

- Ensuring that you properly configured your services to use the latest version.

For more information, see [Shared responsibility](https://docs.cloud.google.com/deep-learning-containers/docs/shared-responsibility).

## Support policy for framework versions

During the supported period for an ML framework version, we will publish new
image versions regularly. The updates may include the following:

- Patch updates for supported frameworks. For example, if we support
  TensorFlow 2.7, and TensorFlow releases 2.7.1 to address bugs, we will
  release a new image version.

- Security updates for supported frameworks.

- Non-breaking updates to other packages and software installed on the image.

- Updates to dependencies that have reached end-of-support. For example, if an
  image has Python 3.7 installed and it reaches the end-of-support date, we
  will release a new image version. If the change in dependency may be a
  breaking change, we will update [Choose a container image](https://docs.cloud.google.com/deep-learning-containers/docs/choosing-container#deciding)
  to indicate the change in the dependency.

Once published, an image version is immutable and does not change. You should
always use the latest image version, as older versions may have security
vulnerabilities or other critical bugs.

### Support policy schedule

Support periods for each framework version follows this schedule:

- **End-of-patch and support date:** After this date, Deep Learning Containers will no
  longer publish new image versions for that framework version. Existing
  resources that have been deployed to Deep Learning Containers continue to function.
  After this date, we recommend you plan to switch to a more recent framework
  version.

  To receive troubleshooting support from Deep Learning Containers, you may be asked
  to upgrade to a framework version that is within the supported time period.
- **End-of-availability date:** After this date, you can no longer use images
  for this framework version. Services may block the creation of new resources
  using these images, and the images will no longer be available for download.

## What's next

- Review the [list of supported framework versions](https://docs.cloud.google.com/deep-learning-containers/docs/choosing-container#deciding).