GitHub Actions: Ubuntu 20 runner image brownout dates and other breaking changes

Ubuntu 20 image is closing down

We are beginning the process of closing down the Ubuntu 20 hosted runner image, following our N-1 OS support policy. This image will be fully retired by April 1, 2025. We recommend updating workflows to use ubuntu-22.04, or ubuntu-24.04.

Brownout dates

To raise awareness of the upcoming removal we will temporarily fail jobs using the ubuntu-20.04 label starting in March 2025. The brownouts will occur on the following dates and times:
– March 4 14:00 UTC – 22:00 UTC
– March 11 13:00 UTC – 21:00 UTC
– March 18 13:00 UTC – 21:00 UTC
– March 25 13:00 UTC – 21:00 UTC

Upcoming breaking changes to hosted runner images

For a full list of this month’s breaking changes to our hosted runner images, please see our announcement page.

Artifact actions v3 brownouts

Artifact actions v3 will be closing down by January 30th, 2025. To raise awareness of the upcoming removal, we will temporarily fail jobs using v3 of actions/upload-artifact or actions/download-artifact. Builds that are scheduled to run during the brownout periods will fail. The brownouts are scheduled for the following dates and times:
– January 16th 3pm – 7pm UTC
– January 23rd 2pm – 10pm UTC

Note: v3 of the artifact actions will continue to be supported for GitHub Enterprise Server customers. The brownouts and retirement will not affect your workflows.

actions/cache v1-v2 and actions/toolkit cache package closing down

Starting February 1st, 2025, Actions’ cache storage will move to a new architecture, as a result we are closing down v1-v2 of actions/cache. In conjunction, all previous versions of the @actions/cache package (prior to 4.0.0) in actions/toolkitwill be closing down. If users run workflows that call the retired versions after February 1st, 2025, the workflows will fail.

You should upgrade to actions/cache v4 or v3 as soon as possible to avoid any disruption in February. For information on how to migrate, see the announcements in the actions/cache and actions/toolkit repositories.

Note: all versions of actions/cache will continue to be supported for GitHub Enterprise Server customers. The retirement will not affect your workflows.

Audit log streaming of API requests targeting your enterprise’s private assets is now generally available. This feature provides you as enterprise administrators new visibility into the API activity within your enterprise.

Audit logs play a critical role in an enterprise owners’ ability to monitor and secure their enterprise. Many enterprises leverage GitHub’s API ecosystem to automate and operate their enterprise at scale. However, API use can also create unique security and operational challenges that must be managed. To help manage these challenges, API requests targeting your enterprise’s private assets can be included in your enterprise’s audit log streams. Please note that API requests targeting public repositories will be omitted from your enterprise’s audit log stream. This new data will allow you as an enterprise owner to:

  • Better understand and analyze API usage targeting your private enterprise assets;
  • Identify and diagnose potentially misconfigured applications or integrations;
  • Track the authentication tokens being used by specific applications or integrations;
  • Troubleshoot API requests contributing to API rate limiting;
  • Analyze API activity when performing forensic investigations; and
  • Develop API specific anomaly detection algorithms to proactively identify potentially malicious API activity.

    An example event payload can be found below:

Example API request audit log event.

Note: Sensitive fields have been redacted for security reasons.

To start streaming API requests, you can follow the instructions in our docs for enabling audit log streaming of API requests. Once enabled, you should begin seeing API request events in your audit log stream.

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The latest AI model from Mistral, Codestral 25.01, is now available in GitHub Models.

Codestral 25.01 is explicitly designed for code generation tasks. It helps developers write and interact with code through a shared instruction and completion API endpoint. As it masters code and can also converse in a variety of languages, it can be used to design advanced AI applications for software developers.

GitHub Models makes it easy for every developer to build AI features and products on GitHub.

Easily try, compare, and implement this model in your code for free in the playground or via the API. Compare it to other code generation models using the side-by-side feature in GitHub Models.

To learn more about GitHub Models, check out the docs. You can also join our community discussions.

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