Product

Organization profiles can now display custom content visible only to members of the organization. A new Member view can be tailored to show an alternative README and pinned private repositories.

We’re releasing exciting improvements that will streamline your Codespaces experience when working with multi-repository projects and monorepos.

Today, we’re excited to bring you a few new features that will help you communicate, collaborate, and connect seamlessly with teams and communities about the software you’re building with the help of GitHub Discussions.

Organizations with GitHub Advanced Security can now proactively protect against secret leaks with secret scanning’s new push protection feature.

GitHub Copilot is now available from Visual Studio 2022 for everyone in the technical preview.

You can now enforce consistent usage of self-hosted runner groups across your organization and enterprise.

Today, we are rolling out a new beta version of GitHub’s home feed, making it easier to discover projects, developers and more across GitHub.

If you’re a GHES customer with heavy read traffic on your monorepo, check out the repository cache, especially if you have CI workloads distributed around the world.

You can now create a branch to work on an issue directly from the issue page so that it’s easier to get started right away.

It is now possible to re-run only failed jobs or a single job in GitHub Actions workflows.

We’ve introduced several new features to help enterprise owners more easily manage their accounts, including two features now in public beta.

Explore and understand your overall GitHub-hosted Actions runner capacity with the new runner view.

The ability to prebuild codespaces is entering public beta. Enable fast environment creation times, regardless of the size and complexity of your repositories.

GitHub Actions workflows in the Security category will now appear among the workflow recommendations based on a repository’s content.

Today we launched new code scanning analysis features powered by machine learning. The experimental analysis finds more of the most common types of vulnerabilities.