Secret scanning now detects secrets in GitHub wikis

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Publicly leaked secrets in GitHub wikis will also be sent to secret scanning partners participating in the secret scanning partner program.

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GitHub Actions: Hardware accelerated Android virtualization now available

Available now, Actions users of our 2-vCPU GitHub-hosted Linux runners will be able to make use of hardware acceleration for Android testing. Previously this feature was only available on runners with 4 or more vCPUs.

To make use of this on Linux, Actions users will need to add the runner user to the KVM user group

      - name: Enable KVM group perms
        run: |
            echo 'KERNEL=="kvm", GROUP="kvm", MODE="0666", OPTIONS+="static_node=kvm"' | sudo tee /etc/udev/rules.d/99-kvm4all.rules
            sudo udevadm control --reload-rules
            sudo udevadm trigger --name-match=kvm

You will then be able to make use of hardware acceleration when making use of Android emulator actions such as reactivecircus/android-emulator-runner.

For more information on how to set-up hardware acceleration, please see our documentation.

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What’s new for GitHub Actions hosted runners

Today we are announcing exciting updates for GitHub Actions hosted runners, the cloud-based service that provides powerful virtual machines to developers and teams to integrate their automation and CI/CD workflows within GitHub. These updates mark a significant leap towards enhancing enterprise readiness for GitHub Actions and a testament to our commitment to simplifying the adoption of GitHub Actions hosted runners across all project sizes and complexities.

  • Azure private networking functionality, that was previously in public beta, is now generally available. This feature allows you to run your Actions workflows on GitHub-hosted runners that are connected to your Azure virtual network, without compromising on security or performance.
  • We are introducing additional runner SKUs to our hosted runner fleet including a 2 vCPU Linux runner and a 4 vCPU Windows runner, both equipped with auto-scaling and private networking functionalities. Both these SKUs are generally available starting today and are geared to support scenarios where smaller machine sizes suffice yet the demand for heightened security and performance persists.
  • Apple silicon (M1) hosted runners, specifically macOS L (12-core Intel) and macOS XL (M1 w/GPU hardware acceleration) which were previously in public beta, are now generally available.
  • We are also unveiling a GPU hosted runner (4 vCPUs, 1 T4 GPU) available in public beta. The GPU runners are available on Linux and Windows, and are enabled with auto-scaling and private networking functionalities. These runners empower teams working with machine learning models such as large language models (LLMs) or those requiring GPU graphic cards for game development to run their tests more efficiently as part of their automation or CI/CD process.

Get Started

  • Azure private networking for GitHub-hosted runners is available across Team and Enterprise plans. To get started, navigate to the ‘Hosted Compute Networking’ section within your Enterprise or Organization settings. For more details, consult our documentation. To request support for additional Azure regions, please fill out this form. As a note, Azure private networking for GitHub Codespaces continues to remain in beta.
  • The newly added 2 vCPU Linux and 4 vCPU Windows SKUs are generally available starting today across Team and Enterprise plans. To use these runners, create a GitHub-hosted runner by selecting the ‘2-core’ or ‘4-core’ size options in the runner creation flow.
  • macOS L and macOS XL runners are generally available across Free, Team and Enterprise plans, and can be used by updating the runs-on key to use one of the GitHub-defined macOS runner labels. To learn more about pricing for these SKUs, refer to our documentation.
  • GPU runners are available starting today in public beta across Team and Enterprise plans. To learn more about how to setup the runner, images, and pricing, refer to our documentation. To share your feedback and help us find the right additional GPU SKUs to support, please fill out this form.

We’re eager to hear your feedback on any and all of these functionalities. Share your thoughts on our GitHub Community Discussion.

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