Exploring the New Actions Performance Metrics Now in Public Preview 👀⏱️ #142513
Replies: 9 comments 13 replies
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The dates in Edit: it turns out my |
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Is there a way to filter by branch? I'd love to be able to filter the insights of my team's action runs by our main branch to determine stability and performance in scenarios where it should pass 100% |
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This is a much-needed addition, thanks for your work on this. For an enterprise like ours with more than 100 organizations, this won't be very useful for administration until we can get an enterprise-level version of this dashboard. That said, here's some additional views we'd love to see here (the most important ones to our enterprise are at the top):
Some of this ☝️ is related to the feedback I left on the usage metrics discussion. If you have API support in the pipeline sooner than an enterprise-level dashboard, we'd love to know so we can plan to cobble together our own enterprise-level summaries. |
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Is there an API for this? We would love to have one to integrate those metrics in application related dashboards 🙏🏻 |
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Is the average for run time mean or median? It would be great to be able to remove some outliers or break them down by certain percentiles. I think our data is skewed short by jobs that get cancelled early as well. Maybe those could be excluded? |
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Any idea in which time-frame this makes it to the GHES (on premise) if at all? |
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Hi, I have a couple of questions/remarks:
Thanks in advance, great feature! |
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I am interested at looking at the 'called' workflow usage so that we can measure reuse of our reusable actions and workflows. Right now I cannot see a way of doing this; the caller workflows and actions are displayed. Example: a ci.yml workflow in a given repository calls:
As the owner of the 3 called workflows I am interested in usage of them, however they are hidden in the GitHub Actions Org Insights because they only show the usage of ci.yml for that given run. In addition some of these are stacked a few levels deep in the hierarchy (e.g. reuse-build may have reuse-action-1 as part of it) - so the API isn't much use either (as detailed here https://docs.github.com/en/actions/sharing-automations/reusing-workflows#monitoring-which-workflows-are-being-used) |
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We are excited to introduce a new observability UI that provides insights into the performance of your workflows and jobs for your organizations or repositories, now available in public preview! Performance metrics are designed to help you monitor, analyze, and optimize your Actions workflows and job execution. With these insights, you can answer common questions like:
Get insights on job origin points, allowing you to address lengthy processes directly and refine areas with the most significant impact.
Getting Started ➡️
To start leveraging these insights, navigate to your organization or repository homepage, select **“Insights” **near the top of the page, and then choose “Actions Performance Metrics” on the left side of the page. Once you’re there, you’ll have public preview access to detailed metrics on your workflows and jobs, offering a comprehensive view of performance at every stage.
GitHub Actions Metrics for Free, Pro, and Team plans 🆓
We are also pleased to announce that with today's release, GitHub Actions Metrics are now available to Free, Pro, and Team plans. Previously, this feature was only available to those on the GitHub Enterprise Cloud plan.
To learn more about GitHub Actions Metrics, check out our public documentation
Share your Feedback 💬
We’re committed to making Actions Performance metrics as helpful and actionable as possible, and hearing directly from you will guide future improvements. As you explore the new feature, keep these questions in mind to help guide your experience:
We'll use both discussions (Enterprise preview back in July ) to collate your feedback 👍
Share your Wins 🏅
We’d love to hear how you’re using the new Actions Performance Metrics to make a difference in your workflows and job management. Has this feature helped you identify and address issues you previously couldn’t pinpoint? What changes did you make, and what was the outcome? Did the insights reveal any surprises in your workflows, such as hidden bottlenecks or frequent failure points?
Share your stories and feedback in the comments below 👇👍
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