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@Naros yeah, cancel-in-progress: true is more "please stop scheduling new work" than "yank the power cord on a 2-hour job right now." Long-running steps (especially on self-hosted / ARC) often keep chewing until the current process exits or the runner tears down.

Workarounds that help today while the feature request cooks:

1. Split the monster job: short cancelable prep + long integration jobs in separate workflows / concurrency groups so a cancel doesn't strand everything.
2. Add cooperative cancellation inside the long step (poll cancelled() / check the run status and exit early).
3. For ARC: look at runner pod cleanup / job TTL settings so cancelled jobs don't sit around holding capacity.
4. Use a tighter concurrency group for the long tests only, so a docs-only push doesn't try to cancel a 150-minute suite.

Your ask is still valid though: "cancel-in-progress should mean minutes, not wait-for-current-step." That distinction belongs in the docs if GitHub can't make cancellation hard-stop everywhere.

Curious: are these GitHub-hosted runners or ARC self-hosted? Behavior differs a lot there.

I would distinguish two layers here:

1. GitHub marking the old run/job as cancelled because a newer run entered the same concurrency group.
2. The runner actually terminating the process tree that is currently executing your long integration step.

The concurrency docs describe the scheduling/cancellation policy:

https://docs.github.com/actions/writing-workflows/choosing-what-your-workflow-does/control-the-concurrency-of-workflows-and-jobs

They explain that cancel-in-progress: true cancels an in-progress run/job in the same group, but in practice the speed of resource release still depends on how the runner and the active process respond to cancellation.

For GitHub-hosted runners, cancellation is usually reasonably quick because GitHub owns the VM lifecycle. For self-hosted/ARC runners, a long-running child process can keep doing work unless it handles termination or the pod/runner is forcefully cleaned up.

A few mitigations that have helped in long integration suites:

1. Put concurrency at the job level for the expensive matrix, not only the workflow level.

   That prevents unrelated cheap jobs from being tied to the same cancellation behavior.

   jobs:
     integration:
       concurrency:
         group: integration-${{ github.ref_name }}-${{ matrix.database }}
         cancel-in-progress: true

2. Add cooperative cancellation inside the long-running test harness.

   For example, wrap the integration command in a small script that periodically checks the GitHub run status through the API and exits if the run is no longer active. This is especially useful if the real work is one giant shell command, Docker Compose run, Gradle task, or database test runner.

3. Make the long step respond to SIGTERM and clean up its child processes.

   If the step launches containers, background jobs, nested shells, or test workers, make sure the wrapper traps termination and stops them:

   cleanup() {
     docker compose down -v || true
     jobs -p | xargs -r kill || true
   }
   trap cleanup TERM INT EXIT
   
   ./run-long-integration-suite.sh &
   wait $!

4. For ARC/self-hosted, check runner pod termination behavior.

   If the pod gets a termination signal but the test process ignores it, Kubernetes may wait for the termination grace period. A long grace period, stuck child process, or cleanup finalizer can look like cancel-in-progress did not work. Review the pod terminationGracePeriodSeconds, runner controller logs, and whether cancelled runner pods actually terminate.

5. Split “should this run?” from “run the 150-minute suite.”

   Use a quick gate job to decide whether the expensive suite is needed, then start the expensive job only when the commit still matters. That avoids burning 1-2 hours on commits that are obsolete before they reach the heavy tests.

Your product request is still valid: if GitHub cannot guarantee hard termination, the docs/UI should probably distinguish “run marked cancelled” from “active runner process has actually stopped.” For ARC users, having a first-class “force terminate current runner pod for cancelled job” behavior would be much closer to what people expect from cancel-in-progress: true.