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A hung test can block a hotfix when it occupies the only runner eligible to deploy. First determine whether the job is still running, queued, or failed; then use the CI platform’s supported cancellation process and verify the runner is actually available before retrying the deployment. To prevent a repeat, bound job runtime, review runner capacity and eligibility, and retain logs—without weakening deployment access controls.
Find out whether the job is running, queued, or failed
These states point to different problems. A test that is still executing may be consuming the runner; a queued deployment may be waiting for an eligible runner; a failed job may already have released the slot. Check the job’s current state in your CI system, its job log, and the runner’s status before taking action.
Eligibility is not the same as availability. A runner must satisfy the job’s configured labels, tags, groups, or equivalent rules, and it must be able to accept work. The title does not identify the platform or configuration, so the exact matching rules and status labels depend on your system.
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For GitHub Actions self-hosted runners, a job can start only when an online, idle runner matches its runs-on labels and runner groups. Without a matching runner, the job remains queued. GitHub documents that such a queued job fails after 24 hours; that is a GitHub Actions limit, not a general CI timeout. See the GitHub self-hosted runner documentation.
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GitLab: check whether a matching runner can pick up the job
GitLab’s documented execution flow places jobs in a queue for matching runners to pick up, with one job per runner in the basic flow. A queued deployment therefore does not prove that a test is still running: inspect the job state and runner activity. See GitLab Runner documentation.
Cancel a genuinely stuck job, then verify recovery
If the test is still running and there is no useful progress, use the cancellation control supported by your CI platform. Before canceling, confirm that the job is the one holding the runner and consider whether stopping it could interrupt necessary cleanup or evidence collection.
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GitLab documents that an unfinished job can be canceled and that a runner still executing the canceled job loses access to GitLab. That does not establish that every process on the runner host stops immediately. After cancellation, check the platform’s final job state, runner status, and host-side processes or cleanup before assuming the runner can safely take the hotfix deployment. See GitLab CI/CD job documentation. For other platforms, follow their current cancellation procedure rather than assuming GitLab’s behavior applies.
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- Confirm the job state and identify the runner assigned to it.
- Cancel the job using the platform’s supported control if it is genuinely stuck.
- Check the final job result and runner status in the CI system.
- Inspect runner logs and, if you administer the host, verify that test processes and cleanup have ended before retrying deployment.
Set timeouts that bound a hang without cutting off normal work
A job timeout limits how long work may run, but its value should reflect the test’s normal runtime, the release deadline, and any required cleanup. The incident details do not establish a safe duration. Set a limit that provides enough time for expected execution and orderly shutdown, and confirm how your CI platform handles cancellation, cleanup, and artifacts at timeout.
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GitLab Runner supports a maximum job timeout as well as separate script and after-script timeout controls. Its documented variables are RUNNER_SCRIPT_TIMEOUT and RUNNER_AFTER_SCRIPT_TIMEOUT; they apply to GitLab Runner and should not be copied into other CI systems. A shorter script limit can leave time for cleanup, but configure it only after checking the runner’s overall timeout and your pipeline’s cleanup requirements. See GitLab Runner advanced configuration.
Review the single-runner bottleneck without loosening deployment access
If tests and deployments depend on the same sole eligible runner, a test that occupies it can leave the deployment with no execution slot. That makes the runner a capacity bottleneck, regardless of why the test hung. Consider these design options against your actual workload and access rules:
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- Add an independently available eligible runner. Redundancy helps only if the additional runner can accept the deployment job and is authorized to do so.
- Separate test work from deployment work. Scheduling tests on a different runner pool can reduce competition for deployment capacity, provided the deployment still runs only on appropriately authorized infrastructure.
- Adjust scheduling or capacity limits. First determine whether the delay comes from runner availability, matching rules, or an internal concurrency bottleneck. In GitLab Runner, worker, request, and build limits can each affect throughput; GitLab documents reviewing and tuning those limits when a bottleneck is identified.
Do not broaden labels, groups, tags, or credentials simply to make a job start. Any capacity change should preserve the authorization boundary that makes a runner eligible to deploy in the first place.
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Keep logs that can explain the next failure
Retain the job output and runner logs needed to distinguish a slow test, a hung process, a matching problem, or a cleanup failure. GitHub specifically recommends preserving ephemeral self-hosted runner logs externally for troubleshooting, because an ephemeral runner can process one job and then deregister. See the GitHub self-hosted runner documentation.
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