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Short answer: GitHub Actions can rerun a workflow or its failed jobs, but the official documentation does not describe a built-in feature that detects an AWS Spot interruption and automatically retries only jobs stopped for that reason. To automate it, a controller must identify the interruption, decide whether a retry is safe, and call GitHub’s rerun API with tightly scoped permissions and a retry limit.
What GitHub can rerun—and what it does not detect
GitHub supports rerunning an entire workflow, all failed jobs, or a specific job. You can do this in the GitHub interface or with GitHub CLI. For example, gh run rerun RUN_ID reruns the workflow, while gh run rerun RUN_ID --failed reruns its failed jobs. See GitHub’s rerun documentation.
GitHub also provides REST API endpoints to rerun a workflow or its failed jobs. A successful API request returns HTTP 201. The API is the mechanism an automation can use to request a rerun; it does not, by itself, establish why a job failed. The official GitHub and AWS documentation cited here does not describe a native integration that recognizes an AWS Spot interruption and automatically reruns the affected job.
What an AWS Spot interruption means for a runner
Spot Instances use spare EC2 capacity, which AWS can reclaim. Depending on the interruption behavior configured for the instance, AWS can terminate it, stop it, or hibernate it; termination is the default. AWS lists capacity needs, price changes, and request constraints among possible interruption reasons. See AWS’s explanation of Spot interruption behavior.
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For a stop or termination, AWS usually sends an interruption notice two minutes beforehand. The notice is available through EventBridge and the instance metadata service, which AWS recommends checking every five seconds. Delivery is best effort, however, and hibernation starts immediately without that two-minute lead time. Treat the notice as an opportunity for graceful handling, not a guarantee that a runner will have time to save state. AWS’s guidance is to “architect your application to be fault-tolerant.” More detail is in AWS’s Spot interruption notice documentation.
Choose a retry approach
| Approach | Best suited to | Important limitation |
|---|---|---|
| GitHub interface | Occasional interruptions that an operator can review | Requires a person to identify the likely cause and request the rerun. |
| GitHub CLI | Explicit operational reruns from a command line | gh run rerun RUN_ID reruns the workflow; gh run rerun RUN_ID --failed reruns failed jobs. Neither command classifies the failure as Spot-related. |
| GitHub REST API plus a controller | A team-built automated decision and rerun process | Your controller must establish the cause, enforce retry limits, and avoid retrying unrelated failures. |
| Runner handling of AWS notices | Graceful shutdown or cleanup when a notice arrives in time | Notices are best effort; hibernation has no two-minute warning. |
For API details, including endpoint permissions, consult GitHub’s workflow-runs REST API reference. The right choice depends on whether an operator needs to review failures, how reliably your setup can distinguish an interruption from a test or configuration failure, and whether the job can safely run again.
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Build an automated rerun without creating a retry loop
A practical design separates interruption detection from the rerun decision. AWS’s notice can help a runner shut down cleanly, but because it may not arrive, the post-failure controller also needs a way to correlate AWS instance events with the failed GitHub job. The cited documentation does not prescribe a universal correlation method; that part depends on how your runners are provisioned and how you record their instance and job identities.
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- Classify before retrying. Use available AWS interruption evidence and runner/job records to distinguish an instance interruption from application, test, workflow, or configuration failures. If the cause is ambiguous, route the run for human review instead of treating every failure as Spot-related.
- Check that rerunning is safe. A rerun starts the job again; it is not a continuation from the point where the instance stopped. Make external side effects and partial outputs safe to repeat, or ensure the job can detect and recover from them.
- Request the narrowest rerun that fits. Use the failed-jobs endpoint when rerunning failed jobs is appropriate, or the workflow endpoint when the workflow itself must run again. Avoid rerunning unrelated work unnecessarily.
- Bound retries and record each attempt. Track attempts against the original workflow run, apply a small policy chosen by your team, and stop when the cause is not confirmed or the limit is reached. GitHub allows reruns for up to 30 days after the initial run and caps a workflow run at 50 reruns total, counting full and partial reruns.
- Keep the token least-privileged. For the failed-jobs API endpoint, a fine-grained personal access token needs Actions write permission on the repository; a classic token needs the
reposcope. Grant only the access needed for the controller and protect its credentials.
GitHub reruns use the original run’s GITHUB_SHA and GITHUB_REF, and the privileges of the actor who originally initiated the workflow. Those details matter when deciding whether replaying a job is safe and when auditing who authorized the original run.
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Test the recovery path in stages
AWS documents a way to initiate a Spot interruption for testing. It sends a rebalance recommendation and an interruption notice, then interrupts the instance after two minutes; if hibernation is configured, hibernation begins immediately. AWS says this mechanism is supported in all regions except Asia Pacific (Jakarta), Asia Pacific (Osaka), China (Beijing), China (Ningxia), and Middle East (UAE). Check the current AWS interruption-testing instructions before using it in a particular region.
- Verify that the runner handles a notice when one is delivered, without assuming the notice is guaranteed.
- Verify that an interrupted runner produces the failure signals your controller expects.
- Verify that the controller correlates the failed run to the relevant instance and refuses to retry unrelated failures.
- Verify that the API request has the intended scope, reruns only the intended work, and stops at the retry limit.
This tests the AWS and GitHub parts of your implementation separately; the documented AWS test does not provide an end-to-end GitHub rerun test.
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When to use manual reruns instead
If Spot interruptions are rare, or your system cannot reliably link a failed job to an interrupted instance, manual review is safer than an automated rule that retries every failure. An operator can inspect the run and request a full or failed-jobs rerun in GitHub or with the CLI. If interruptions are frequent, invest first in reliable instance-to-job correlation and repeat-safe job design; the API can submit a rerun, but it cannot make an uncertain diagnosis correct.
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