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When a GitHub Actions run fails, start with the failed job and step in the run’s log; when a job is unexpectedly skipped or runs when it should not, inspect its condition evaluation. “GitHub Actions log failures” can mean either a failed workflow that needs diagnosis or logs that do not contain enough detail to explain what happened. The right next step depends on which problem you have.
Find the failed job and its step
In the repository, open Actions, select the workflow and run, then use the run summary or visualization graph to locate the job with a failure. GitHub Docs says every workflow run generates a graph showing progress; the graph also presents job states and dependencies. Select a job to open its logs. You need repository read access to view them. GitHub’s visualization graph documentation explains the view.
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In the job log, expand the failed step and read its output first. A failed check is not necessarily a code-test failure: the useful clue may instead be a setup command, dependency download, runner, network, billing, or workflow-trigger issue. GitHub’s workflow run log guide covers the run-log view and troubleshooting basics.
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Search, download, or retrieve logs from the command line
For a long log, use the log search field. It searches only expanded steps, so expand the relevant steps before searching. Download the log archive when you need files not visible in the step output or want to inspect or share the evidence outside the browser.
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GitHub CLI can display all logs for a run, or narrow the output to a job or failed steps:
gh run view RUN_ID --log
gh run view --job JOB_ID --log
gh run view --job JOB_ID --log-failedReplace RUN_ID or JOB_ID with the relevant identifier. You can pipe the output to a text-search utility to find a known error string. Be aware that an archive for a partially rerun workflow contains only the jobs from that rerun; gather logs from earlier attempts as well if you need the full run history.
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Enable more diagnostic detail when ordinary output is not enough
GitHub supports two debug settings with different scopes. Enable them only when the regular step output does not answer the question.
| Setting | What it adds | How to enable |
|---|---|---|
| Step debug logging | More detailed output from workflow steps | Set the ACTIONS_STEP_DEBUG secret or variable to true. |
| Runner diagnostic logging | Runner and worker process diagnostic log files in the downloaded archive | Set ACTIONS_RUNNER_DEBUG to true. |
Anyone able to run the workflow can enable debug logging for a rerun. Creating or changing repository, organization, or environment secrets and variables requires the corresponding write or administrator permissions described in GitHub’s debug logging documentation. Treat diagnostic archives according to your repository’s normal secret-handling practices when reviewing or sharing them.
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A rerun can show whether a failure is reproducible and, when debug logging is enabled, provide more detail. GitHub CLI supports rerunning all jobs, failed jobs, or a specific job, and its debug option can enable diagnostic logging:
gh run rerun RUN_ID
gh run rerun RUN_ID --failed
gh run rerun RUN_ID --job JOB_ID --debugRemove the leading space before the second and third commands when copying them into a shell. Most importantly, a rerun uses the original event’s commit SHA and ref. It is not automatically a test of a newer commit; compare runs against the same revision when checking whether a failure is reproducible. See GitHub’s rerun guidance for available rerun scopes.
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Investigate jobs that were unexpectedly skipped or run
When a job-level condition appears to have produced the wrong outcome, download the run’s log archive and open JOB-NAME/system.txt for the relevant job. GitHub documents three useful entries:
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This evidence concerns job-level if conditions. For step-level condition details, use debug logging. GitHub’s condition-expression log guide describes how to interpret the file.
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Use APIs or centralized monitoring only when the workflow calls for it
Automate inspection with GitHub’s REST API
If you need scripted reporting, the workflow-jobs REST API exposes job and step status information and provides a job-log download endpoint that redirects to a plain-text log file. This can support internal tooling without changing how developers inspect an individual run.
Consider a cross-pipeline view for organization-wide needs
GitHub’s built-in run views, archives, CLI, and API are usually the natural starting point for diagnosing a particular failure. A centralized CI view may be useful when a team needs to track workflows across repositories or connect pipeline activity to broader observability workflows.
Datadog documents CI Visibility for GitHub Actions, including workflow execution views and optional forwarding of job logs to Log Management. Datadog says forwarded logs are billed separately, and log files larger than 1 GiB are truncated; see its GitHub Actions CI Visibility setup documentation. Before adopting a third-party service, assess whether it solves a real visibility need and account for access, log handling, retention, and service-specific billing.
Quick Recap
Choose the right diagnostic path
| Need | Start with |
|---|---|
| Explain one failed step | Expand and inspect that step in the run log. |
| Find a message in long output or share evidence | Search expanded steps or download the log archive. |
| Get more detail about a hard-to-explain failure | Enable step debug logging; add runner diagnostics when runner or worker detail is needed. |
| Check whether a failure repeats | Rerun the relevant job, accounting for the original SHA and ref. |
| Understand an unexpected job skip or run | Inspect JOB-NAME/system.txt for job-level condition evaluation. |
| Build automated reports | Use the workflow-jobs REST API or GitHub CLI. |
| See activity across repositories or pipelines | Evaluate whether centralized CI visibility justifies the added log handling and cost. |
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