Trace an outage by first confirming its user impact, then building a shared timeline, investigating with the right telemetry, and testing specific cause hypotheses. If a safe, evidence-based mitigation is available, restore service before waiting for a complete explanation. Verify recovery, communicate status, and document the cause and follow-up actions so the incident produces lasting improvements.
1. Confirm the alert and establish impact
An alert is a signal to investigate, not proof that users are affected. Check whether the service is actually unhealthy and identify which operations, users, regions, and time window are involved. Where available, compare service health with the relevant service-level objectives (SLOs) and indicators (SLIs), such as error rate or latency.
Monitoring should help responders detect problems, diagnose them, visualize service behavior, and spot trends. Google’s guidance explains these roles in Monitoring. Record what is known, what is uncertain, and how impact is changing; this gives the response a clear starting point.
2. Create a shared incident timeline
Keep a single timeline in the incident record or shared response channel. Include the alert time, first observed symptom, relevant deployments and configuration changes, dependency events, mitigation attempts, and recovery checks. Note who observed each event and, when possible, link to the supporting dashboard, log, or change record.
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Use timing to generate questions, not to declare a cause. A change that precedes an alert may be relevant, but monitoring can lag behind an action or symptom. Google cautions that this delay can lead responders to draw false conclusions from apparent timing correlations (Monitoring).
3. Match telemetry to the question
Metrics and logs answer different questions. Metrics are useful for a fast, aggregated view of health and scale, and commonly power alerts and dashboards. Logs can provide event-level detail, request context, and entity identifiers that are too high-cardinality to make useful metric labels. Use each source for what it shows well, then compare findings across them.
| Signal | Best starting question | What it can show |
|---|---|---|
| Metrics and dashboards | When did service health change, and how widespread is it? | Aggregated behavior, trends, and whether an alert or SLO-related indicator is worsening. |
| Structured logs | What happened to particular requests or entities? | Detailed events and contextual identifiers that may be impractical as metric labels. |
| Traces, if available | Where did a request spend time or fail across a service path? | Potential cross-service request context; the cited Google guidance does not establish a comparative performance claim for tracing. |
The metrics-versus-logs distinction and their roles in monitoring are described in Google’s Monitoring guidance. Do not assume that one telemetry source alone establishes the cause.
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4. Coordinate investigation and communication
Give the response a clear incident lead, a shared communication channel or incident record, and defined escalation paths to service owners and dependency teams. Keep a concise status summary that states customer impact, what responders know, what they are checking, and the next update. Assign investigation threads so teams can compare evidence rather than duplicate work.
Escalate when evidence points to a system owned by another team, while keeping impact and restoration visible to everyone involved. Google’s Incident Management Guide describes the importance of reliable alerting and on-call processes; its incident-response example also shows the value of confirming user impact, communicating it, and involving the relevant infrastructure team (Root Cause Analysis for Probing Incident).
5. Mitigate safely before the explanation is complete
If the affected area is understood and a prepared recovery action is safe under your system’s runbooks and risk controls, use it to reduce user impact. Depending on the system, the available option might be a rollback, traffic shift, restart, or another controlled recovery. None is universally safe: consider blast radius, data consistency, dependencies, and the risk of making the incident worse.
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Google SRE states that its practice is to stop incident impact first and then find the root cause, unless the cause is identified early. In other words, responders do not need a complete mechanism-level explanation before taking a justified mitigation (Root Cause Analysis for Probing Incident). Record the action, its rationale, expected effect, and observed result in the timeline.
6. Test cause hypotheses against evidence
Turn possible explanations into hypotheses that can be checked. For each one, write down what evidence would support it and what would weaken it. Compare symptom onset and recovery with metrics, relevant log events, traces if available, deployment and configuration history, and dependency behavior. A hypothesis that fits only the timing is not yet a root cause.
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- Countercheck: Look for failures in unaffected paths, regions, or versions that would suggest a broader dependency or infrastructure problem.
- Keep alternatives open: A plausible external explanation can distract from the actual failure. Google’s incident example describes investigators initially focusing on an apparent image-source problem before finding a corrupt image in a different storage layer (Root Cause Analysis for Probing Incident).
Continue to distinguish confirmed facts from working theories in incident updates. If an action appears to fix the issue, that is useful evidence, but it does not by itself explain why the failure occurred.
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7. Verify recovery and close the response deliberately
After mitigation, check the user-visible operations that were failing as well as relevant health indicators. Look for sustained recovery, not just a brief improvement, and monitor for recurrence. Ask the relevant on-call engineers or service owners to confirm the affected path is healthy, communicate the resolution, and keep the timeline of checks and decision points.
Google’s incident-response example describes validating recovery with the relevant on-call engineers before closing the incident (Root Cause Analysis for Probing Incident). If symptoms return, reopen the investigation rather than treating the earlier improvement as proof that the incident is over.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.8. Write a postmortem that leads to action
A useful postmortem records impact, timeline, trigger, root cause, contributing conditions, detection and response lessons, and corrective actions with owners. Keep it blameless: the aim is to understand how system design, processes, and safeguards allowed the incident to happen, not to assign fault to the last person or change in the timeline.
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Google’s guidance describes postmortems as a way to identify systemic patterns and guide improvements (Postmortem Practices for Incident Management; Postmortem Analysis). The analysis chapter reports historical findings from Google’s own postmortem sample, not general industry probabilities. In its 2010–2017 sample of thousands of postmortems, listed trigger shares included binary pushes at 37%, configuration pushes at 31%, user behavior changes at 9%, processing pipelines at 6%, service-provider changes at 5%, performance decay at 5%, capacity management at 5%, and hardware at 2%. These figures describe that historical sample only; they should not be used to predict the cause of a new outage.
The same chapter presents a root-cause category breakdown of software at 41.35%, development-process failure at 20.23%, complex system behaviors at 16.90%, deployment planning at 6.74%, and network failure at 2.75%. A separate period for that breakdown is not stated, so treat it as a reported Google classification rather than a current or universal distribution. Assign each corrective action an owner and a way to verify completion; the learning is not complete while follow-up work remains unowned (Postmortem Practices for Incident Management).
A compact incident checklist
- Validate the alert and identify affected users, operations, regions, and time window.
- Start a shared timeline and record observations, changes, mitigations, and checks.
- Use metrics for aggregated health and logs for event-level context; correlate evidence across sources.
- Name an incident lead, assign investigation threads, and communicate impact and status.
- Take a safe, evidence-based mitigation when it can reduce impact; do not wait for a complete root-cause explanation.
- Test hypotheses against evidence, including evidence that could disprove them.
- Verify user-visible recovery, monitor for recurrence, and communicate resolution.
- Document root cause and contributing conditions in a blameless postmortem, with owned corrective actions.
For more detail on Google SRE’s incident-management material, see the Google SRE Workbook index.
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