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Incident Correlation

Incident correlation is the process of linking operational incidents—alerts, errors, and outages—to upstream events such as deployments and CI activity. This page explains practical steps engineers use to establish causal links and triage incidents faster.

What is incident correlation​

Incident correlation is the practice of building timelines and causal mappings that connect alerts and runtime errors to recent changes, deployments, and pipeline events. It focuses on signal alignment (time, commit, artifact) and causal plausibility.

Why this problem happens​

  • Event siloing: alerts, logs, and deploy metadata are stored in different systems.
  • Late discovery: teams often notice an incident long after the relevant deploy happened.
  • Ambiguous ownership: multiple teams and services may be touched by a release, making causal reasoning more difficult.

How engineers debug this​

  1. Build the incident timeline: collect alert timestamps, error spikes, and recent deploy timestamps.
  2. Identify candidate deploys: find deploys that overlap the incident window and match the service/region.
  3. Cross-check commits and artifacts: map deploys to commits and review change sets for risky modifications.
  4. Correlate with CI events: check preceding CI failures or flaky test spikes that could indicate unstable changes.
  5. Prioritize mitigation based on impact and evidence: rollback, patch, or mitigate with feature flags.

Best practices​

  • Keep deploy metadata attached to incidents (deploy id, commit range).
  • Automate incident annotation with deploy context where possible.
  • Maintain a short retention window for high-resolution deploy markers for quick correlation.

Tools that help​

OctoLaunch automates timeline creation and highlights candidate deploys when an incident occurs. It reduces manual search across CI, deploys, and monitoring systems by presenting an aligned view with evidence and suspicion scores.

FAQ​

  • Q: How do you pick the right time window to look for candidate deploys?
    • A: Start with the incident onset and expand backward by a short multiple of typical deployment propagation time (5–30 minutes for many systems), then widen if evidence is missing.
  • Q: Can correlation produce false positives?
    • A: Yes—correlation is probabilistic. Use additional signals (logs, traces, user reports) to confirm causality before rolling back.
  • Q: How does OctoLaunch score candidate deploys?
    • A: OctoLaunch factors timing, affected services, and related CI anomalies into a heuristic suspicion score to prioritize investigation.

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