timeline-trace-investigator

Incident timeline reconstruction from distributed traces requires aggregating chronological evidence from logs, deployments, and metrics to identify gaps and correlate events across multiple services for downstream debugging.

Debugging latency spikes across microservices requires trace analysis to identify missing spans, time gaps, and silent services, then correlating those gaps with deployment changes and metric spikes to pinpoint root causes.

Gap detection in distributed trace analysis identifies missing spans, time gaps between service calls, and silent services that fail to emit traces, helping engineers find broken links in multi-service incident chains.

Correlating deployments and config changes with errors requires linking deployment history and metrics spikes to trace anomalies, enabling structured TimelineEvidence output that maps chronological events to root causes.

Timeline trace investigation supports post-mortem analysis of cascading failures by collecting multi-source evidence from distributed traces, logs, and deployments, then producing structured TimelineEvidence with events, gaps, and correlations.

Multi-service incident timeline reconstruction requires distributed traces, deployment history, logs, and metrics as input, which the analysis engine processes to generate structured TimelineEvidence with chronological events and gap detections.