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Traversal’s output is designed to be transparent, explainable, and audit-friendly, so you can understand exactly why Traversal reached its conclusions.

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Root cause analysis

Traversal root causes your incidents automatically. Each root cause analysis includes:
  • Summary statement — a concise description of the identified root cause
  • Confidence level — High, Medium, or Low
  • Evidence citations — the signals and data that support the conclusion
  • Relevant anomalies — detected deviations from baseline behavior
  • Timeline context — the sequence of events leading to and during the incident
  • Impact estimation — scope and severity of the failure

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Confidence levels

Every root cause analysis and alert assessment includes a confidence rating. Use this to calibrate how much human review the conclusion needs.
ConfidenceMeaning
HighStrong correlation patterns, consistent evidence across multiple signals.
MediumTheory is plausible and likely but missing full visibility or traces.
LowWeak or partial signals. Requires human confirmation.
Hover over any confidence label in the web app to see an inline explanation of what it means for that specific investigation.
Traversal’s confidence rating reflects data completeness, not certainty. Lower confidence often means missing information — such as absent logs or traces — or ambiguous symptoms. Incomplete data leads to lower confidence, and humans remain in the loop for high-impact decisions.

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Evidence citations

Traversal always shows its work. Every conclusion is backed by cited evidence you can inspect and validate. Evidence can include:
  • Metrics anomalies
  • Log lines
  • Error rate spikes
  • Deployment events
  • Code diffs (read-only)
  • Upstream and downstream failures
  • Topology relationships
  • Pull requests
Citations are interactive — you can engage with them directly from the investigation view without losing your place:
  • Hover over a citation to preview it inline
  • Click to expand it to a full detail view
  • Follow the source link to jump to the underlying data in your observability platform (Datadog, Elasticsearch, etc.) whenever available
Source links let you verify the raw signal behind any finding — useful when you want to validate Traversal’s interpretation or dig deeper than the summary.

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Timelines

The timeline shows the ordered sequence of events so you can understand what happened first and how failures cascaded. Timelines include:
  • When symptoms began
  • When anomalies were detected
  • When deployments occurred
  • When related alerts fired
  • When dependent services began failing
Traversal may offer guidance alongside its root cause analysis:
  • Diagnostic suggestions
  • Remediation steps
  • Runbook-style guidance
  • Suggested team escalations
These are recommendations, not actions. Traversal will not make changes to your system without your explicit permission.