Understanding Traversal's Responses
Traversal’s output is designed to be transparent, explainable, and audit-friendly, so engineers can understand why Traversal reached its conclusions.
This page explains the common elements you’ll see across our main features.
Root Cause Analysis
Traversal root causes your incidents.
Each root cause analysis includes:
Summary statement
Confidence level (High / Medium / Low)
Evidence citations
Relevant anomalies
Timeline context
Impact estimation
Confidence Levels
Every root cause analysis or alert assessment includes a confidence rating:
High
Strong correlation patterns, consistent evidence across multiple signals.
Medium
Theory is plausible and likely but missing full visibility or traces.
Low
Weak or partial signals. Requires human confirmation.
Explanations for each confidence level can also be found directly in the web app by hovering over each confidence level label.
How To Use This
Traversal’s confidence rating reflects data completeness, not certainty.
Lower confidence often means missing information (e.g. missing logs or traces) or ambiguous symptoms. Always keep in mind that incomplete data leads to lower confidence, and humans remain in the loop for high-impact decisions.
Evidence Citations
Traversal always shows its work.
Evidence can include:
Metrics anomalies
Log lines
Error rate spikes
Deployment events
Code diffs (read-only)
Upstream/downstream failures
Topology relationships
Pull requests
Each citation is clickable, allowing engineers to validate or challenge the AI’s interpretation.
Timelines
Timelines show the sequence of:
When symptoms began
When anomalies were detected
When deployments occurred
When related alerts fired
When dependent services began failing
This helps you understand what happened first and how failures cascaded.
Recommended Next Steps
Traversal may offer:
Diagnostic suggestions
Remediation steps
Runbook-style guidance
Suggested team escalations
These are recommendations, not actions. Traversal will not make changes to your system without permission.
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