Debugging Distributed Agents
Pinpoint why an autonomous system failed without searching through 50 different log streams.
The Observability Gap
When an agent-driven workflow fails in production, the "State" is scattered across multiple pods. Attaching a debugger to a single container is useless because the failure likely originated three steps ago in a different service.
The Trace ID: Your Unified Lever
Every user interaction starts with a Trace ID. This ID is cryptographically propagated by the Consonant Relayer across every agent call, tool execution, and database query.
Multi-Pod Log Tailing
cons logs --trace-id d8f2-44a1-8e9cThis command automatically aggregates logs from all agents that participated in session d8f2-44a1-8e9c, sorted chronologically.
Waterfall Debugging
The cons trace command reconstructs the execution timeline. It allows you to see exactly where "Latent Hallucinations" or "Component Timeouts" occurred.
cons trace d8f2-44a1-8e9c
[0ms] SYSTEM: Goal Received
[120ms] PLANNER: Plan generated (Step 1: Auditor, Step 2: Coder)
[150ms] AGENT:auditor -> REQUEST: Check security of main.py
[1200ms] AGENT:auditor <- RESPONSE: "File is safe" (tokens: 502)
[1250ms] AGENT:coder -> REQUEST: Refactor main.py
[15000ms] AGENT:coder <- ERROR: Context window exceededHallucination Detection
Consonant's sidecar uses small, specialized "Verifier" models to check agent outputs in real-time. If an output violates a predefined schema or policy, it is marked as a "Trace Fault," alerting you before the invalid data reaches your core systems.