Structured Logging

Structured logging replaces freeform text messages like `"Tool call failed at 14:23"` with queryable JSON objects: `{"timestamp": "2026-07-09T14:23:01Z", "level": "error", "agent_id": "abc123", "tool_name": "web_search", "error_code": "TIMEOUT", "duration_ms": 5002}`. The difference is not cosmetic — it determines whether you can diagnose a failure in seconds or spend hours grepping through walls of text.

**Key fields for agent systems.** Every log line in an agent system should carry at minimum: `trace_id` (a single identifier that spans the entire task), `span_id` (identifies this particular step within the task), `agent_id`, `tool_name` (when a [[tool-use]] call is being logged), `duration_ms`, `token_count`, and `error_code`. With these fields, a single query can reconstruct the exact sequence of tool calls an agent made across a multi-hour autonomous run.

**Log levels.** Debug logs capture full prompt and response text — valuable locally, dangerous in production. Info logs record task starts, completions, and key decision points. Warn logs flag recoverable anomalies (retried tool calls, approaching [[agent-budget]] thresholds). Error logs record failures that required intervention or caused task abortion. In production, debug logging of prompt content should be disabled by default and enabled only on a per-trace basis under explicit authorization.

**Correlation across tool calls.** The `trace_id` is the connective tissue of structured logging. When an agent makes five tool calls across thirty seconds, correlating them into a single logical task requires every log entry to carry the same trace identifier. This is also the bridge between structured logs and distributed tracing in [[telemetry]] systems — the same `trace_id` and `span_id` values appear in both.

**Privacy and [[confidentiality]] considerations.** Prompt and response logging is the fastest way to inadvertently capture PII — user queries, retrieved documents, generated content may all contain sensitive data. Before enabling full-content logging, ensure log pipelines have appropriate access controls, retention limits, and redaction filters. The [[audit-trail]] value of logging must be weighed against data minimization obligations.

**Common misconception.** Structured logging is not the same as verbose logging. The goal is queryable precision, not volume. A single well-structured error log line that names the agent, tool, error code, and duration is more operationally useful than ten lines of freeform stack trace.

See [[gemini-enterprise-agents]] for a production [[observability]] architecture that pairs structured logging with [[agent-heartbeat]] monitoring.

## Related Terms

- [[glossary/observability|Observability]] — the practice of capturing traces, logs, and metrics to understand agent runtime behaviour - [[glossary/telemetry|Telemetry]] — the structured runtime signals (traces, spans, metrics) emitted by agents for debugging - [[glossary/audit-trail|Audit Trail]] — the immutable chronological record of every action taken, enabling forensic review - [[courses/gemini-enterprise-agents|Course: Gemini Enterprise Agents]] — hands-on practice with the concepts covered in this entry