Log Aggregation for Multi-Agent Systems

Multi-agent systems generate logs from many sources: agent runtimes, policy engines, safety scanners, orchestrators, tool services, and infrastructure. Without aggregation, these logs are scattered across services and impossible to correlate. Log aggregation brings them together into a queryable store that supports monitoring, debugging, and compliance.

Structured Logging

All components should emit structured logs in a consistent format. JSON is the standard choice. Every log entry should include a timestamp, service name, log level, trace ID, and a structured payload.

{
  "timestamp": "2026-02-18T14:30:00.123Z",
  "service": "policy-engine",
  "level": "info",
  "trace_id": "abc-123",
  "event": "policy.evaluation",
  "action": "data.export",
  "decision": "deny",
  "policy_version": "v42",
  "evaluation_ms": 3
}

Collection Architecture

Two common architectures for log collection:

Agent-based: A lightweight log collection agent runs alongside each service, reading log files or receiving log streams and forwarding them to the central store. Tools like Fluentd and Vector work well for this.

Direct shipping: Each service sends logs directly to the central store via HTTP or a message queue. This eliminates the collection agent but couples services to the log store's API.

Storage Considerations

Multi-agent systems produce high log volumes. Choose a storage backend that handles the expected volume at an acceptable cost. Consider retention requirements: compliance may require retaining safety-related logs for years while operational logs can be rotated after weeks.

Authensor's audit receipts are separate from operational logs. Receipts are immutable, hash-chained records stored in PostgreSQL. Operational logs go to whatever aggregation backend the team prefers.

Querying and Correlation

The primary use case for aggregated logs is correlation: given a trace ID, show every log entry from every service for that trace. This requires the trace ID to be present in every log entry and the log store to support efficient filtering on trace ID.

Security of Logs

Logs contain sensitive information: action parameters, resource identifiers, user data, and policy decisions. Protect the log store with access controls. Encrypt logs in transit and at rest. Redact sensitive fields before storage if they are not needed for debugging.

Retention Policies

Define retention by log category. Safety audit logs: retain per compliance requirements. Operational logs: retain for 30 to 90 days. Debug logs: retain for 7 days or less.

Aggregated logs are the memory of your multi-agent system. Without them, incidents are mysteries.