The Four Pillars of Agent Observability

Traditional observability has three pillars: logs, metrics, and traces. Agent observability adds a fourth: decision records. Logs capture what happened. Metrics capture how much and how fast. Traces capture the flow through the system. Decision records capture why — the reasoning, confidence, alternatives considered, and data that influenced each autonomous decision the agent made.

The fourth pillar is necessary because agent systems make decisions that humans need to understand after the fact. When a traditional system sends an email, the logs show it was sent. When an agent system decides to send an email, the decision record shows: what triggered the decision, what alternatives the agent considered, what data influenced the choice, what confidence level the agent had, and what the expected outcome was. Without decision records, debugging an agent's behavior requires reverse-engineering its reasoning from outputs — which is approximately as productive as debugging a program without stack traces.

1. 1. Structured Logging Every agent action produces a structured log entry with: timestamp, agent ID, action type, input hash, output hash, and duration. Structured logs are queryable. Unstructured logs are archaeology.
2. 2. Agent-Specific Metrics Beyond infrastructure metrics (CPU, memory), track agent metrics: tasks completed per hour, average response time, error rate, escalation rate, decision confidence distribution, and output quality scores.
3. 3. Decision Records For every autonomous decision, record: trigger, alternatives considered, data inputs, confidence score, selected action, and expected outcome. Decision records are the audit trail that makes agent behavior explainable.