What is an Agent Observability?

Agents fail in ways traditional software monitoring wasn't built for: a slow API call is easy to spot with a latency metric, but an agent quietly making a subtly wrong decision, looping unproductively, or drifting from its intended behavior after a model update needs a different kind of visibility — into reasoning steps, tool call patterns, and outcome quality, not just uptime and response time. A mature observability setup layers several things together: structured, per-stage logs that name exactly which step failed and why (not a generic "error"), metrics on tool-call success rates and agent-loop step counts, and traceability from a high-level activity log down to the specific model call or tool invocation that produced a given result. This is also where problems get caught before they become incidents — a spike in failed capability checks or an unusual pattern of tool calls is often the first sign something upstream (a changed API, an expired credential, a model regression) needs attention.