What is Agent Telemetry?
ObservabilityThe instrumentation stream an agent emits: spans, eval scores, cost per call, flagged actions. Telemetry is what makes a run investigable; without it, 'the agent got stuck' is a week of archaeology.
Why It Matters
Telemetry is the difference between an incident and a mystery. An agent that emits spans, costs, and flagged actions leaves a record you can interrogate. An agent that emits nothing leaves you reconstructing “the agent got stuck” from side effects and guesswork.
It is also the evidence layer every other discipline reads from. Evals score recorded runs, governance reviews flagged actions, forensics replays the trace tree. Telemetry is upstream of all of it.
What the Stream Carries
Spans. Every step of the run with its kind, inputs, outputs, and latency. The raw record of what happened.
Cost data. Per-call and per-step spend, so a run’s expense is attributable rather than aggregate.
Eval scores. Grades attached to the run where a scorer executed, tying quality to the specific behavior that produced it.
Flagged actions. Policy checks that fired: what was evaluated, what was decided, whether it escalated.
Where It Breaks
Sampling is the common self-inflicted wound. Dropping telemetry to save cost deletes the unusual runs first, and unusual runs are the ones that needed inspection. The other break is coverage gaps: a step that was never instrumented produces no span, and incidents have a way of happening in exactly the uninstrumented parts.
The subtler failure is telemetry without destination. Streams that land in a dashboard nobody reviews during incidents are captured evidence nobody uses.
How Flytebit Handles It
Full-fidelity capture is the starting position in our observability work: every span kind recorded, per-call cost attributed, nothing sampled away, and the stream wired to the destinations that consume it, evals, governance checks, incident forensics. The reasoning is in Observability for Agentic AI Governance.