Skip to content
Learn with AlakhSharma

C28

Agent Observability

7 lessons3.5 hoursPlannedFree

Outcome

Trace, debug, and monitor LLM agents and multi-agent systems in production.

Prerequisites

Lessons

  1. L01Why agents need tracing: non-determinism and multi-step failures · coming soonExercise: List five questions about an agent run you can't answer from logs alone.
  2. L02Traces and spans for LLM and tool calls (OpenTelemetry GenAI conventions) · coming soonExercise: Instrument an agent with OpenTelemetry.
  3. L03Tracing platforms: Langfuse, Arize Phoenix, and self-hosted options · coming soonExercise: Send traces to a tracing backend and inspect one run end to end.
  4. L04Token, cost, and latency accounting per task · coming soonExercise: Build a per-task cost and latency breakdown across agents.
  5. L05Debugging multi-agent runs from traces · coming soonExercise: Find the root cause of a looping agent from its trace.
  6. L06Online evaluation and feedback loops · coming soonExercise: Sample production traces, score them with an LLM judge, and add failures to the eval set.
  7. L07Dashboards, SLOs, and alerts for agent systems · coming soonExercise: Define SLOs and alert rules for an agent service.