Your agent passed every test and shipped. Two weeks later, someone asks why it approved something it should not have—and the logs cannot explain the decision.

Traditional monitoring can tell you whether the service was healthy. Latency, error rate, and uptime matter, but they do not show which context the agent received, which tools it called, how decisions changed across handoffs, or where a multi-step workflow drifted.

This session shows how to build an agent-observability layer with OpenTelemetry. We will start with a live failure that looks normal in the application logs. Then we will trace the request across model calls, tool execution, and agent handoffs until the reason for the bad decision becomes visible.

Along the way, we will capture the signals that matter: inputs and outputs at reasoning boundaries, tool arguments and results, token cost, latency, errors, and the evidence used to make a decision. We will also examine what not to capture—and why observability should not become indiscriminate prompt logging.

Attendees will leave able to distinguish infrastructure monitoring from agent tracing, instrument an agent pipeline, troubleshoot a failed decision, and define the minimum observability required before an agent reaches production.

If you cannot explain what the agent did, you are not ready to operate it.

Audience: Engineers and technical leads operating agent systems in or near production.
Format: 60–75-minute technical talk with a live tracing demonstration.
Demo: Microsoft Agent Framework on Azure instrumented with OpenTelemetry; concepts transfer to other runtimes.
Materials: Talk-specific repository, slides, and recording are not yet published.
Vendor scope: Vendor-neutral observability model with a Microsoft implementation.