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AI-200 Learn

Secure, monitor, and troubleshoot Azure solutions, 20–25% of the exam

Observe and troubleshoot apps on Azure

This learning path teaches you how to gain end-to-end observability into distributed AI applications on Azure: instrumenting applications with OpenTelemetry to capture distributed traces and export telemetry to Azure Monitor Application Insights, and analyzing telemetry with KQL queries, dashboards, workbooks, and alerts.

Start with Explore OpenTelemetry and its role in observability
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Instrument an app with OpenTelemetry

Learn how to instrument distributed applications with OpenTelemetry on Azure, create custom spans and traces, export telemetry to Azure Monitor Application Insights, and use trace data to debug performance issues in distributed AI solutions.

  1. Explore OpenTelemetry and its role in observability
  2. Add the OpenTelemetry SDK to an application
  3. Configure spans and traces
  4. Export telemetry to Azure Monitor
  5. Debug distributed flows with trace data
  6. Exercise - Instrument an app with the OpenTelemetry SDK

Analyze app telemetry with logs and metrics

Learn to write KQL queries against Application Insights logs, explore error patterns and performance trends, build dashboards and workbooks for ongoing visibility, and configure alerts to detect failures and anomalies in AI solutions on Azure.

  1. Write basic KQL queries
  2. Explore logs for errors and performance
  3. Build dashboards for app telemetry
  4. Create workbooks for interactive analysis
  5. Set alerts for app failures and anomalies
  6. Exercise - Query logs with KQL