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- Learn how to instrument distributed applications with OpenTelemetry on Azure to capture distributed traces, diagnose latency issues, and gain deep observability into AI solution components.
After completing this module, you'll be able to:
- Explain how OpenTelemetry provides vendor-neutral observability for distributed AI applications on Azure.
- Add and configure the Azure Monitor OpenTelemetry Distro in an application to collect telemetry data.
- Create and manage custom spans and traces to capture request flows across distributed services.
- Export telemetry data to Azure Monitor Application Insights for analysis and visualization.
- Use trace data in Application Insights to identify and debug performance issues in distributed workflows.
- Query, visualize, and act on application telemetry collected in Application Insights to detect failures, identify performance trends, and maintain operational visibility for AI solutions on Azure.
After completing this module, you'll be able to:
- Write KQL queries to retrieve and analyze application telemetry from Application Insights.
- Explore log data to identify error patterns, performance bottlenecks, and trends in application behavior.
- Build Azure dashboards that display key telemetry metrics and log query results for operational monitoring.
- Create Azure Monitor Workbooks for interactive, parameter-driven telemetry analysis.
- Configure alert rules that detect application failures, performance degradation, and anomalies.
