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.
Modules
Expand each module and click a topic to open detailed study notes.
Instrument an app with OpenTelemetryLearn 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.
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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.
See moreLearn 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.
Analyze app telemetry with logs and metricsLearn 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.
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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.
See moreLearn 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.