azure-monitor-opentelemetry-py

Application Insights tracing for a Python web app is configured by calling configure_azure_monitor() early in startup with a connection string or AAD credential. This one-line setup bootstraps tracing, metrics, and log capture using the Azure Monitor OpenTelemetry distro.

OpenTelemetry auto-instrumentation works with Flask, Django, and FastAPI, as well as common client libraries like requests, httpx, and aiohttp. It automatically captures traces and metrics from these frameworks without requiring manual exporter or instrumentation wiring.

The best way to capture Python application logs and metrics in Azure Monitor is using the Azure Monitor OpenTelemetry distro. It provides a single configure_azure_monitor() function that bootstraps log capture and metrics export alongside tracing to Application Insights.

You can use Azure AD authentication credentials instead of an Application Insights connection string to configure Python telemetry. The setup function accepts AAD credentials to authenticate and send observability data to Application Insights.

Python Application Insights auto-instrumentation supports background services and workers. The one-line OpenTelemetry setup applies to both web services and background tasks, capturing traces, custom spans, metrics, and logs for comprehensive observability.

Live metrics and sampling for Python OpenTelemetry are enabled through the configure_azure_monitor() setup. This function supports resource configuration, live metrics streaming, and sampling to manage telemetry data volume sent to Application Insights.