azure-monitor-opentelemetry-py

Application Insights monitoring for Python apps is enabled via a one-line setup using the OpenTelemetry configure_azure_monitor() function from the azure-monitor-opentelemetry package. This initializes auto-instrumentation to collect traces, metrics, and logs with minimal configuration.

Application Insights auto-instrumentation works seamlessly with Flask, Django, and FastAPI frameworks. The OpenTelemetry integration automatically instruments web requests and traces across these Python web frameworks without requiring manual trace handling.

OpenTelemetry auto-instrumentation is a mechanism that automatically collects observability data such as traces, metrics, and logs from Python applications. It eliminates manual instrumentation code by automatically capturing telemetry from supported frameworks and libraries.

Azure Monitor configuration supports environment-based setup for Application Insights instrumentation. You can use environment variables alongside the configure_azure_monitor() call to manage connection settings and optional instrumentations without hardcoding credentials directly in your Python application.

Custom traces and metrics are sent to Azure Monitor through the OpenTelemetry API after initializing the configure_azure_monitor() function. This allows you to emit custom telemetry data alongside the automatically collected web request and logging data from your Python application.

Application Insights setup with optional credentials is handled by passing authentication parameters to the configure_azure_monitor() function. This initializes the OpenTelemetry instrumentation pipeline with the specified credentials, enabling secure telemetry data export to Azure Monitor.