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/appinsights-instrumentation

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Guidance for instrumenting webapps with Azure Application Insights. Provides telemetry patterns, SDK setup, and configuration references. WHEN: how to instrument app, App Insights SDK, telemetry patterns, what is App Insights, Application Insights guidance, instrumentation examples, APM best practices.

12 files
22.8 KB
MIT
Updated 2 months ago
GitHub
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referencessdkazure-monitor-opentelemetry-py.md

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Azure Monitor OpenTelemetry — Python SDK Quick Reference

Condensed from azure-monitor-opentelemetry-py. Full patterns (Flask/Django/FastAPI, custom metrics, sampling, live metrics) in the azure-monitor-opentelemetry-py plugin skill if installed.

Install

pip install azure-monitor-opentelemetry

Quick Start

from azure.monitor.opentelemetry import configure_azure_monitor
configure_azure_monitor()

Best Practices

Call configure_azure_monitor() early — before importing instrumented libraries
Use environment variables for connection string in production
Set cloud role name for multi-service Application Map
Enable sampling in high-traffic applications
Use structured logging for better log analytics queries
Add custom attributes to spans for better debugging
Use AAD authentication for production workloads

Source: SKILL.md on GitHub

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This skill provides guidance and technical reference for instrumenting applications with Azure Application Insights. It follows industry best practices for configuration management, including secret handling, and uses official Microsoft libraries and tools. No security issues were detected.
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Signed by skilld at b3c238e. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub yesterday.

Activeupdated 2 months ago

Capability

metadata: { "author": "Microsoft", "version": "1.2.1" }

/appinsights-instrumentation