appinsights-instrumentation

作者: microsoft

使用Azure Application Insights檢測Web應用程式的指南。提供遙測模式、SDK設定與組態參考。適用時機:如何檢測應用程式、App Insights SDK、遙測模式、什麼是App Insights、Application Insights指南、檢測範例、APM最佳實踐。

npx skills add https://github.com/microsoft/skills --skill appinsights-instrumentation

AppInsights Instrumentation Guide

This skill provides guidance and reference material for instrumenting webapps with Azure Application Insights.

⛔ ADDING COMPONENTS?

If the user wants to add App Insights to their app, invoke azure-prepare instead. This skill provides reference material—azure-prepare orchestrates the actual changes.

When to Use This Skill

  • User asks how to instrument (guidance, patterns, examples)
  • User needs SDK setup instructions
  • azure-prepare invokes this skill during research phase
  • User wants to understand App Insights concepts

When to Use azure-prepare Instead

  • User says "add telemetry to my app"
  • User says "add App Insights"
  • User wants to modify their project
  • Any request to change/add components

Prerequisites

The app in the workspace must be one of these kinds

  • An ASP.NET Core app hosted in Azure
  • A Node.js app hosted in Azure

Guidelines

Collect context information

Find out the (programming language, application framework, hosting) tuple of the application the user is trying to add telemetry support in. This determines how the application can be instrumented. Read the source code to make an educated guess. Confirm with the user on anything you don't know. You must always ask the user where the application is hosted (e.g. on a personal computer, in an Azure App Service as code, in an Azure App Service as container, in an Azure Container App, etc.).

Prefer auto-instrument if possible

If the app is a C# ASP.NET Core app hosted in Azure App Service, use AUTO guide to help user auto-instrument the app.

Manually instrument

Manually instrument the app by creating the AppInsights resource and update the app's code.

Create AppInsights resource

Use one of the following options that fits the environment.

  • Add AppInsights to existing Bicep template. See examples/appinsights.bicep for what to add. This is the best option if there are existing Bicep template files in the workspace.
  • Use Azure CLI. See scripts/appinsights.ps1 for what Azure CLI command to execute to create the App Insights resource.

No matter which option you choose, recommend the user to create the App Insights resource in a meaningful resource group that makes managing resources easier. A good candidate will be the same resource group that contains the resources for the hosted app in Azure.

Modify application code

  • If the app is an ASP.NET Core app, see ASPNETCORE guide for how to modify the C# code.
  • If the app is a Node.js app, see NODEJS guide for how to modify the JavaScript/TypeScript code.
  • If the app is a Python app, see PYTHON guide for how to modify the Python code.

SDK Quick References

Platform-Specific Guides

來自 microsoft 的更多技能

oss-growth
microsoft
開源增長駭客角色
agent-framework-azure-ai-py
microsoft
使用Microsoft Agent Framework Python SDK(agent-framework-azure-ai)构建Azure AI Foundry代理。适用于使用AzureAIAgentsProvider创建持久化代理、使用托管工具(代码解释器、文件搜索、网络搜索)、集成MCP服务器、管理对话线程或实现流式响应。涵盖函数工具、结构化输出和多工具代理。
development
airunway-aks-setup
microsoft
在AKS上設定AI Runway——從裸叢集到執行模型。涵蓋叢集驗證、控制器安裝、GPU評估、供應商設定及首次部署。時機:「設定AI Runway」、「上線AKS叢集」、「安裝AI Runway」、「airunway設定」、「部署模型至AKS」、「在AKS上進行GPU推論」、「在AKS上設定KAITO」、「在AKS上執行LLM」、「在AKS上使用vLLM」、「在AKS上設定模型服務」、「AI Runway控制器」。
devops
applicationinsights-web-ts
microsoft
使用Application Insights JavaScript SDK(@microsoft/applicationinsights-web)為瀏覽器/Web應用程式進行檢測。適用於真實使用者監控(RUM)——頁面檢視、點擊、AJAX/fetch依賴、例外、自訂事件,以及與後端OpenTelemetry追蹤關聯的瀏覽器端GenAI代理追蹤。涵蓋SDK載入器指令碼與npm設定、框架擴充(React、React Native、Angular)、點擊分析、遙測初始化器,以及從瀏覽器發出的代理/工具/模型span的OTel GenAI語意慣例。
devops
azure-ai-anomalydetector-java
microsoft
使用適用於 Java 的 Azure AI 異常偵測器 SDK 建置異常偵測應用程式。在實作單變量/多變量異常偵測、時間序列分析或 AI 驅動監控時使用。
development
azure-ai-language-conversations-py
microsoft
使用 azure-ai-language-conversations Python SDK 實作對話語言理解(CLU)。當使用 ConversationAnalysisClient 分析對話意圖與實體、建置 NLP 功能,或將語言理解整合至應用程式時使用。
development
azure-ai-ml-py
microsoft
Azure Machine Learning SDK v2 for Python。用於機器學習工作區、作業、模型、資料集、計算資源與管線。 觸發詞:「azure-ai-ml」、「MLClient」、「workspace」、「model registry」、「training jobs」、「datasets」。
development
azure-ai-textanalytics-py
microsoft
Azure AI 文字分析 SDK,用於情感分析、實體辨識、關鍵片語、語言偵測、PII 與醫療保健 NLP。適用於文字的自然語言處理。 觸發詞:「文字分析」、「情感分析」、「實體辨識」、「關鍵片語」、「PII 偵測」、「TextAnalyticsClient」。
development