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Application Insights SDK

Free

Monitor web app performance and user interactions seamlessly.

by sickn3344.7k stars on sickn33/agentic-awesome-skills
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Updated Aug 10, 2026
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Free · Opens the source repo

What Application Insights SDK does

The Application Insights JavaScript SDK for TypeScript is designed to instrument browser and web applications, providing developers with tools for Real User Monitoring (RUM). This skill allows you to automatically collect telemetry data such as page views, clicks, AJAX requests, unhandled exceptions, and custom events. It also supports browser-side traces for GenAI agents, enabling you to correlate frontend activities with backend performance metrics. This makes it particularly useful for developers looking to gain insights into user interactions and application performance in real time.

By integrating the Application Insights SDK, developers can leverage features such as auto-collection of page views and AJAX dependencies, which simplifies the process of tracking user engagement. The SDK also includes plugins for popular frameworks like React and Angular, allowing for enhanced instrumentation tailored to specific application architectures. This means that whether you are building a single-page application or a more traditional web app, you can effectively monitor how users are interacting with your application and identify potential issues that may arise.

Before implementing this skill, it is advisable to review the current API patterns and ensure that you have the necessary setup in place. The SDK requires a connection string for initialization, which is sent in plaintext to the client. Therefore, it's crucial to use a separate Application Insights resource with local authentication enabled if you need to isolate browser telemetry from backend data. This focus on security and performance makes the Application Insights SDK a reliable choice for developers aiming to enhance their application's observability.

In summary, this skill is ideal for developers and designers who want to implement robust monitoring capabilities in their web applications. By utilizing the Application Insights JavaScript SDK, you can ensure that you have the necessary insights to improve user experience and application performance effectively.

When to use it

Use this skill when you need to instrument a web application for monitoring user interactions and performance metrics with minimal setup.

When not to use it

This skill is not suitable for server-side applications or environments where Node.js is the primary runtime, as it is specifically designed for browser-based monitoring.

What you can build with it

Tracking User Engagement

Implement the Application Insights SDK to monitor how users interact with your web application, capturing clicks and page views automatically.

Identifying Performance Issues

Use the SDK to track AJAX requests and response times, helping you pinpoint performance bottlenecks in your application.

Integrating with Frameworks

Leverage the SDK's plugins for React or Angular to enhance telemetry collection and better understand user behavior within your framework.

How to install Application Insights SDK

View source

1. Install with the skills CLI

npx skills add sickn33/agentic-awesome-skills/applicationinsights-web-ts --agent claude-code

2. Or install it manually

Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.

Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs

Inside SKILL.md

Written by sickn33

Application Insights JavaScript SDK (Web) for TypeScript

When to Use

Use this skill when you need instrument browser/web apps with the Application Insights JavaScript SDK (@microsoft/applicationinsights-web). Use for Real User Monitoring (RUM) — page views, clicks, AJAX/fetch dependencies, exceptions, custom events, and browser-side GenAI agent traces correlated to backend...

Real User Monitoring (RUM) for browser apps with @microsoft/applicationinsights-web. Auto-collects page views, AJAX/fetch dependencies, unhandled exceptions, and (with the Click Analytics plugin) clicks. Supports custom events, metrics, and GenAI agent traces that follow OpenTelemetry GenAI semantic conventions and correlate to backend spans via W3C Trace Context.

Distinct from azure-monitor-opentelemetry-ts, which is for Node.js server apps. This skill is for browser/web code (and React Native).

Before Implementation

Search microsoft-docs MCP for current API patterns:

  • Query: "Application Insights JavaScript SDK setup"
  • Query: "Application Insights JavaScript SDK configuration"
  • Query: "Application Insights JavaScript framework extensions React Angular"
  • Verify package version: npm view @microsoft/applicationinsights-web version

Packages

PackagePurpose
@microsoft/applicationinsights-webCore RUM SDK (page views, AJAX, exceptions).
@microsoft/applicationinsights-clickanalytics-jsAuto-collect click telemetry.
@microsoft/applicationinsights-react-jsReact plugin (router instrumentation, hooks, HOC, ErrorBoundary).
@microsoft/applicationinsights-react-nativeReact Native plugin (native crashes, sessions).
@microsoft/applicationinsights-angularplugin-jsAngular plugin (router events, ErrorHandler).
@microsoft/applicationinsights-debugplugin-jsDev-only telemetry inspector.
@microsoft/applicationinsights-perfmarkmeasure-jsUser Timing (performance.mark/measure) integration.

Installation

npm i --save @microsoft/applicationinsights-web
# Optional plugins (install only what you use):
npm i --save @microsoft/applicationinsights-clickanalytics-js
npm i --save @microsoft/applicationinsights-react-js @microsoft/applicationinsights-react-native @microsoft/applicationinsights-angularplugin-js

Typings ship with the package — no separate @types/... install needed.

Connection String

The browser SDK requires a connection string at init time. It ships in plaintext to clients — Microsoft Entra ID auth is not supported for browser telemetry. Use a separate App Insights resource with local auth enabled for browser RUM if you need to isolate it from backend telemetry.

# Vite / CRA / Next.js — expose to client via the public env prefix
VITE_APPINSIGHTS_CONNECTION_STRING="InstrumentationKey=...;IngestionEndpoint=https://...;LiveEndpoint=https://..."
NEXT_PUBLIC_APPINSIGHTS_CONNECTION_STRING="InstrumentationKey=..."

Quick Start (npm)

import { ApplicationInsights } from "@microsoft/applicationinsights-web";

export const appInsights = new ApplicationInsights({
  config: {
    connectionString: import.meta.env.VITE_APPINSIGHTS_CONNECTION_STRING,
    enableAutoRouteTracking: true,        // SPA route changes -> page views
    enableCorsCorrelation: true,          // propagate Request-Id / traceparent to cross-origin AJAX
    enableRequestHeaderTracking: true,
    enableResponseHeaderTracking: true,
    distributedTracingMode: 2,            // DistributedTracingModes.AI_AND_W3C — emit traceparent for backend correlation
    autoTrackPageVisitTime: true,
    disableFetchTracking: false,          // fetch() is auto-instrumented by default
    excludeRequestFromAutoTrackingPatterns: [/livemetrics\.azure\.com/i]
  }
});

appInsights.loadAppInsights();
appInsights.trackPageView();

Call loadAppInsights() exactly once, as early as possible (before user interactions you want tracked). Then trackPageView() for the initial load — when enableAutoRouteTracking is on, subsequent route changes are automatic.

Quick Start (SDK Loader Script)

Recommended when you want auto-updating SDK and zero build pipeline. Paste this as the first <script> in <head>:

<script type="text/javascript" src="https://js.monitor.azure.com/scripts/b/ai.3.gbl.min.js" crossorigin="anonymous"></script>
<script type="text/javascript">
  var appInsights = window.appInsights || function (cfg) {
    /* See: https://learn.microsoft.com/azure/azure-monitor/app/javascript-sdk
       Use the latest snippet from the Microsoft Learn page above — it includes
       backup-CDN failover (cr), SDK-load-failure reporting, and the queue shim
       so calls before SDK ready are not lost. */
  }({ src: "https://js.monitor.azure.com/scripts/b/ai.3.gbl.min.js",
      crossOrigin: "anonymous",
      cfg: { connectionString: "YOUR_CONNECTION_STRING" } });
</script>

Loader-only API (queued until SDK loads): trackEvent, trackPageView, trackException, trackTrace, trackDependencyData, trackMetric, trackPageViewPerformance, startTrackPage, stopTrackPage, startTrackEvent, stopTrackEvent, addTelemetryInitializer, setAuthenticatedUserContext, clearAuthenticatedUserContext, flush.

Core Tracking APIs

// Page views (SPAs that disable enableAutoRouteTracking)
appInsights.trackPageView({ name: "Checkout", uri: "/checkout", properties: { cartSize: 3 } });

// Custom events (user actions, business events)
appInsights.trackEvent({ name: "PurchaseCompleted" }, { orderId: "ord_123", amountUsd: 49.95 });

// Exceptions (caught errors)
try {
  await pay(order);
} catch (err) {
  appInsights.trackException({ exception: err as Error, severityLevel: 3, properties: { orderId: order.id } });
}

// Traces (logs, severity 0=Verbose, 1=Info, 2=Warning, 3=Error, 4=Critical)
appInsights.trackTrace({ message: "Cart hydrated from local storage", severityLevel: 1 });

// Custom metrics (numeric)
appInsights.trackMetric({ name: "checkout.duration_ms", average: 1234 });

// Dependencies (manually-tracked outbound calls — fetch/XHR are auto-tracked)
appInsights.trackDependencyData({
  id: crypto.randomUUID(),
  name: "GET /api/orders",
  duration: 87, success: true, responseCode: 200,
  data: "https://api.example.com/api/orders", target: "api.example.com", type: "Fetch"
});

// User identity (set ONCE per authenticated session — values are PII; do not pass emails)
appInsights.setAuthenticatedUserContext("user-id-123", "tenant-456", /*storeInCookie*/ true);
appInsights.clearAuthenticatedUserContext(); // on logout

// Force send before unload
appInsights.flush();

Telemetry Initializers (enrichment & filtering)

Run for every envelope before send. Return false to drop.

import type { ITelemetryItem } from "@microsoft/applicationinsights-web";

appInsights.addTelemetryInitializer((item: ITelemetryItem) => {
  item.tags ??= {};
  item.tags["ai.cloud.role"] = "web-shop";
  item.tags["ai.cloud.roleInstance"] = window.location.hostname;
  item.data ??= {};
  item.data["app.version"] = import.meta.env.VITE_APP_VERSION;
  item.data["app.build"] = import.meta.env.VITE_BUILD_SHA;

  // Drop noisy health-check page views
  if (item.baseType === "PageviewData" && item.baseData?.uri?.endsWith("/healthz")) return false;

  // Scrub query-string secrets
  if (item.baseData?.uri) {
    item.baseData.uri = item.baseData.uri.replace(/([?&](https://github.com/microsoft/skills/tree/main/.github/plugins/azure-sdk-typescript/skills/applicationinsights-web-ts/token|sig|key)=)[^&]+/gi, "$1REDACTED");
  }
});

Click Analytics

import { ClickAnalyticsPlugin } from "@microsoft/applicationinsights-clickanalytics-js";

const clickPlugin = new ClickAnalyticsPlugin();
const appInsights = new ApplicationInsights({
  config: {
    connectionString: import.meta.env.VITE_APPINSIGHTS_CONNECTION_STRING,
    extensions: [clickPlugin],
    extensionConfig: {
      [clickPlugin.identifier]: {
        autoCapture: true,
        dataTags: { useDefaultContentNameOrId: true, customDataPrefix: "data-ai-" },
        urlCollectHash: false,
        behaviorValidator: (b: string) => /^[a-z0-9_]+$/.test(b) ? b : ""
      }
    }
  }
});
appInsights.loadAppInsights();

Mark elements with data-ai-* attributes; clicks are emitted as Custom Events with parent-content metadata.

SPA Route Tracking

  • Built-in: set enableAutoRouteTracking: true. Hooks history.pushState/replaceState and popstate.
  • React Router: use @microsoft/applicationinsights-react-js withAITracking HOC (see references/framework-extensions.md).
  • Manual: call appInsights.trackPageView({ name, uri }) in your router's useEffect on route change. Disable enableAutoRouteTracking to avoid double counting.

Distributed Tracing (correlate to backend)

Set distributedTracingMode: 2 (DistributedTracingModes.AI_AND_W3C). The SDK adds traceparent (and legacy Request-Id) to outbound fetch/XHR. Backends instrumented with OpenTelemetry (e.g. @azure/monitor-opentelemetry) auto-link to the browser's operation_Id.

For cross-origin calls, also set enableCorsCorrelation: true and add the calling origin to the CORS exposed headers on the API.

GenAI Agent Traces (OTel semantic conventions)

When the browser invokes an AI agent (function-calling, tool-use, model calls direct from the client), emit App Insights Dependency telemetry whose attributes follow the OpenTelemetry GenAI semantic conventions so they are queryable alongside backend agent spans in App Insights / Log Analytics.

Set the opt-in env first so backend instrumentations agree on the same schema version:

OTEL_SEMCONV_STABILITY_OPT_IN=gen_ai_latest_experimental

Required attribute keys (use the OTel names verbatim)

Span / opRequired attributes
invoke_agent {agent.name}gen_ai.operation.name=invoke_agent, gen_ai.provider.name, gen_ai.agent.name, gen_ai.agent.id (when known)
create_agent {agent.name}gen_ai.operation.name=create_agent, gen_ai.provider.name, gen_ai.agent.name, gen_ai.request.model
chat {model}gen_ai.operation.name=chat, gen_ai.provider.name, gen_ai.request.model, gen_ai.response.model, gen_ai.usage.input_tokens, gen_ai.usage.output_tokens
execute_tool {tool.name}gen_ai.operation.name=execute_tool, gen_ai.tool.name, gen_ai.tool.type (function | extension | datastore), gen_ai.tool.call.id

gen_ai.provider.name well-known values: openai, azure.ai.openai, azure.ai.inference, anthropic, aws.bedrock, gcp.gemini, gcp.vertex_ai, cohere, mistral_ai, groq, deepseek, perplexity, x_ai, ibm.watsonx.ai.

Sensitive content opt-in. gen_ai.system_instructions, gen_ai.input.messages, gen_ai.output.messages, gen_ai.tool.call.arguments, gen_ai.tool.call.result are Opt-In by default. Gate them behind a runtime flag and avoid them in production unless you have approved data handling.

Pattern: invoke_agent + nested tool/model spans

import { ApplicationInsights, SeverityLevel } from "@microsoft/applicationinsights-web";

type GenAiAttrs = Record<string, string | number | boolean | undefined>;

function startGenAiSpan(name: string, attrs: GenAiAttrs) {
  const id = crypto.randomUUID();
  const start = performance.now();
  const baseProps: GenAiAttrs = { "gen_ai.span.id": id, ...attrs };
  return {
    end(success: boolean, extra: GenAiAttrs = {}, error?: Error) {
      const duration = Math.round(performance.now() - start);
      const properties = { ...baseProps, ...extra };
      appInsights.trackDependencyData({
        id, name, duration, success,
        responseCode: error ? 500 : 200,
        type: "GenAI",
        target: String(attrs["gen_ai.provider.name"] ?? "genai"),
        properties: properties as Record<string, string>
      });
      if (error) {
        appInsights.trackException({
          exception: error,
          severityLevel: SeverityLevel.Error,
          properties: { ...properties, "error.type": error.name } as Record<string, string>
        });
      }
    }
  };
}

// Agent invocation
const agentSpan = startGenAiSpan("invoke_agent ResearchAssistant", {
  "gen_ai.operation.name": "invoke_agent",
  "gen_ai.provider.name": "azure.ai.openai",
  "gen_ai.agent.name": "ResearchAssistant",
  "gen_ai.agent.id": "asst_5j66UpCpwteGg4YSxUnt7lPY",
  "gen_ai.request.model": "gpt-4o-mini",
  "server.address": "myresource.openai.azure.com"
});

try {
  // Nested chat completion span
  const chat = startGenAiSpan("chat gpt-4o-mini", {
    "gen_ai.operation.name": "chat",
    "gen_ai.provider.name": "azure.ai.openai",
    "gen_ai.request.model": "gpt-4o-mini"
  });
  const res = await callAzureOpenAi(/* ... */);
  chat.end(true, {
    "gen_ai.response.model": res.model,
    "gen_ai.response.id": res.id,
    "gen_ai.response.finish_reasons": JSON.stringify(res.choices.map(c => c.finish_reason)),
    "gen_ai.usage.input_tokens": res.usage.prompt_tokens,
    "gen_ai.usage.output_tokens": res.usage.completion_tokens,
    "gen_ai.output.type": "text"
  });

  // Nested tool execution span
  const tool = startGenAiSpan("execute_tool getWeather", {
    "gen_ai.operation.name": "execute_tool",
    "gen_ai.tool.name": "getWeather",
    "gen_ai.tool.type": "function",
    "gen_ai.tool.call.id": "call_abc123"
  });
  const toolResult = await runGetWeather({ location: "SF" });
  tool.end(true);

  agentSpan.end(true, {
    "gen_ai.usage.input_tokens": res.usage.prompt_tokens,
    "gen_ai.usage.output_tokens": res.usage.completion_tokens
  });
} catch (err) {
  agentSpan.end(false, { "error.type": (err as Error).name }, err as Error);
}

The browser's traceparent is automatically attached to outbound fetch (when distributedTracingMode: 2), so downstream Azure OpenAI / agent backend spans hang under the same operation_Id in App Insights.

For the full attribute reference, well-known values, and content-capture guidance, see references/agent-traces.md.

KQL: query GenAI traces in App Insights

dependencies
| where type == "GenAI"
| extend op   = tostring(customDimensions["gen_ai.operation.name"]),
         agent = tostring(customDimensions["gen_ai.agent.name"]),
         model = tostring(customDimensions["gen_ai.request.model"]),
         tin   = toint(customDimensions["gen_ai.usage.input_tokens"]),
         tout  = toint(customDimensions["gen_ai.usage.output_tokens"])
| summarize calls=count(), p95_ms=percentile(duration, 95),
            avg_in=avg(tin), avg_out=avg(tout) by op, agent, model, bin(timestamp, 5m)

React (TypeScript)

See references/framework-extensions.md for full React, React Native, Angular, Next.js, and Vite recipes.

import { ApplicationInsights } from "@microsoft/applicationinsights-web";
import { ReactPlugin, withAITracking } from "@microsoft/applicationinsights-react-js";
import { createBrowserHistory } from "history";

const reactPlugin = new ReactPlugin();
const browserHistory = createBrowserHistory();

export const appInsights = new ApplicationInsights({
  config: {
    connectionString: import.meta.env.VITE_APPINSIGHTS_CONNECTION_STRING,
    extensions: [reactPlugin],
    extensionConfig: { [reactPlugin.identifier]: { history: browserHistory } }
  }
});
appInsights.loadAppInsights();

export const TrackedCheckout = withAITracking(reactPlugin, Checkout, "Checkout");

React Native

import { ApplicationInsights } from "@microsoft/applicationinsights-web";
import { ReactNativePlugin } from "@microsoft/applicationinsights-react-native";

const rnPlugin = new ReactNativePlugin();
const appInsights = new ApplicationInsights({
  config: {
    connectionString: process.env.EXPO_PUBLIC_APPINSIGHTS_CONNECTION_STRING,
    extensions: [rnPlugin],
    disableFetchTracking: false
  }
});
appInsights.loadAppInsights();

Performance — Web Vitals

Auto-collected: page-load timings via PerformanceTiming / PerformanceNavigationTiming. To add Core Web Vitals:

import { onCLS, onLCP, onINP, type Metric } from "web-vitals";

function send(m: Metric) {
  appInsights.trackMetric(
    { name: `web_vitals.${m.name.toLowerCase()}`, average: m.value },
    { rating: m.rating, navigationType: m.navigationType, id: m.id }
  );
}
onCLS(send); onLCP(send); onINP(send);

Cookies & Privacy

new ApplicationInsights({ config: {
  connectionString,
  isCookieUseDisabled: true,         // hard-disable all cookies
  cookieCfg: { enabled: true, domain: ".example.com", path: "/", expiry: 365 }
}});

To honor consent dynamically:

appInsights.getCookieMgr().setEnabled(userGaveConsent);
appInsights.config.disableTelemetry = !userGaveConsent;

Sampling

Server-side ingestion sampling (recommended) is configured on the App Insights resource. SDK-side sampling reduces network use:

new ApplicationInsights({ config: { connectionString, samplingPercentage: 50 } });

Per-type sampling via telemetry initializer: drop with return false based on item.baseType.

Offline / Send-on-Unload

The SDK uses sendBeacon (default onunloadDisableBeacon: false) to flush on pagehide / unload. For SPAs, also call appInsights.flush() before destructive transitions (logout, hard reload).

Common Pitfalls

  1. Do not initialize twice. Re-importing the module under different bundles produces duplicate page views. Use a single shared module export.
  2. Initialize before first user input to avoid losing early clicks/exceptions.
  3. Connection string is public — never reuse the same App Insights resource for backend secrets.
  4. enableAutoRouteTracking + manual trackPageView = duplicates. Pick one.
  5. CORS distributed tracing requires the API to allow Request-Id, Request-Context, traceparent, tracestate request headers and expose Request-Context response header.
  6. GenAI sensitive content (gen_ai.input.messages etc.) is Opt-In — never log without an explicit runtime flag and approved data handling.
  7. Agent token usage is on chat spans, not invoke_agent — copy aggregated usage to the parent agent span only if you know it.
  8. React StrictMode double-invokes effects in dev — guard loadAppInsights() with a module-level singleton.

Bundle Size

The full web SDK is ~110 KB minified (~36 KB gzipped). For aggressive budgets, use the Loader Script path so the SDK loads asynchronously off the critical path, or tree-shake unused plugins.

Key Types

import {
  ApplicationInsights,
  SeverityLevel,
  DistributedTracingModes,
  type IConfiguration,
  type IConfig,
  type ITelemetryItem,
  type ITelemetryPlugin,
  type ICustomProperties,
  type IPageViewTelemetry,
  type IEventTelemetry,
  type IExceptionTelemetry,
  type ITraceTelemetry,
  type IMetricTelemetry,
  type IDependencyTelemetry
} from "@microsoft/applicationinsights-web";

Best Practices

  1. One singleton instance exported from a single module.
  2. Initialize early in the app entrypoint, before router setup.
  3. Use telemetry initializers to attach app.version, tenantId, and to scrub PII / query-string secrets.
  4. Set distributedTracingMode: 2 and ensure your APIs accept/expose W3C trace context headers.
  5. For GenAI, follow OTel gen_ai.* attribute names verbatim — they are queryable across browser and backend telemetry uniformly.
  6. Gate sensitive content capture (gen_ai.input.messages / gen_ai.output.messages) behind a build-time or runtime opt-in.
  7. Flush on logout / sensitive navigation so in-flight telemetry isn't dropped.

References

Limitations

  • Use this skill only when the task clearly matches its upstream source and local project context.
  • Verify commands, generated code, dependencies, credentials, and external service behavior before applying changes.
  • Do not treat examples as a substitute for environment-specific tests, security review, or user approval for destructive or costly actions.

Frequently asked questions about Application Insights SDK

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