Application Insights for Node.js

Azure Application Insights monitors your backend services and components after you deploy them to help you discover and rapidly diagnose performance and other issues. Add this SDK to your Node.js services to include deep info about Node.js processes and their external dependencies such as database and cache services. You can use this SDK for your Node.js services hosted anywhere: your datacenter, Azure VMs and Web Apps, and even other public clouds.

This library tracks the following out-of-the-box:

Incoming and outgoing HTTP requests
Important system metrics such as CPU usage
Unhandled exceptions
Events from many popular third-party libraries (see Automatic third-party instrumentation)

You can manually track more aspects of your app and system using the API described in the Track custom telemetry section.

Supported Node.JS versions

Platform Version	Supported
Node.JS `v15`	✅
Node.JS `v14`	✅
Node.JS `v12`	✅
Node.JS `v10`	✅
Node.JS `v8`	✅

Getting Started

Create an Application Insights resource in Azure by following these instructions.
Grab the Connection String from the resource you created in step 1. Later, you'll either add it to your app's environment variables or use it directly in your scripts.
Add the Application Insights Node.js SDK to your app's dependencies and package.json:
```
npm install --save applicationinsights
```
Note: If you're using TypeScript, please install @types/node package to prevent build issues, this npm package contains built-in typings.
As early as possible in your app's code, load the Application Insights package:
```
let appInsights = require('applicationinsights');
```
Configure the local SDK by calling appInsights.setup('YOUR_CONNECTION_STRING');, using the connection string you grabbed in step 2. Or put it in the APPLICATIONINSIGHTS_CONNECTION_STRING environment variable and call appInsights.setup() without parameters.

For more configuration options see below.
Finally, start automatically collecting and sending data by calling appInsights.start();.

Basic Usage

Important: applicationinsights must be setup and started before you import anything else. There may be resulting telemetry loss if other libraries are imported first.

For out-of-the-box collection of HTTP requests, popular third-party library events, unhandled exceptions, and system metrics:

let appInsights = require("applicationinsights");
appInsights.setup("YOUR_CONNECTION_STRING").start();

If the instrumentation key is set in the environment variable APPLICATIONINSIGHTS_CONNECTION_STRING, .setup() can be called with no arguments. This makes it easy to use different connection strings for different environments.

Load the Application Insights library (i.e. require("applicationinsights")) as early as possible in your scripts, before loading other packages. This is needed so that the Application Insights library can prepare later packages for tracking. If you encounter conflicts with other libraries doing similar preparation, try loading the Application Insights library after those.

Because of the way JavaScript handles callbacks, additional work is necessary to track a request across external dependencies and later callbacks. By default this additional tracking is enabled; disable it by calling setAutoDependencyCorrelation(false) as described in the Configuration section below.

Azure Functions

Due to how Azure Functions (and other FaaS services) handle incoming requests, they are not seen as http requests to the Node.js runtime. For this reason, Request -> Dependency correlelation will not work out of the box. To enable tracking here, you simply need to grab the context from your Function request handler, and wrap your Function with that context.

Setting up Auto-Correlation for Azure Functions

You do not need to make any changes to your existing Function logic. Instead, you can update the default export of your httpTrigger to be wrapped with some Application Insights logic:

...

// Default export wrapped with Application Insights FaaS context propagation
export default async function contextPropagatingHttpTrigger(context, req) {
    // Start an AI Correlation Context using the provided Function context
    const correlationContext = appInsights.startOperation(context, req);

    // Wrap the Function runtime with correlationContext
    return appInsights.wrapWithCorrelationContext(async () => {
        const startTime = Date.now(); // Start trackRequest timer

        // Run the Function
        await httpTrigger(context, req);

        // Track Request on completion
        appInsights.defaultClient.trackRequest({
            name: context.req.method + " " + context.req.url,
            resultCode: context.res.status,
            success: true,
            url: req.url,
            duration: Date.now() - startTime,
            id: correlationContext.operation.parentId,
        });
        appInsights.defaultClient.flush();
    }, correlationContext)();
};

Azure Functions Example

An example of making an axios call to https://httpbin.org and returning the reponse.

const appInsights = require("applicationinsights");
appInsights.setup("<YOUR_CONNECTION_STRING>")
    .setAutoCollectPerformance(false)
    .start();

const axios = require("axios");

/**
 * No changes required to your existing Function logic
 */
const httpTrigger = async function (context, req) {
    const response = await axios.get("https://httpbin.org/status/200");

    context.res = {
        status: response.status,
        body: response.statusText,
    };
};

// Default export wrapped with Application Insights FaaS context propagation
export default async function contextPropagatingHttpTrigger(context, req) {
    // Start an AI Correlation Context using the provided Function context
    const correlationContext = appInsights.startOperation(context, req);

    // Wrap the Function runtime with correlationContext
    return appInsights.wrapWithCorrelationContext(async () => {
        const startTime = Date.now(); // Start trackRequest timer

        // Run the Function
        await httpTrigger(context, req);

        // Track Request on completion
        appInsights.defaultClient.trackRequest({
            name: context.req.method + " " + context.req.url,
            resultCode: context.res.status,
            success: true,
            url: req.url,
            duration: Date.now() - startTime,
            id: correlationContext.operation.parentId,
        });
        appInsights.defaultClient.flush();
    }, correlationContext)();
};

Configuration

The appInsights object provides a number of methods to setup SDK behavior. They are listed in the following snippet with their default values.

let appInsights = require("applicationinsights");
appInsights.setup("<YOUR_CONNECTION_STRING>")
    .setAutoDependencyCorrelation(true)
    .setAutoCollectRequests(true)
    .setAutoCollectPerformance(true, true)
    .setAutoCollectExceptions(true)
    .setAutoCollectDependencies(true)
    .setAutoCollectConsole(true, false)
    .setUseDiskRetryCaching(true)
    .setAutoCollectPreAggregatedMetrics(true)
    .setSendLiveMetrics(false)
    .setAutoCollectHeartbeat(false)
    .setInternalLogging(false, true)
    .setDistributedTracingMode(appInsights.DistributedTracingModes.AI_AND_W3C)
    .start();

Please review their descriptions in your IDE's built-in type hinting, or applicationinsights.ts for detailed information on what these control, and optional secondary arguments.

Note that by default setAutoCollectConsole is configured to exclude calls to console.log (and other console methods). By default, only calls to supported third-party loggers (e.g. winston, bunyan) will be collected. You can change this behavior to include calls to console methods by using setAutoCollectConsole(true, true).

The TelemetryClient object contains a config property with many optional settings. These can be set as follows:

client.config.PROPERTYNAME = VALUE;

These properties are client specific, so you can configure appInsights.defaultClient separately from clients created with new appInsights.TelemetryClient().

Property	Description
instrumentationKey	Application Insights Instrumentation Key
endpointUrl	The ingestion endpoint to send telemetry payloads to
proxyHttpUrl	A proxy server for SDK HTTP traffic (Optional, Default pulled from `http_proxy` environment variable)
proxyHttpsUrl	A proxy server for SDK HTTPS traffic (Optional, Default pulled from `https_proxy` environment variable)
maxBatchSize	The maximum number of telemetry items to include in a payload to the ingestion endpoint (Default `250`)
maxBatchIntervalMs	The maximum amount of time to wait to for a payload to reach maxBatchSize (Default `15000`)
disableAppInsights	A flag indicating if telemetry transmission is disabled (Default `false`)
samplingPercentage	The percentage of telemetry items tracked that should be transmitted (Default `100`)
correlationIdRetryIntervalMs	The time to wait before retrying to retrieve the id for cross-component correlation (Default `30000`)
correlationHeaderExcludedDomains	A list of domains to exclude from cross-component correlation header injection (Default See Config.ts)
ignoreLegacyHeaders	Disable including legacy headers in outgoing requests, x-ms-request-id
distributedTracingMode	Sets the distributed tracing modes (Default=AI)
enableAutoCollectExternalLoggers	Sets the state of console. If true logger activity will be sent to Application Insights
enableAutoCollectConsole	Sets the state of logger tracking (enabled by default for third-party loggers only). If true, logger auto collection will include console.log calls (default false)
enableAutoCollectExceptions	Sets the state of exception tracking (enabled by default). If true uncaught exceptions will be sent to Application Insights
enableAutoCollectPerformance	Sets the state of performance tracking (enabled by default). If true performance counters will be collected every second and sent to Application Insights
enableAutoCollectExtendedMetrics	Sets the state of performance tracking (enabled by default). If true, extended metrics counters will be collected every minute and sent to Application Insights
enableAutoCollectPreAggregatedMetrics	Sets the state of pre aggregated metrics tracking (enabled by default). If true pre aggregated metrics will be collected every minute and sent to Application Insights
enableAutoCollectHeartbeat	Sets the state of request tracking (enabled by default). If true HeartBeat metric data will be collected every 15 minutes and sent to Application Insights
enableAutoCollectRequests	Sets the state of request tracking (enabled by default). If true requests will be sent to Application Insights
enableAutoCollectDependencies	Sets the state of dependency tracking (enabled by default). If true dependencies will be sent to Application Insights
enableAutoDependencyCorrelation	Sets the state of automatic dependency correlation (enabled by default). If true dependencies will be correlated with requests
enableUseAsyncHooks	Sets the state of automatic dependency correlation (enabled by default). If true, forces use of experimental async_hooks module to provide correlation. If false, instead uses only patching-based techniques. If left blank, the best option is chosen for you based on your version of Node.js.
enableUseDiskRetryCaching	If true events that occurred while client is offline will be cached on disk
enableResendInterval	The wait interval for resending cached events.
enableMaxBytesOnDisk	The maximum size (in bytes) that the created temporary directory for cache events can grow to, before caching is disabled.
enableInternalDebugLogging	Enables debug and warning logging for AppInsights itself. If true, enables debug logging
enableInternalWarningLogging	Enables debug and warning logging for AppInsights itself. If true, enables warning logging
enableSendLiveMetrics	Enables communication with Application Insights Live Metrics. If true, enables communication with the live metrics service
disableAllExtendedMetrics	Disable all environment variables set
extendedMetricDisablers	Disable individual environment variables set. `"extendedMetricDisablers": "..."`
noDiagnosticChannel	In order to track context across asynchronous calls, some changes are required in third party libraries such as mongodb and redis. By default ApplicationInsights will use diagnostic-channel-publishers to monkey-patch some of these libraries. This property is to disable the feature. Note that by setting this flag, events may no longer be correctly associated with the right operation.
noPatchModules	Disable individual monkey-patches. Set `noPatchModules` to a comma separated list of packages to disable. e.g. `"noPatchModules": "console,redis"` to avoid patching the console and redis packages. The following modules are available: `azuresdk, bunyan, console, mongodb, mongodb-core, mysql, redis, winston, pg`, and `pg-pool`. Visit the diagnostic-channel-publishers' README for information about exactly which versions of these packages are patched.
noHttpAgentKeepAlive	HTTPS without a passed in agent
httpAgent	An http.Agent to use for SDK HTTP traffic (Optional, Default undefined)
httpsAgent	An https.Agent to use for SDK HTTPS traffic (Optional, Default undefined)
aadTokenCredential	Azure Credential instance to be used to authenticate the App. AAD Identity Credential Classes

All these properties except httpAgent, httpsAgent and aadTokenCredential could be configured using configuration file applicationinsights.json located under root folder of applicationinsights package installation folder, Ex: node_modules/applicationinsights. These configuration values will be applied to all TelemetryClients created in the SDK.

{
    "samplingPercentage": 80,
    "enableAutoCollectExternalLoggers": true,
    "enableAutoCollectExceptions": true,
    "enableAutoCollectHeartbeat": true,
    "enableSendLiveMetrics": true,
    ...
}

Custom JSON file could be provided using APPLICATIONINSIGHTS_CONFIGURATION_FILE environment variable.

process.env.APPLICATIONINSIGHTS_CONFIGURATION_FILE = "C:/applicationinsights/config/customConfig.json"

// Application Insights SDK setup....

Sampling

By default, the SDK will send all collected data to the Application Insights service. If you collect a lot of data, you might want to enable sampling to reduce the amount of data sent. Set the samplingPercentage field on the Config object of a Client to accomplish this. Setting samplingPercentage to 100 (the default) means all data will be sent, and 0 means nothing will be sent.

If you are using automatic correlation, all data associated with a single request will be included or excluded as a unit.

Add code such as the following to enable sampling:

const appInsights = require("applicationinsights");
appInsights.setup("<YOUR_CONNECTION_STRING>");
appInsights.defaultClient.config.samplingPercentage = 33; // 33% of all telemetry will be sent to Application Insights
appInsights.start();

Multiple roles for multi-component applications

If your application consists of multiple components that you wish to instrument all with the same Instrumentation Key and still see these components as separate units in the Portal as if they were using separate Instrumentation Keys (for example, as separate nodes on the Application Map) you may need to manually configure the RoleName field to distinguish one component's telemetry from other components sending data to your Application Insights resource. (See Monitor multi-component applications with Application Insights (preview))

Use the following to set the RoleName field:

const appInsights = require("applicationinsights");
appInsights.setup("<YOUR_CONNECTION_STRING>");
appInsights.defaultClient.context.tags[appInsights.defaultClient.context.keys.cloudRole] = "MyRoleName";
appInsights.start();

If running in Azure App service or Azure functions the SDK will automatically populate the cloud role when following code is added:

const appInsights = require("applicationinsights");
appInsights.setup("<YOUR_CONNECTION_STRING>");
appInsights.defaultClient.setAutoPopulateAzureProperties(true);
appInsights.start();

Automatic third-party instrumentation

In order to track context across asynchronous calls, some changes are required in third party libraries such as mongodb and redis. By default ApplicationInsights will use diagnostic-channel-publishers to monkey-patch some of these libraries. This can be disabled by setting the APPLICATION_INSIGHTS_NO_DIAGNOSTIC_CHANNEL environment variable. Note that by setting that environment variable, events may no longer be correctly associated with the right operation. Individual monkey-patches can be disabled by setting the APPLICATION_INSIGHTS_NO_PATCH_MODULES environment variable to a comma separated list of packages to disable, e.g. APPLICATION_INSIGHTS_NO_PATCH_MODULES=console,redis to avoid patching the console and redis packages.

The following modules are available: azuresdk, bunyan, console, mongodb, mongodb-core, mysql, redis, winston, pg, and pg-pool. Visit the diagnostic-channel-publishers' README for information about exactly which versions of these packages are patched.

Automatic instrumentation for several Azure SDKs is also enabled, currently Cognitive Search, Communication Common and Cosmos DB SDKs are not supported. Javascript Azure SDKs

The bunyan, winston, and console patches will generate Application Insights Trace events based on whether setAutoCollectConsole is enabled. The rest will generate Application Insights Dependency events based on whether setAutoCollectDependencies is enabled. Make sure that applicationinsights is imported before any 3rd-party packages for them to be instrumented successfully.

Live Metrics

To enable sending live metrics of your app to Azure, use setSendLiveMetrics(true). Filtering of live metrics in the Portal is currently not supported.

Extended Metrics

Note: The ability to send extended native metrics was added in version 1.4.0

To enable sending extended native metrics of your app to Azure, simply install the separate native metrics package. The SDK will automatically load it when it is installed and start collecting Node.js native metrics.

npm install applicationinsights-native-metrics

Currently, the native metrics package performs autocollection of Garbage Collection CPU time, Event Loop ticks, and heap usage:

Garbage Collection: The amount of CPU time spent on each type of garbage collection, and how many occurrences of each type.
Event Loop: How many ticks occurred and how much CPU time was spent in total.
Heap vs Non-Heap: How much of your app's memory usage is in the heap or non-heap.

Distributed Tracing Modes

By default, this SDK will send headers understood by other applications/services instrumented with an Application Insights SDK. You can optionally enable sending/receiving of W3C Trace Context headers in addition to the existing AI headers, so you will not break correlation with any of your existing legacy services. Enabling W3C headers will allow your app to correlate with other services not instrumented with Application Insights, but do adopt this W3C standard.

const appInsights = require("applicationinsights");
appInsights
  .setup("<YOUR_CONNECTION_STRING>")
  .setDistributedTracingMode(appInsights.DistributedTracingModes.AI_AND_W3C)
  .start()

Track custom telemetry

You can track any request, event, metric or exception using the Application Insights client. Examples follow:

let appInsights = require("applicationinsights");
appInsights.setup().start(); // assuming connection string is in environment variables. start() can be omitted to disable any non-custom data
let client = appInsights.defaultClient;
client.trackEvent({name: "my custom event", properties: {customProperty: "custom property value"}});
client.trackException({exception: new Error("handled exceptions can be logged with this method")});
client.trackMetric({name: "custom metric", value: 3});
client.trackTrace({message: "trace message"});
client.trackDependency({target:"http://dbname", name:"select customers proc", data:"SELECT * FROM Customers", duration:231, resultCode:0, success: true, dependencyTypeName: "ZSQL"});
client.trackRequest({name:"GET /customers", url:"http://myserver/customers", duration:309, resultCode:200, success:true});
 
let http = require("http");
http.createServer( (req, res) => {
  client.trackNodeHttpRequest({request: req, response: res}); // Place at the beginning of your request handler
});

Note that custom properties are converted to their string representation before being sent, see Using properties for more information.

An example utility using trackMetric to measure how long event loop scheduling takes:

function startMeasuringEventLoop() {
  var startTime = process.hrtime();
  var sampleSum = 0;
  var sampleCount = 0;

  // Measure event loop scheduling delay
  setInterval(() => {
    var elapsed = process.hrtime(startTime);
    startTime = process.hrtime();
    sampleSum += elapsed[0] * 1e9 + elapsed[1];
    sampleCount++;
  }, 0);

  // Report custom metric every second
  setInterval(() => {
    var samples = sampleSum;
    var count = sampleCount;
    sampleSum = 0;
    sampleCount = 0;

    if (count > 0) {
      var avgNs = samples / count;
      var avgMs = Math.round(avgNs / 1e6);
      client.trackMetric({name: "Event Loop Delay", value: avgMs});
    }
  }, 1000);
}

Preprocess data with Telemetry Processors

public addTelemetryProcessor(telemetryProcessor: (envelope: Contracts.Envelope, context: { http.RequestOptions, http.ClientRequest, http.ClientResponse, Error, correlationContext }) => boolean)

You can process and filter collected data before it is sent for retention using Telemetry Processors. Telemetry processors are called one by one in the order they were added before the telemetry item is sent to the cloud.

If a telemetry processor returns false that telemetry item will not be sent.

All telemetry processors receive the telemetry data and its envelope to inspect and modify. They also receive a context object. The contents of this object is defined by the contextObjects parameter when calling a track method for manually tracked telemetry. For automatically collected telemetry, this object is filled with available request information and the persistent request context as provided by appInsights.getCorrelationContext() (if automatic dependency correlation is enabled).

The TypeScript type for a telemetry processor is:

telemetryProcessor: (envelope: ContractsModule.Contracts.Envelope, context: { http.RequestOptions, http.ClientRequest, http.ClientResponse, Error, correlationContext }) => boolean;

For example, a processor that removes stack trace data from exceptions might be written and added as follows:

function removeStackTraces ( envelope, context ) {
  if (envelope.data.baseType === "ExceptionData") {
    var data = envelope.data.baseData;
    if (data.exceptions && data.exceptions.length > 0) {
      for (var i = 0; i < data.exceptions.length; i++) {
        var exception = data.exceptions[i];
        exception.parsedStack = null;
        exception.hasFullStack = false;
      }
    }
    // Add extra properties
    var originalError = context["Error"];
    if(originalError && originalError.prop){
      data.properties = data.properties || {};
      data.properties.customProperty = originalError.prop;
    }
  }
  return true;
}

appInsights.defaultClient.addTelemetryProcessor(removeStackTraces);

More info on the telemetry API is available in the docs.

Use multiple Application Insights resources

You can create multiple Azure Application Insights resources and send different data to each by using their respective connection string. For example:

let appInsights = require("applicationinsights");

// configure auto-collection under one Connection String
appInsights.setup("<YOUR_CONNECTION_STRING>").start();

// track some events manually under another connection string
let otherClient = new appInsights.TelemetryClient("<YOUR_CONNECTION_STRING>");
otherClient.trackEvent({name: "my custom event"});

Examples

Track dependencies

let appInsights = require("applicationinsights");
let client = new appInsights.TelemetryClient();

var success = false;
let startTime = Date.now();
// execute dependency call here....
let duration = Date.now() - startTime;
success = true;

client.trackDependency({target:"http://dbname", name:"select customers proc", data:"SELECT * FROM Customers", duration:duration, resultCode:0, success: true, dependencyTypeName: "ZSQL"});

Assign custom properties to be included with all events

appInsights.defaultClient.commonProperties = {
  environment: process.env.SOME_ENV_VARIABLE
};

Manually track all HTTP GET requests

Note that all requests are tracked by default. To disable automatic collection, call .setAutoCollectRequests(false) before calling start().

appInsights.defaultClient.trackRequest({name:"GET /customers", url:"http://myserver/customers", duration:309, resultCode:200, success:true});

Alternatively you can track requests using trackNodeHttpRequest method:

var server = http.createServer((req, res) => {
  if ( req.method === "GET" ) {
      appInsights.defaultClient.trackNodeHttpRequest({request:req, response:res});
  }
  // other work here....
  res.end();
});

Track server startup time

let start = Date.now();
server.on("listening", () => {
  let duration = Date.now() - start;
  appInsights.defaultClient.trackMetric({name: "server startup time", value: duration});
});

Self-diagnostics

"Self-diagnostics" refers to internal logging from Application Insights Node.js SDK.

This functionality can be helpful for spotting and diagnosing issues with Application Insights itself.

By default, Application Insights Node.js SDK logs at warning level to console, following code demonstrate how to enable debug logging as well and generate telemetry for internal logs:

let appInsights = require("applicationinsights");
appInsights.setup("<YOUR_CONNECTION_STRING>")
    .setInternalLogging(true, true) // Enable both debug and warning logging
    .setAutoCollectConsole(true, true) // Generate Trace telemetry for winston/bunyan and console logs
    .start();

Logs could be put into local file using APPLICATIONINSIGHTS_LOG_DESTINATION environment variable, supported values are file and file+console, a file named applicationinsights.log will be generated on tmp folder by default, including all logs, /tmp for *nix and USERDIR/AppData/Local/Temp for Windows. Log directory could be configured using APPLICATIONINSIGHTS_LOGDIR environment variable.

process.env.APPLICATIONINSIGHTS_LOG_DESTINATION = "file";
process.env.APPLICATIONINSIGHTS_LOGDIR = "C:/applicationinsights/logs"

// Application Insights SDK setup....

Branches

Ongoing development takes place on the develop branch. Please submit pull requests to this branch.
Releases are merged to the master branch and published to npm.

Contributing

For details on contributing to this repository, see the contributing guide.

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.microsoft.com.

When you submit a pull request, a CLA-bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repositories using our CLA.

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact opencode@microsoft.com with any additional questions or comments.

@audc/applicationinsights

Application Insights for Node.js

Supported Node.JS versions

Getting Started

Basic Usage

Azure Functions

Setting up Auto-Correlation for Azure Functions

Azure Functions Example

Configuration

Sampling

Multiple roles for multi-component applications

Automatic third-party instrumentation

Live Metrics

Extended Metrics

Distributed Tracing Modes

Track custom telemetry

Preprocess data with Telemetry Processors

Use multiple Application Insights resources

Examples

Self-diagnostics

Branches

Contributing

Readme

Keywords

Package Sidebar

Install

Repository

Homepage

Weekly Downloads

Version

License

Unpacked Size

Total Files

Last publish

Collaborators

@audc/applicationinsights

Application Insights for Node.js

Supported Node.JS versions

Getting Started

Basic Usage

Azure Functions

Setting up Auto-Correlation for Azure Functions

Azure Functions Example

Configuration

Sampling

Multiple roles for multi-component applications

Automatic third-party instrumentation

Live Metrics

Extended Metrics

Distributed Tracing Modes

Track custom telemetry

Preprocess data with Telemetry Processors

Use multiple Application Insights resources

Examples

Self-diagnostics

Branches

Contributing

Readme

Keywords

Package Sidebar

Install

Repository

Homepage

DownloadsWeekly Downloads

Version

License

Unpacked Size

Total Files

Last publish

Collaborators

Weekly Downloads