# Node.js > Get telemetry for your app in less than 5 minutes! --- This page will show you how to get started with OpenTelemetry in Node.js. You will learn how to instrument both [traces][] and [metrics][] and log them to the console. > [!NOTE] > > The logging library for OpenTelemetry for Node.js is still under development > hence an example for it is not provided below. For status details, see > [Status and Releases](/docs/languages/js/#status-and-releases). ## Prerequisites Ensure that you have the following installed locally: - [Node.js](https://nodejs.org/en/download/) - [TypeScript](https://www.typescriptlang.org/download), if you will be using TypeScript. ## Example Application The following example uses a basic [Express](https://expressjs.com/) application. If you are not using Express, that's OK — you can use OpenTelemetry JavaScript with other web frameworks as well, such as Koa and Nest.JS. For a complete list of libraries for supported frameworks, see the [registry](/ecosystem/registry/?component=instrumentation&language=js). For more elaborate examples, see [examples](/docs/languages/js/examples/). ### Dependencies To begin, set up an empty `package.json` in a new directory: ```shell npm init -y ``` Next, install Express dependencies.

npm install express @types/express
npm install -D tsx  # a tool to run TypeScript (.ts) files directly with node

npm install express

### Create and launch an HTTP Server Create a file named `app.ts` (or `app.js` if not using TypeScript) and add the following code to it:

/*app.ts*/
import express, { Express } from 'express';

const PORT: number = parseInt(process.env.PORT || '8080');
const app: Express = express();

function getRandomNumber(min: number, max: number) {
  return Math.floor(Math.random() * (max - min + 1) + min);
}

app.get('/rolldice', (req, res) => {
  res.send(getRandomNumber(1, 6).toString());
});

app.listen(PORT, () => {
  console.log(`Listening for requests on http://localhost:${PORT}`);
});

/*app.js*/
const express = require('express');

const PORT = parseInt(process.env.PORT || '8080');
const app = express();

function getRandomNumber(min, max) {
  return Math.floor(Math.random() * (max - min + 1) + min);
}

app.get('/rolldice', (req, res) => {
  res.send(getRandomNumber(1, 6).toString());
});

app.listen(PORT, () => {
  console.log(`Listening for requests on http://localhost:${PORT}`);
});

Run the application with the following command and open in your web browser to ensure it is working.

$ npx tsx app.ts
Listening for requests on http://localhost:8080

$ node app.js
Listening for requests on http://localhost:8080

## Instrumentation The following shows how to install, initialize, and run an application instrumented with OpenTelemetry. ### More Dependencies First, install the Node SDK and autoinstrumentations package. The Node SDK lets you initialize OpenTelemetry with several configuration defaults that are correct for the majority of use cases. The `auto-instrumentations-node` package installs instrumentation libraries that will automatically create spans corresponding to code called in libraries. In this case, it provides instrumentation for Express, letting the example app automatically create spans for each incoming request. ```shell npm install @opentelemetry/sdk-node \ @opentelemetry/api \ @opentelemetry/auto-instrumentations-node \ @opentelemetry/sdk-metrics \ @opentelemetry/sdk-trace-node ``` To find all autoinstrumentation modules, you can look at the [registry](/ecosystem/registry/?language=js&component=instrumentation). ### Setup The instrumentation setup and configuration must be run _before_ your application code. One tool commonly used for this task is the [--import](https://nodejs.org/api/cli.html#--importmodule) flag. Create a file named `instrumentation.ts` (or `instrumentation.mjs` if not using TypeScript), which will contain your instrumentation setup code. > [!NOTE] > > The following examples using `--import instrumentation.ts` (TypeScript) > require Node.js v.20 or later. If you are using Node.js v.18, please use the > JavaScript example.

/*instrumentation.ts*/
import { NodeSDK } from '@opentelemetry/sdk-node';
import { ConsoleSpanExporter } from '@opentelemetry/sdk-trace-node';
import { getNodeAutoInstrumentations } from '@opentelemetry/auto-instrumentations-node';
import {
  PeriodicExportingMetricReader,
  ConsoleMetricExporter,
} from '@opentelemetry/sdk-metrics';

const sdk = new NodeSDK({
  traceExporter: new ConsoleSpanExporter(),
  metricReader: new PeriodicExportingMetricReader({
    exporter: new ConsoleMetricExporter(),
  }),
  instrumentations: [getNodeAutoInstrumentations()],
});

sdk.start();

/*instrumentation.mjs*/
import { NodeSDK } from '@opentelemetry/sdk-node';
import { ConsoleSpanExporter } from '@opentelemetry/sdk-trace-node';
import { getNodeAutoInstrumentations } from '@opentelemetry/auto-instrumentations-node';
import {
  PeriodicExportingMetricReader,
  ConsoleMetricExporter,
} from '@opentelemetry/sdk-metrics';

const sdk = new NodeSDK({
  traceExporter: new ConsoleSpanExporter(),
  metricReader: new PeriodicExportingMetricReader({
    exporter: new ConsoleMetricExporter(),
  }),
  instrumentations: [getNodeAutoInstrumentations()],
});

sdk.start();

## Run the instrumented app Now you can run your application as you normally would, but you can use the `--import` flag to load the instrumentation before the application code. Make sure you don't have other conflicting `--import` or `--require` flags such as `--require @opentelemetry/auto-instrumentations-node/register` in your `NODE_OPTIONS` environment variable.

$ npx tsx --import ./instrumentation.ts app.ts
Listening for requests on http://localhost:8080

$ node --import ./instrumentation.mjs app.js
Listening for requests on http://localhost:8080

(Note: If your application is written in JavaScript as ECMAScript Modules (ESM), or compiled to ESM from TypeScript, then a loader hook is required to properly support instrumentation. Use `node --experimental-loader=@opentelemetry/instrumentation/hook.mjs --require ./instrumentation.js app.js`. See [ESM support docs](https://github.com/open-telemetry/opentelemetry-js/blob/main/doc/esm-support.md) for details on ESM support in OpenTelemetry.) Open in your web browser and reload the page a few times. After a while you should see the spans printed in the console by the `ConsoleSpanExporter`.

View example output

```js { resource: { attributes: { 'host.arch': 'arm64', 'host.id': '8FEBBC33-D6DA-57FC-8EF0-1A9C14B919F8', 'process.pid': 12460, // ... some resource attributes elided ... 'process.runtime.version': '22.17.1', 'process.runtime.name': 'nodejs', 'process.runtime.description': 'Node.js', 'telemetry.sdk.language': 'nodejs', 'telemetry.sdk.name': 'opentelemetry', 'telemetry.sdk.version': '2.0.1' } }, instrumentationScope: { name: '@opentelemetry/instrumentation-express', version: '0.52.0', schemaUrl: undefined }, traceId: '61e8960c349ca2a3a51289e050fd3b82', parentSpanContext: { traceId: '61e8960c349ca2a3a51289e050fd3b82', spanId: '631b666604f933bc', traceFlags: 1, traceState: undefined }, traceState: undefined, name: 'request handler - /rolldice', id: 'd8fcc05ac4f60c99', kind: 0, timestamp: 1755719307779000, duration: 2801.5, attributes: { 'http.route': '/rolldice', 'express.name': '/rolldice', 'express.type': 'request_handler' }, status: { code: 0 }, events: [], links: [] } { resource: { attributes: { 'host.arch': 'arm64', 'host.id': '8FEBBC33-D6DA-57FC-8EF0-1A9C14B919F8', 'process.pid': 12460, // ... some resource attributes elided ... 'process.runtime.version': '22.17.1', 'process.runtime.name': 'nodejs', 'process.runtime.description': 'Node.js', 'telemetry.sdk.language': 'nodejs', 'telemetry.sdk.name': 'opentelemetry', 'telemetry.sdk.version': '2.0.1' } }, instrumentationScope: { name: '@opentelemetry/instrumentation-http', version: '0.203.0', schemaUrl: undefined }, traceId: '61e8960c349ca2a3a51289e050fd3b82', parentSpanContext: undefined, traceState: undefined, name: 'GET /rolldice', id: '631b666604f933bc', kind: 1, timestamp: 1755719307777000, duration: 4705.75, attributes: { 'http.url': 'http://localhost:8080/rolldice', 'http.host': 'localhost:8080', 'net.host.name': 'localhost', 'http.method': 'GET', 'http.scheme': 'http', 'http.target': '/rolldice', 'http.user_agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10.15; rv:141.0) Gecko/20100101 Firefox/141.0', 'http.flavor': '1.1', 'net.transport': 'ip_tcp', 'net.host.ip': '::ffff:127.0.0.1', 'net.host.port': 8080, 'net.peer.ip': '::ffff:127.0.0.1', 'net.peer.port': 63067, 'http.status_code': 200, 'http.status_text': 'OK', 'http.route': '/rolldice' }, status: { code: 0 }, events: [], links: [] } ```

The generated span tracks the lifetime of a request to the `/rolldice` route. Send a few more requests to the endpoint. After a moment, you'll see metrics in the console output, such as the following:

View example output

```yaml { descriptor: { name: 'http.server.duration', type: 'HISTOGRAM', description: 'Measures the duration of inbound HTTP requests.', unit: 'ms', valueType: 1, advice: {} }, dataPointType: 0, dataPoints: [ { attributes: { 'http.scheme': 'http', 'http.method': 'GET', 'net.host.name': 'localhost', 'http.flavor': '1.1', 'http.status_code': 200, 'net.host.port': 8080, 'http.route': '/rolldice' }, startTime: [ 1755719307, 782000000 ], endTime: [ 1755719482, 940000000 ], value: { min: 1.439792, max: 5.775, sum: 15.370167, buckets: { boundaries: [ 0, 5, 10, 25, 50, 75, 100, 250, 500, 750, 1000, 2500, 5000, 7500, 10000 ], counts: [ 0, 5, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ] }, count: 6 } }, { attributes: { 'http.scheme': 'http', 'http.method': 'GET', 'net.host.name': 'localhost', 'http.flavor': '1.1', 'http.status_code': 304, 'net.host.port': 8080, 'http.route': '/rolldice' }, startTime: [ 1755719433, 609000000 ], endTime: [ 1755719482, 940000000 ], value: { min: 1.39575, max: 1.39575, sum: 1.39575, buckets: { boundaries: [ 0, 5, 10, 25, 50, 75, 100, 250, 500, 750, 1000, 2500, 5000, 7500, 10000 ], counts: [ 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ] }, count: 1 } } ] } { descriptor: { name: 'nodejs.eventloop.utilization', type: 'OBSERVABLE_GAUGE', description: 'Event loop utilization', unit: '1', valueType: 1, advice: {} }, dataPointType: 2, dataPoints: [ { attributes: {}, startTime: [ 1755719362, 939000000 ], endTime: [ 1755719482, 940000000 ], value: 0.00843049454565211 } ] } { descriptor: { name: 'v8js.gc.duration', type: 'HISTOGRAM', description: 'Garbage collection duration by kind, one of major, minor, incremental or weakcb.', unit: 's', valueType: 1, advice: { explicitBucketBoundaries: [ 0.01, 0.1, 1, 10 ] } }, dataPointType: 0, dataPoints: [ { attributes: { 'v8js.gc.type': 'minor' }, startTime: [ 1755719303, 5000000 ], endTime: [ 1755719482, 940000000 ], value: { min: 0.0005120840072631835, max: 0.0022552499771118163, sum: 0.006526499509811401, buckets: { boundaries: [ 0.01, 0.1, 1, 10 ], counts: [ 6, 0, 0, 0, 0 ] }, count: 6 } }, { attributes: { 'v8js.gc.type': 'incremental' }, startTime: [ 1755719310, 812000000 ], endTime: [ 1755719482, 940000000 ], value: { min: 0.0003403329849243164, max: 0.0012867081165313721, sum: 0.0016270411014556885, buckets: { boundaries: [ 0.01, 0.1, 1, 10 ], counts: [ 2, 0, 0, 0, 0 ] }, count: 2 } }, { attributes: { 'v8js.gc.type': 'major' }, startTime: [ 1755719310, 830000000 ], endTime: [ 1755719482, 940000000 ], value: { min: 0.0025888750553131105, max: 0.005744750022888183, sum: 0.008333625078201293, buckets: { boundaries: [ 0.01, 0.1, 1, 10 ], counts: [ 2, 0, 0, 0, 0 ] }, count: 2 } } ] } ```

## Next Steps Enrich your instrumentation generated automatically with [manual instrumentation](/docs/languages/js/instrumentation) of your own codebase. This gets you customized observability data. You'll also want to configure an appropriate exporter to [export your telemetry data](/docs/languages/js/exporters) to one or more telemetry backends. If you'd like to explore a more complex example, take a look at the [OpenTelemetry Demo](/docs/demo/), which includes the JavaScript based [Payment Service](/docs/demo/services/payment/) and the TypeScript based [Frontend Service](/docs/demo/services/frontend/). ## Troubleshooting Did something go wrong? You can enable diagnostic logging to validate that OpenTelemetry is initialized correctly:

/*instrumentation.ts*/
import { diag, DiagConsoleLogger, DiagLogLevel } from '@opentelemetry/api';

// For troubleshooting, set the log level to DiagLogLevel.DEBUG
diag.setLogger(new DiagConsoleLogger(), DiagLogLevel.INFO);

// const sdk = new NodeSDK({...

/*instrumentation.mjs*/
import { diag, DiagConsoleLogger, DiagLogLevel } from '@opentelemetry/api';

// For troubleshooting, set the log level to DiagLogLevel.DEBUG
diag.setLogger(new DiagConsoleLogger(), DiagLogLevel.INFO);

// const sdk = new NodeSDK({...

> [!NOTE] > > The OpenTelemetry documentation assumes that the compiled application is run > as [CommonJS](https://nodejs.org/api/modules.html#modules-commonjs-modules). > If the application runs as ESM, add the loader hook as specified in the > [ESM Support Doc](https://github.com/open-telemetry/opentelemetry-js/blob/main/doc/esm-support.md). {{__hugo_ctx/}} [traces]: /docs/concepts/signals/traces/ [metrics]: /docs/concepts/signals/metrics/