Prometheus metrics in Node.js: prom-client library for monitoring

prom-client library: Monitoring Node.js applications with Prometheus

In modern web development, monitoring application performance and health has become a necessity. One of the most popular solutions for collecting and analyzing metrics is Prometheus — an open-source system that collects data in the form of time series. For integration with Node.js, there is an official library prom-client, which makes it easy to export metrics in a format understandable to Prometheus.

In this article, we will thoroughly examine how to install and use prom-client, what types of metrics are available, and how to integrate them with the Express web framework.

Installation and setup

First, install the library via npm:

npm install prom-client

After installation, import it into your application:

const prometheus = require('prom-client');const express = require('express');const app = express();

Main metric types

The prom-client library supports four main Prometheus metric types:

• Counter — a counter that only increases (e.g., number of requests).
• Gauge — a value that can both increase and decrease (e.g., number of active connections).
• Histogram — a histogram measuring value distribution (e.g., response time).
• Summary — summary statistics, similar to Histogram, but with more precise quantiles.

Example: Counter (request counter)

Let's create a counter to track the total number of HTTP requests:

const httpRequestsTotal = new prometheus.Counter({  name: 'http_requests_total',  help: 'Total number of HTTP requests',  labelNames: ['method', 'route', 'status']});

// Middleware for counting requestsapp.use((req, res, next) => {  res.on('finish', () => {    httpRequestsTotal.inc({      method: req.method,      route: req.path,      status: res.statusCode    });  });  next();});

Example: Gauge (active connections)

Gauge is convenient for tracking current state, for example, the number of active users:

const activeUsers = new prometheus.Gauge({  name: 'active_users',  help: 'Number of active users'});

app.get('/login', (req, res) => {  activeUsers.inc(); // Increase on login  res.send('Logged in');});

app.get('/logout', (req, res) => {  activeUsers.dec(); // Decrease on logout  res.send('Logged out');});

Example: Histogram (response time)

Histogram allows you to measure how long request processing takes:

const httpRequestDuration = new prometheus.Histogram({  name: 'http_request_duration_seconds',  help: 'Duration of HTTP requests in seconds',  labelNames: ['method', 'route'],  buckets: [0.1, 0.5, 1, 2, 5] // Bucket boundaries in seconds});

app.use((req, res, next) => {  const end = httpRequestDuration.startTimer();  res.on('finish', () => {    end({ method: req.method, route: req.path });  });  next();});

Exporting metrics for Prometheus

For Prometheus to collect data, you need to create an endpoint (usually /metrics) that returns all registered metrics:

app.get('/metrics', async (req, res) => {  res.set('Content-Type', prometheus.register.contentType);  res.end(await prometheus.register.metrics());});

app.listen(3000, () => {  console.log('Server running on port 3000');});

Custom metrics with labels

You can add labels for more detailed filtering. For example, let's split metrics by API versions:

const apiCalls = new prometheus.Counter({