Monitoring JavaScript Applications: Metrics and Alerts from A to Z

Monitoring JavaScript Applications: Metrics and Alerts from A to Z

In the modern development world, it is not enough to simply write working code. It is critically important to understand how your application behaves in a production environment. Monitoring JavaScript applications (especially on Node.js) is not just a trend, but a necessity. It allows you to identify bottlenecks, prevent failures, and ensure high service availability. In this article, we will cover the full cycle: from collecting key metrics to setting up alerts, using a modern stack of tools.

Why is Node.js Monitoring Important?

Node.js applications often operate asynchronously, processing thousands of requests per second. Without monitoring, you risk:

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• Missing a memory leak that could crash the server.
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• Not noticing an increase in response time (latency), which degrades the user experience.
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• Losing data due to unhandled errors.
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A monitoring system gives you visibility (observability) and allows you to make decisions based on data, not guesses.

Key Metrics for JavaScript Applications

All metrics can be divided into three groups: infrastructure, business metrics, and application metrics. Let's look at them in detail.

1. Infrastructure Metrics (USE Method)

These are basic server health indicators: CPU, memory, disk, network. For Node.js, memory (heap, non-heap) and the number of open file descriptors are especially important.

2. Application Metrics (RED Method)

The RED method (Rate, Errors, Duration) is the gold standard for microservices:

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• Rate: requests per second (RPS).
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• Errors: percentage of requests that resulted in an error (4xx, 5xx).
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• Duration: request execution time (p50, p95, p99 percentiles).
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3. Business Metrics

Specific to your product: number of registered users, completed orders, active sessions, etc.

Collecting Metrics with Prometheus and Node.js

Prometheus is the de facto standard for collecting metrics. For Node.js, we use the prom-client library. Let's look at a setup example.

Installation and Basic Setup

npm install prom-client express

Let's create a server with a /metrics endpoint:

const express = require('express');\nconst client = require('prom-client');\n\nconst app = express();\nconst port = 3000;\n\n// Create a metrics registry\nconst register = new client.Registry();\n\n// Add default Node.js metrics\nclient.collectDefaultMetrics({ register });\n\n// Create a custom histogram for response time\nconst httpRequestDuration = new client.Histogram({\n    name: 'http_request_duration_seconds',\n    help: 'Duration of HTTP requests in seconds',\n    labelNames: ['method', 'route', 'status'],\n    buckets: [0.01, 0.05, 0.1, 0.5, 1, 2, 5]\n});\nregister.registerMetric(httpRequestDuration);\n\n// Middleware for measuring time\napp.use((req, res, next) => {\n    const end = httpRequestDuration.startTimer();\n    res.on('finish', () => {\n        end({ method: req.method, route: req.route?.path || 'unknown', status: res.statusCode });\n    });\n    next();\n});\n\n// Endpoint for metrics\napp.get('/metrics', async (req, res) => {\n    res.set('Content-Type', register.contentType);\n    res.end(await register.metrics());\n});\n\napp.get('/', (req, res) => {\n    res.send('Hello, monitoring!');\n});\n\napp.listen(port, () => {\n    console.log(`App listening at http://localhost:${port}`);\n});

Custom Counters

Let's add an error counter:

const errorCounter = new client.Counter({\n    name: 'app_errors_total',