Node.js Monitoring & Observability

Here’s a complete guide on Node.js Monitoring & Observability, covering tools, techniques, metrics, and best practices to keep your Node.js applications healthy in production.

🔍 Node.js Monitoring & Observability

Monitoring and observability ensure your Node.js applications are performant, reliable, and error-free in production.

  • Monitoring → Tracks metrics (CPU, memory, requests, errors).

  • Observability → Provides insights into app behavior (traces, logs, events).

1️⃣ Key Metrics to Monitor

Metric Why It Matters
CPU Usage Detects high computation or infinite loops
Memory Usage Detect memory leaks or excessive consumption
Event Loop Lag Measures responsiveness; delays indicate blocking code
Response Time Slow endpoints affect user experience
Request Rate Detect traffic spikes and load patterns
Error Rate High errors indicate app issues
Disk I/O Monitor database and file system performance
Uptime Ensure service availability

2️⃣ Built-in Node.js Monitoring Tools

2.1 Process Module



 

2.2 Event Loop Delay


 

3️⃣ Profiling & Performance Tools

3.1 Node.js Inspector

node --inspect app.js

  • Connect via Chrome DevTools

  • Debug memory leaks, CPU profiling

3.2 Clinic.js

npm install -g clinic
clinic doctor -- node app.js

  • Visualize CPU & event loop performance

  • Detect bottlenecks and memory leaks

4️⃣ Logging & Observability

Logging is a critical part of observability:

  • Use structured logging with Winston or Pino

  • Log:

    • Request/response times

    • Errors & exceptions

    • User actions/events

Example with Pino + Express:


 

5️⃣ Application Performance Monitoring (APM) Tools

Tool Features
New Relic Node.js monitoring, metrics, traces
Datadog Infrastructure + app metrics, dashboards
Elastic APM Open-source, integrates with Elasticsearch
Prometheus + Grafana Metrics collection + visualization
Sentry Error tracking & performance monitoring
PM2 Process manager with built-in monitoring

5.1 PM2 Monitoring

npm install pm2 -g
pm2 start app.js --name my-app
pm2 monit # Realtime monitoring of CPU, memory, and events

Features:

  • Cluster mode for CPU scaling

  • Process restarts on crash

  • Log aggregation

  • Metrics: CPU %, Memory usage

5.2 Prometheus + Grafana Example

  1. Install prom-client:

npm install prom-client

  1. Expose metrics:


 

  1. Grafana can visualize /metrics endpoint.

6️⃣ Tracing & Distributed Observability

  • For microservices, track requests across services using OpenTelemetry:

npm install @opentelemetry/api @opentelemetry/sdk-node

  • Allows:

    • Tracing HTTP requests

    • Correlating logs with traces

    • Finding performance bottlenecks

7️⃣ Error Tracking

  • Catch unhandled errors:


 

  • Use Sentry:

npm install @sentry/node
const Sentry = require('@sentry/node');
Sentry.init({ dsn: process.env.SENTRY_DSN });

8️⃣ Best Practices for Monitoring Node.js

  1. Monitor CPU, memory, event loop lag, and uptime

  2. Use structured logging for traceability

  3. Use PM2 or Docker for process management & monitoring

  4. Implement centralized logging (ELK, CloudWatch, Datadog)

  5. Track errors and performance with APM tools (New Relic, Sentry)

  6. Use Prometheus + Grafana for metrics visualization

  7. Implement tracing for microservices (OpenTelemetry)

  8. Monitor production environment variables, config, and secrets

9️⃣ Summary

Aspect Tools / Techniques
Logs Winston, Pino, Morgan
Metrics process.memoryUsage(), process.cpuUsage(), perf_hooks
Error Tracking Sentry, PM2, process.on()
APM New Relic, Datadog, Elastic APM
Visualizations Grafana + Prometheus
Tracing OpenTelemetry

Node.js observability ensures you detect issues early, improve performance, and maintain reliability in production.

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