Node.js is a powerful, fast, and lightweight runtime environment to build high-speed apps. But its event-driven and single-threaded nature can cause performance bottlenecks. As a result, issues like memory leaks, CPU congestion, and slow performance may appear. However, there are some methods by which you can take this optimization to the next level.
In this guide, we will talk about some popular methods to optimize a Node.js app’s performance, and for this, you don’t need to hire Node.js developers, as you can apply these settings on your own.
Let’s get started.
Before we get into performance optimization, let’s take a look at the core reason why a Node app’s performance may go down. This is not a drawback of the Node ecosystem, but it requires developers to understand its core nature. The very features that make it performant may turn into blockers if not optimized or used properly.
Node.js features an event-driven, single-threaded architecture, providing a high-performant environment for apps featuring real-time processing. Asynchronous programming is very popular today, and Node.js has this feature. But this dynamic nature can lead to memory leaks and CPU loads without appropriate monitoring.
Since it is hailed as a high-performing runtime environment, many developers downplay the importance of monitoring and optimization.
An effective optimization starts with proper monitoring, and how to perform effective monitoring; we will start with this, then move into the optimization guide.
A Multifaceted Node.js Performance Monitoring
Monitoring tools and methodology are constantly evolving so that developers can make this process smoother and faster than ever. As a result, every fortnight, new tools appear. Some of them are for complete app monitoring, and others can be used to monitor specific parts of an application, such as CPU utilization, memory usage, response time, etc.
You can build a strategy comprising manual and tool-based monitoring using popular tools. This will help you monitor the application comprehensively.
Begin this process by gathering metrics reflecting particular aspects of a system or process. The metrics could include:
CPU Utilization
The percentage of CPU resources used by your Node.js application.
Memory Usage
Tools and methods to check memory usage.
Response Time
Response time is how much time your application takes to respond to a request. If response time is high, it means the app is not properly optimized.
The acceptable response time depends on the type of application, but here are general benchmarks:
- < 100 ms – Excellent (ideal for real-time systems like games or trading platforms)
- 100–500 ms – Good (standard for most web applications)
- 500 ms–1 second – Acceptable, but may start to feel sluggish
- 1 second – Noticeably slow, may hurt user experience
- 2 seconds – Poor; users might abandon the app or site
For APIs, under 300 ms is generally considered good.
Database Queries Per Second
This shows how many queries are executed per second. High QPS means a load on your data server.
Error Rate
This will show issues that require your attention.
Besides, you can collect throughput, latency, event loop lag, garbage collection (GC) activity, uptime, active threads, and many others. With the help of popular Node.js monitoring tools, you can get these metrics.
Use built-in tools to monitor the app’s performance:
process.memoryUsage()to track heap and memory.- Log metrics
heapUsed,heapTotal, and external to identify memory leaks. - Use
perf_hooksto measure the execution time of any specific code block, and detailed performance metrics withperformance.now()orPerformanceObserver. - For loop delays, use
perf_hooks.monitorEventDelay.
Application Performance Monitoring (APM) Tools for Node.js Apps
There is an array of application monitoring tools (APM) available for programmers to keep track of Node applications. Below are some popular tools that you must use to collect performance-related data in your app:
- Dynatrace
- AppMetrics
- Datadog
- AppDynamics
- PM2
How to Optimize Node.js Performance
- Avoid using synchronous functions. You can replace code written in a synchronous manner with asynchronous counterparts. It will prevent event blocking.
- Choose appropriate data structures to reduce computational overhead.
- Group I/O operations. It will improve throughput.
- Leverage worker threads smartly for CPU-intensive tasks to free up the event loop.
- For memory leaks, use heap snapshots or tools like heapdump.
- Process large datasets, such as uploads and JSON parsing, with streams. It will reduce memory usage.
- Use compression techniques with Gzip or Brotli.
- Implement caching with Redis or in-memory stores.
- Use HTTP/2 with libraries like http2 for multiplexing and reducing latency.
- Use connection pools (e.g., pg-pool for PostgreSQL, mongoose for MongoDB) to manage database connections efficiently.
- Run multiple Node.js processes using the cluster module to utilize all CPU cores.
- You can use a load balancer for traffic distribution between two or more devices
- With tools like npm audit/snyk, you can spot vulnerable packages.
- If you have to find out the unused code, you can use webpack/rollup.
Final Words
In this article, we have provided a brief summary of performance monitoring in Node.js and offered a few tools and methods for improving the performance of a Node.js app. While this list is not exhaustive, you can use this information to ease the performance improvement process.
