Plenty of developers who start coding in Node.js do so because of how easy it is to get started.
But once you are ready to take your application to the next level, you need to take a step back. Why did you choose to build in Node.js, and where do you want to take your application from here?
Your “next level” may be a plunge to a production environment or introducing your business to a larger customer base. Whatever the case may be, you are now reading this post. This means you are at least vaguely aware of the concept of “performance monitoring”.
To scale your Node.js application, you need to figure out just how to use performance monitoring to your advantage.
Let’s start out by confronting some popular myths.
Node.js is not necessarily a fast or high-performing coding environment. It’s a programming environment built on top of JavaScript (a famously broken programming language) and V8, Google’s JavaScript engine built on C++. Despite the bells and whistles, JavaScript is technically an interpreted language, even though modern engines do compile to some extent. All of those layers already imply some compromise on performance.
Even more damning is the fact that Node.js is bound by JavaScript being a single-threaded language. By default, you cannot run multiple processes in parallel. If one function gets stuck in an endless loop, the application will start consuming more and more resources, leaving you with a costly memory leak. If you’re in production, that memory leak can cost you a user (or, worst case, even a paying customer!).
Node.js developers frequently find themselves at a crossroads. At a certain point, their application gets complex enough or the number of regular users gets large enough that just getting by on their code is no longer enough.
If you find yourself in this situation, you have three choices:
Unless you are trying to burn yourself and your business into the ground, only options 2 and 3 are realistic.
Option 2 is also probably not the best outcome. Switching your entire code base to a different language is extremely time-consuming. While there are definitely situations in which you gain more than you lose from switching to a more efficient language, most of you reading this guide are likely not there.
So, your only real path forward is option 3: learn better ways of scaling your application through data-informed performance improvements.
Great! Where do you start?
The world of performance monitoring is very overwhelming. You have your built-in tools within your chosen framework or with your cloud provider (Azure, AWS, etc.). You have the methods for logging and performance analysis within the Node.js environment itself. And then you have the wild west of third-party monitoring and analysis tools in all of their glory, from open-source to expensive, ranging in complexity from a simple hammer to a fusion-plasma-powered space bulldozer.
Set all of those tools aside for a moment. What are you even trying to accomplish with them? After all, performance monitoring & optimization in Node.js come down to a few key principles.
Understand where your application is not doing so well. Poor performance can mean crashes, frequent errors, memory leaks, inefficient CPU usage, or simply long processing times for functions.
Once you know where your application is performing badly, figure out why it’s not performing.
This is information that your cloud provider is probably not set up to help you with.
To isolate any performance issue to its root cause, you have to set up comprehensive logs and custom alerts. Do you know which functions are most critical? Monitor those. Is your application crashing in production but not in development? Get the data to figure out what the difference might be.
Now that you can pin down which parts of your application are causing problems and why those problems are occurring, begin resolving those problems by pushing updates to your code.
For instance, are the inefficiencies in your code CPU-intensive or I/O-intensive?
If you’re struggling with CPU usage, then you need to run worker threads to execute JavaScript threads in parallel at the same time.
But if you are trying to optimize I/O intensive functions, you need to better incorporate Node’s event loop functionality and built-in asynchronous operations.
The key performance metrics used by the biggest developers around the world (like those at Google) are:
Remember that an “error” on your log can be entirely different from an error as perceived by your user. For example, you can successfully resolve a request by throwing a 404 error page, but the person on the other end is still frustrated and unable to find what they were looking for.
Resource usage or resource saturation is important for 2 reasons:
When your application crashes, your users will act in one of two ways:
In either case, downtime is bad news for your development team.
If you don’t know what is happening within your application, you won’t know what to improve.
So start by setting up a comprehensive logging workflow.
First, your application should be regularly creating dump files as it runs in production. You can do that with the abort process or with heap methods.
Then, you should be recording and saving all the diagnostic reports and logs that your application generates across all of its environments and instances. Saving your logs to a dashboard that’s easy to access and read with all the essential information like error breakdown, recurrence, and root cause analysis in one place can speed up your debugging process quite significantly.
Flame graphs are a good way to determine which parts of your code are the most resource intensive and thus most likely to cause problems.
A flame graph visualizes how much CPU time is dedicated to each function of your code. Once you isolate those troublesome functions, you can further analyze if you should deploy asynchronous programming or other improvements.
To create a flame graph, you can simply follow instructions within Node.js directly or use a third-party tool for more detailed insights.
Once you have a sense of where your application performance is suffering, you should set up custom alerts.
While it’s easy to skip this step and default to generic alerts (especially if they are suggested by any of your tools), you have to customize alerts if you want them to be useful!
If your alerts aren’t configured, then your team may get spammed with false positives and important issues may get lost in the noise. Or you may have the opposite problem, failing to receive any alerts even for significant performance thresholds.
When monitoring your application, you should also remember to keep track of any security issues.
If your application is getting attacked, that malicious activity will show up in your performance metrics. Watch out for unusual volume of requests, sudden spikes in resource use, or other signs of cyber threats.
The best tool for monitoring your Node.js application is one that you can customize to give you all the insights you need.
As you’re assessing different options, ask yourself:
At Railtown.ai, we’ve designed an all-in-one debugging, monitoring, and logging tool for your Node.js projects.
Our AI-powered insights can help you discover the root cause for your performance issues in Node.js and resolve those issues quickly and efficiently. Get started for free today!
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