Regardless of the tech stack used, many developers have already used Redis or, at least, heard of it. Redis is specifically known for providing distributed caching mechanisms for cluster-based applications. While this is true, it’s not its only purpose. Redis is a powerful and versatile in-memory database. Powerful because it is incredibly super fast. Versatile because it can handle caching, database-like features, session management, real-time analytics, event streaming, etc.

Many teams take advantage of the convenience of deploying their apps to the platform as a service (PaaS) providers such as DigitalOcean. Cloud solutions like this are an easy way for teams to deploy and scale their applications without worrying about the details. However, even in these managed environments, poorly written apps can cause issues. If your pages load too slowly, users will likely leave your site and look for another.

What’s the most wanted feature for a Node.js application? Well, high performance with no downtime is one of the top answers for this question. But how do you accomplish this? Monitoring is key to gain a better understanding of the health of your application. For example, by implementing monitoring, you can detect problems, such as a memory leak or long-running processes that block the Node.js event loop.

When building a production application, you are usually on the lookout for ways to optimize its performance while keeping any possible trade-offs in mind. In this post, we’ll take a look at an approach that can give you a quick win when it comes to improving the way your Node.js apps handle the workload. An instance of Node.js runs in a single thread which means that on a multi-core system (which most computers are these days), not all cores will be utilized by the app.

Don’t you hate it when you see an uncaughtException error pop up and crash your Node.js app? Yeah… I feel you. Can anything be worse? Oh yeah, sorry, unhandledRejection I didn’t see you there. What a nightmare you are. 😬 I maintain all Node.js open-source repos at Sematext. A few of them can help you out with error handling, but more about that further down. Here at Sematext, we take error handling seriously! I want to share a bit of that today.

We just released a Magic Dashboard for Garbage Collection stats for our Node.js integration. If you are leaking memory, this dashboard will help you discover and fix this problem. No setting up is required, this dashboard will magically automatically appear among the rest of your dashboards. ✨

Building SaaS products is hard. Making customers happy is even harder. I should know, I’ve built a start-up that failed! But, not everything is that bad. I learned a lot. Now I maintain a few open-source Node.js projects at Sematext. It’s an observability SaaS. I joined to help make the log management features as good as they can be. If you’ve never heard that term before, my co-worker wrote a great introductory explanation of what Log Management is right here.

There is more to Distributed Tracing with Jaeger than just capturing machine data as with metrics, or tailing log files. To start, you should read this primer. In this article, I will walk you through the initial principles you’ll need before executing anything within your codebase. This is going to focus on Node.js, as slight differences and concerns exist for browser applications.

Monitoring for your Node.js apps can be hard. The tricky part is understanding what you need to monitor, instrumenting your code, and then making sense of all the data that’s been emitted. (That’s almost every part you might say 😅 ). At AppSignal, we dogfood our product and understand the pain users feel ourselves. The key points we focus on are the ease of use, flexibility, and developer experience.