Distributed tracing is essential to understanding and debugging a system, as it follows data moving both within and across process boundaries. If you’re just getting started with distributed tracing, our Introduction to Distributed Tracing is an excellent starting point. In this blog post, we’ll be looking at implementing distributed tracing between microservices via a message broker, all with open-source tools.
The Node.js/JavaScript ecosystem is the most popular in the world with more than 1 million packages hosted on npmjs.com. Also, the latest features of the language and the incredible work by the Node.js/V8/libuv teams ensures that Node.js runs everywhere with great performance. However, sometimes you might need something that is not offered by the runtime or the ecosystem, no matter how strong it is. For Sqreen, this situation arose when we set out to build our In-App WAF.
Debugging is the art of removing bugs — hopefully quickly, and in this guide, I’ll show you multiple ways to debug React. In terms of React, we can have many different kinds of bugs, including: There are more categories than this, but it’s enough to get started debugging in React. Let’s open by talking about how to create a small application using React and how to debug it.
When you need to troubleshoot an issue in your Node.js application, logs provide information about the severity of the problem, as well as insights into its root cause. You can use logs to capture stack traces and other types of activity, and trace them back to specific session IDs, user IDs, request endpoints—anything that will help you efficiently monitor your application.
In May, AWS announced the official launch of AWS Lambda support for the Node.js 10x runtime. While there were immediate concerns with the runtime, as detailed by Michael Hart at Bustle and others like Brian Leroux, the latest update appears to have solved many of the issues. Also announced in May, AWS Lambda has rolled out a new execution environment for AWS Lambda and the migration recently completed for all AWS Lambda functions on July 29th.
AWS Lambda is a service that confuses many people. For that reason, you may be wondering just how it works, and how you’d use it to build a highly scalable event-driven application. As someone who’s presumably no stranger to the internet, you must have seen the terms serverless, function-as-a-service, or AWS Lambda thrown across your screen a few times. Perhaps you’re looking to learn more. If so, you’re in luck.
The Node 10 release and the retiring of the Node 6 runtime created a debate around what you can expect from runtimes and from AWS. With that, came some criticism about AWS Lambda being too slow in adopting the Node LTS long-term support releases. However, shortly after the release, a bug was found in the Node 10 initial runtime which raised a question – should we give things a little bit of time to settle before rushing in and adopting them?
AWS has officially released the support for Node.js 10.x runtime in their AWS Lambda service. The Node.js 10.x runtime is available in all regions where Lambda is available. Node.js 10 (AKA “Dubnium”) is the official LTS version.
Node.js monitoring is a tricky task. There are certain challenges to look out for. Because Node.js is a dynamically typed programming language and single-threaded you give the interpreter and runtime a lot of freedom to make decisions. This can easily result in memory leaks and high CPU loads. Parallel execution is simulated in Node.js by using asynchronous execution of functions. But, if a single function blocks the thread or event queue, the application performance will take a huge hit.
What is the most important feature your Node.js application can have? Do you think it’s having fancy fuzzy logic for your full-text search, or maybe using sockets for real-time chats? You tell me. What’s the fanciest, most amazing and sexy feature you can add to your Node.js application?
