When it comes to monitoring your Elixir application, it's challenging to make sense of the many metrics and statistics that you can read from the internals of the Erlang virtual machine. In this post, we'll be looking at the scheduler utilization metric in order to understand what it is, why we should monitor it, and how to monitor it.
When running and maintaining an application in a production environment, we want to feel confident about the behavior of the application and know when it isn’t working as expected. At the least, we want to track errors, monitor performance, and collect specific metrics throughout the application.
AppSignal users will immediately notice that we’ve updated our product navigation. The new navigation is simpler, cleaner, and improves usability for (power) users. Let’s dive into these changes, along with some background on our philosophy of designing for developers.
Our front-end JavaScript library has been updated with an easier way to add more metadata to front-end errors using the sendError and wrap helpers. Previously, sendError and wrap helpers only supported customizing tags and the namespace for the error. More information could be set on error spans if they were manually created, but now that type of information can be added to errors sent using these helpers.
Good news for Node.js developers using AppSignal: a new version of our Node.js library is available on npm with improved error tracking. We’ve added two new helpers to make your life easier as a Node.js developer. One helper allows you to track errors whenever you need to, no matter how many nested spans you have in your current context. The other lets you send an isolated error with no spans or context involved (for more information about spans, check out our docs).
In this post, we’ll show you what atoms are in Elixir, why you should monitor them, and how to do so with AppSignal. Let’s prevent your app from crashing with a pop up of an error such as.
If your application runs in a virtualized environment, there is a crucial metric you might not be aware of: CPU steal. In this post, we’ll explain what CPU steal is, how to monitor it, and what happens to your app when CPU steal is high.
In this article, you’ll learn how to capture error logs in your Cloudflare Workers application using AppSignal. We’ll build a simple workers project and integrate AppSignal’s code to collect the necessary metrics. We’ll also learn how to utilize AppSignal’s dashboard to analyze and track errors. Let’s get stuck in!
Since the launch of uptime monitoring, we have received a lot of positive feedback. There were also a couple of much-requested additional features that we hope to address in this huge update.
Good logging practices are crucial for monitoring and troubleshooting your Node.js servers. They help you track errors in the application, discover performance optimization opportunities, and carry out different kinds of analysis on the system (such as in the case of outages or security issues) to make critical product decisions. Even though logging is an essential aspect of building robust web applications, it’s often ignored or glossed over in discussions about development best practices.
