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In this tutorial, we will go through a working example of a NestJS application auto-instrumented with OpenTelemetry. In our example we will use a simple application that outputs “Hello World!” when we call it in the browser. We will instrument this application with OpenTelemetry’s Node.js client library to generate trace data and send it to an OpenTelemetry Collector. The Collector will then export the trace data to an external distributed tracing analytics tool of our choice.

Debugging JavaScript is an inevitable part of web development, and not the nicest one. Debugging jobs always seem to pop up when you’re already buried under piles of work, and a teammate pings you about an issue that was overlooked in testing and has been causing frustrations since your last release. That’s why it helps to be prepared for that eventuality, and equipped with the developer tools to help you debug faster.

For those who aren’t that familiar with it, Electron is an open-source framework that allows developers to build cross-platform desktop applications in JavaScript. Some of the most popular desktop applications like VS Code, Slack, Discord, and Atom, are all built in Electron.

In our Configuring OpenTelemetry in Ruby blog post, we showed how to configure OpenTelemetry in a Ruby on Rails backend. In this post, we’ll cover how to configure OpenTelemetry in the front-end JavaScript in order to measure performance of browser and mobile devices and how to configure distributed tracing to work across the frontend and back end telemetry collection. Let’s dive in!

SDKs naturally increase in size over time. After all, it does take more bytes to implement more features. This is not a big deal for most languages—the relative size of each new feature is small, and load times and storage aren’t big concerns for code running on a server.

Choosing a JavaScript framework for a new project can be a daunting task. There’s always a new one getting hype from the community, while the established players still have a lot to offer. So you need to do your homework and make sure the framework you choose is the right one for your specific requirements. Popularity alone is never the best indicator, but a review of the most widely-used options should help you decide which way to go.

JavaScript mutators shine among the improvements in Sensu Go 6.5 – they are both more effective and more efficient at transforming Sensu event data than pipe mutators. This post explores the advantages of JavaScript mutators and includes an example, but first, a brief review. In the Sensu observability pipeline, checks generate events, which Sensu then filters, transforms, and processes. A mutator is a component that transforms the event data.