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.

If you run an interactive website or application, JavaScript security is a top priority. There’s a huge array of things that can go wrong, from programmatic errors and insecure user inputs to malicious attacks. While JavaScript error monitoring can help you catch many of these issues, understanding common JavaScript security risks and following best practices is just as important.

Javascript execution analysis on dev environments is easy—just use Google Developer or some other free tools. However, getting the same level of analysis while your application is being used by a real user is much harder. You can’t possibly ask the end-user to help you troubleshoot. Even if you did, the user probably wouldn’t know what to do and they definitely wouldn’t be impressed by your organization.

This article was written by Nicolas Bohorquez and was originally published in The New Stack. Scroll below for the author’s picture and bio. Telegraf is the preferred way to collect data for InfluxDB. Though in some use cases, client libraries are better, such as when parsing a stream of server-side events. In this tutorial, you’ll learn how to read a data stream, store it as a time series into InfluxDB and run queries over the data using InfluxDB’s JavaScript client library.

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.

Here at Sentry, we like to dogfood our product as much as possible. Sometimes, it results in unusual applications of our product and sometimes these unusual applications pay off in a meaningful way. In this blog post, we’ll examine one such case where we use the Sentry JavaScript SDK to instrument Jest (which runs our frontend test suite) and how we addressed the issues that we found.

This series was co-written by Musa Barighzaai and Tyler Sullberg. In the previous post, we explored high-level differences between thinking in Clojure compared to thinking in JavaScript. We are now ready to start building our first Clojure microservice. The microservice we are going to build will be very simple. It will be an HTTP server that uses a Redis data store to count how many times a given IP address has pinged the /counter endpoint.

This series was co-written by Tyler Sullberg and Musa Barighzaai. This is the third and final post in a series of posts for JavaScript developers about how to set up Clojure microservices. The previous posts were: Those previous posts are useful context, but you can clone the repo and jump into this post without reading them.

This series was co-written by Tyler Sullberg and Musa Barighzaai. CircleCI is growing, which is wonderful. However, one of the growth challenges we have is that our backend is primarily written in Clojure, and few developers know Clojure. Many CircleCI engineers, including myself, have learned Clojure on the job. Before joining CircleCI, I was a JavaScript developer. As the lingua franca of software engineers, JavaScript is a relatively straightforward language to learn.