Today we’re announcing the first-ever solution for live debugging a CI/CD pipeline. You can now place stop/resume breakpoints and inspect live pipelines in the same way that developers debug their applications. It’s the easiest, fastest way to troubleshoot and fix bugs in complex pipelines. Live debugging is very well known to software developers and is one of the most efficient ways to find and fix bugs in application code.
Today, we’re releasing TrackJS Global Error Statistics to the public. This aggregated production data is a useful measure of the state of client-side JavaScript errors and the quality of the web. We break it down by the most common errors, browsers, and operating systems. We did this a few years ago with the State of Client-Side JavaScript Errors. It was quite useful, but very time consuming to produce.
.NET Profilers are a developer’s best friend when it comes to optimizing application performance. They are especially critical when doing low level CPU and memory optimizations. But did you know that there are three different types of profilers? All are very valuable but serve relatively different purposes and different types of performance profiling. Let’s explore the different types.
Debugging performance issues in production can be a pain and, in some cases, impossible without the right tools. Java profilers have been around forever, but the profilers most developers think about are only one type: standard JVM profilers. However, using one type of profiler is not enough. Suppose you’re analyzing your application’s performance. There are multiple profiling activities which you may execute.
It’s remarkable to me how many developers have no idea what their time is worth. I speak with a lot of developers, and when I mention my work on TrackJS, I frequently hear “I could build that”. Yeah, you could. Observability tools aren’t rocket science. But you shouldn’t. Your time is too valuable to build better mousetraps. Your time is valuable and finite. Both to you and to your company.
In our Sentry for Data series, we explain precisely why Sentry is the perfect tool for your data team. The present post focuses on how we used Sentry to make debugging Apache Beam easier (and faster). Since its creation, Sentry has embraced a single vision: help all developer teams build the best software, faster. We want to give developers the information they need to resolve issues quickly, without having to dig through noisy log lines.
