To us, dogfooding means using Sentry to improve Sentry. Here in this article, you’ll see how we used Performance to improve our search infrastructure. Recently, we extended our performance monitoring solution support to PHP and Serverless. We’re bringing it to Ruby and Java + Springboot soon too. But as some of you may have noticed, there’s also a new view in Performance, Trends. Trends shows you the most improved and regressed transactions in relation to releases.
To improve front-end performance in your application, it’s important to understand what kind of problems users are experiencing. They may be encountering slow load times, seeing unexpected shifts, or having trouble interacting with UI components. The question is, how bad is it? Is it perpetual-rage-click bad? Is it ditch-your-app bad? Is it rant-on-Twitter bad?
Sentry is excellent at capturing runtime errors in your applications. With the recent additions of performance monitoring and release health, it can further help as you build and ship code. Recently we used Sentry to ensure we didn’t break Sentry while doing a large refactor. When replacing an API or code path with a new implementation you’ll likely ‘deprecate’ the old path, but how do you know when that old path is finally not in use?
While Spring Boot provides everything developers need build applications, it leaves operational aspects of debugging issues to the developers and third-party services. If up until now all you had was log aggregation, where you can browse and filter through a web UI, prepare to have your mind blown with Sentry’s automatic error grouping, alerting, breadcrumbs, and much more. Sentry has recently launched a major update to the Java SDK. In the post, we’ll focus on Spring Boot and Logback.
Troubleshooting production issues in Lambda environments is often challenging. CloudWatch requires developers to comb through logs, search for relevant terms that they may not always know of and has hard-to-consume stack traces. For obvious reasons, we recommend using Sentry to instrument your Lambda Functions code in order to report error stack traces and associated debugging context. Here’s a walk through on how to instrument a Node function.
