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We recently migrated JavaScript/SourceMap processing to Rust where we were hitting a lock contention problem in our processing infrastructure that kept people up for a few days. What happened, why and how did we solve it?

Knowing the user interactions which happened in your app right before it crashed is crucial context information for fixing errors. Tracking interactions like click and swipes manually can be tedious, so we at sentry looked into ways on how to do that automatically for your Jetpack Compose enabled Android app. Learn how you can intercept any touch event, how to determine Composable identifiers and ultimately how our sentry Android SDK ties it all together.

What is a self identifying file, what are debug IDs and why do we want a fundamental change in the web ecosystem for source maps.

Sentry is a very fast-moving company. In just one month we merged 165 pull requests from 19 authors and changed over 800 files, with a total of over 22,000 additions and almost 10,000 deletions. By updating to Lerna 6 with Nx caching, we were able to reduce our CI run times by about 35%.

With over 700 pull requests a month, making sure Sentry's test suite runs quicky is extremely important. This post will talk about our journey converting our component tests from Enzyme to React Testing Library that took almost 18 months, 17 engineers and almost 5000 tests.

Jetpack Compose, a new declarative UI toolkit by Google made for building native Android apps, is rapidly gaining traction. The main advantage of using Jetpack Compose is that it allows you to write UI code that is more concise and easier to understand. This leads to improved maintainability and reduced development time. The main advantage of using Jetpack Compose is that it allows you to write UI code that is more concise and easier to understand. This leads to improved maintainability and reduced development time.

The mobile development ecosystem has always been very diverse, arguably more diverse than the web development ecosystem. Both React Native and Flutter have a declarative approach from the start, but with Android and iOS now joining the declarative bandwagon, we can see that the future of mobile development is declarative.

Sentry helps every developer diagnose, fix, and optimize the performance of their code, and we need to deliver high quality stack traces in order to do so. In this blog post, we want to explain why source maps are insufficient for solving this problem, the challenges we faced, and how we eventually pulled it off by parsing JavaScript.

One of Sentries core company values is “for every developer”. We want to support every developer out there with our tools. But not every developer uses the newest or widely adopted tech stack, so we also try to support older versions of libraries and frameworks. To make sure that our SDK works correctly we have around 450 automated tests in our test suite that run for each change we make to the SDK.

Profilers measure the performance of a program at runtime by adding instrumentation to collect information about the frequency and duration of function calls. They are crucial tools for understanding the real-world performance characteristics of code and are often the first step in optimizing a program. In this post, we’ll walk through how we built Sentry’s iOS profiler, which is capable of collecting high quality profiling data from real user devices in production with minimal overhead.