A good developer knows how to debug code. In fact, most software engineers spend the majority of their time debugging existing code rather than writing new code. When it comes to native app development, debugging and tracking errors during development can be a tricky task. So, in this post, I’ll help you understand how you can debug your React Native applications and also track errors during app development.
Do your cron jobs (aka scheduled jobs) ever fail or not run as expected? Scheduled jobs are supposed to be predictable – as the name implies. But as with many things, predictable!= reliable. Cron jobs fail too and we think you should know when that happens, Crons allows you to monitor the uptime and performance of any scheduled, recurring job in Sentry. Once set up, you’ll get alerts and metrics to help you solve errors, detect timeouts, and prevent disruptions to your service.
Performance testing is an important part of any application. It helps developers to increase the application reliability while providing a smooth user experience to the end users. However, when it comes to Unity projects, games and interactive applications have a higher requirement for performance compared to traditional applications.
The mobile development ecosystem has always been very diverse, arguably more diverse than the web development ecosystem. While it seems like every day there are more frameworks and tools for web developers, a lot of them are built on top of JavaScript and implement similar patterns to each other. The mobile ecosystem, on the other hand, has a core set of languages that make the differences between mobile tools and frameworks much easier to identify.
The fitness industry is no stranger to ‘smart’ equipment, and what distinguishes one product from another ultimately comes down to user experience. Product success depends on stability, something top of mind for developers at Tonal. Ranked as one of New York Magazine’s best smart home training solutions 2022 and Men’s Health’s best connected cable machine 2022, Tonal literally sets the bar for smart home trainers.
Errors are part of building software. Even if you are one of the fabled 10X engineers, errors are still going to happen. When an error does occur, typically you are going to look at the stack trace to understand the why and who for triaging. But figuring out who to assign an issue to just based on the stack trace can be difficult. How many times do you see a stack trace in a Sentry issue, head to GitHub, and try to figure out who changed the line of code in question? Often would be our guess.
Today Codecov is joining the Sentry family. Codecov began as a code coverage reporting tool in 2014 and has since emerged as a market leader in the test analytics space. Codecov makes coverage actionable for over two dozen test frameworks, and has helped over a million software developers improve their approach to testing, coverage, and code reliability. You might be asking, what do test analytics have to do with application monitoring?
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. You might have noticed a significant improvement in Sentry JavaScript stack traces recently. 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.
So you’re building a mobile app that’s performing big data requests; or crunching big data. But now you’re asking yourself: With Sentry’s Custom Instrumentation you can keep an eye on those big data-handling functions. Let’s see how you can implement them in your Storyboard and SwiftUI projects.
Profiling is an important tool in every developer’s toolkit because it provides a granular view into the execution of your program from your production environment. This is an important concept, as performance bottlenecks can often be very hard or even impossible to reproduce locally due to external constraints or loads only seen in a production environment.
