Clever.fm is developing a platform to connect podcast listeners with community and content to make podcasting financially sustainable for creators. Our application provides features such as capturing moments, sharing snippets, and having discussions on podcast episodes.
The following guest post addresses how to improve your services’s performance with Sentry and other application profilers for Python. Check out this post to learn more about application profiling and Sentry’s upcoming mobile application profiling offering. We’re making intentional investments in performance monitoring to make sure we give you all the context to help you solve what’s urgent faster.=
Unless you stare at Sentry all day waiting for error or performance problems to pop up, chances are you rely on alerts to let you know when something breaks or slows down. There are two types of alerts you can set up: 1) Issue Alerts, which are tied to issues that meet predefined criteria, and 2) Metric Alerts, which trigger when error volume or performance metrics like apdex, latency, or throughput surpass a pre-defined threshold.
Monitoring performance in front-end applications is vital. It focuses on the areas of the application users experience. These areas are slow rendering or frame rate, network request errors, and unresponsive user experience. Your application’s users expect the experience of using the application to be fast, responsive, and smooth. In the first article of this series, we discussed some tips for optimizing your React Native application performance.
There are multiple factors including speed, performance, UI interactions, etc. which are critical to the success of your iOS application. Slow and unresponsive applications are despised by users, so it’s critical to thoroughly test before releasing to the public.
Welcome to the final article in this Unity series where we are developing a Unity game.
