Plurrrr

If you have a Python program that is currently running you may want to understand what the real-world performance profile of the code is. This program could be in a production environment or just on your local machine. You will want to understand where the running program spends its time and if any “hot spots” exist that should be investigated further for improvement. You may be dealing with a production system that is misbehaving and you may want to profile it in an unobtrusive way that doesn’t further impact production performance or require code modifications. What’s a good way to do this? This article will talk about py-spy, a tool that allows you to profile Python programs that are already running.

This post is for anyone interested in writing performant and safe applications in Rust quickly. It walks the reader through designing and implementing an HTTP Tunnel and basic, language-agnostic, principles of creating robust, scalable, observable, and evolvable network applications.