In an ever-expanding world of microservices, APIs, and devices, maintaining an overview of application states and the myriad errors that can occur is challenging. For years, Sentry has been a go-to choice for developers to monitor their applications and receive notifications about issues within their code. Traditionally, Sentry was predominantly a Python shop, but they became one of the early adopters of Rust in their technology stack. They have been utilizing Rust for a few years now (since at least 2017), starting with sentry-cli, a command-line utility to work with Sentry, and continuing with their source map parsing pipeline, which reduced processing times from 20 seconds to less than 500 milliseconds. More recently, they have been developing two new projects in Rust: relay and symbolicator. Relay acts as a proxy for sending events to Sentry, while symbolicator is a service for handling the symbolication of stack traces. Both projects are open source and available on GitHub. Arpad Borsos (swatinem), Senior Native Platform Engineer at Sentry, sat down with me to discuss their journey with Rust and how it has enabled them to build a cutting-edge monitoring platform for large-scale applications. Our conversation covered topics such as 100x speedups, the Rust-Python interface, and the comparison between actor-based and task-based concurrency.
