The Day the Garbage Collector Slowed Down a Real-Time Treasure Hunt
The article discusses the challenges faced while optimizing a real-time treasure hunt application built on Go. The team encountered latency issues due to garbage collection, prompting a switch to Rust for better memory management. Ultimately, the transition resulted in improved performance metrics and reduced memory usage.
- ▪The initial implementation of the treasure hunt application in Go struggled with latency due to garbage collection pauses.
- ▪After switching to Rust and implementing a custom allocator, the application achieved a p99 latency of 27 ms compared to 82 ms with Go.
- ▪The memory footprint was reduced from 140 MiB to 42 MiB, demonstrating significant efficiency gains.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3942594) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } pretty ncube Posted on May 27 The Day the Garbage Collector Slowed Down a Real-Time Treasure Hunt #webdev #programming #rust #performance The Problem We Were Actually Solving Last July we rolled out a new tier of Veltrix: real-time treasure hunts where users solve location-based puzzles in under 30 seconds. The backend is a state machine that ingests GPS pings, validates them against event geofences, and emits updated leaderboards every second.
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