Scalable Treasure Hunts Are a Myth, But We Almost Made One
The article discusses the challenges faced by a team attempting to scale their server infrastructure for a treasure hunt application. Initially, they focused on optimizing database queries, but this did not resolve their performance issues. Ultimately, they simplified their architecture, resulting in significant improvements in latency and CPU utilization.
- ▪The team realized their modular system was hindering performance due to excessive inter-component communication.
- ▪After changing to a single-threaded, in-memory cache design, they saw their average latency drop from 400ms to 50ms.
- ▪The new architecture allowed them to handle thousands of concurrent users more efficiently.
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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 23 Scalable Treasure Hunts Are a Myth, But We Almost Made One #webdev #programming #rust #performance The Problem We Were Actually Solving As it turns out, we weren't really solving the problem of scaling our server infrastructure, but rather the problem of our own internal architecture. Our team had designed the system to be modular, with various components communicating with each other over a complex network of message queues and HTTP requests.
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