It Was 2024 When We Tried to Outsmart the Treasure Hunt Engine
The article discusses the challenges faced by a team during a high-traffic game launch in 2024. They encountered significant performance issues due to a surge in concurrent users, which overwhelmed their database architecture. To address these issues, they implemented a caching layer to improve query performance while maintaining database integrity.
- ▪The team faced a 15× increase in traffic due to a viral TikTok clip, leading to database connection timeouts.
- ▪Initial attempts to scale the database connection pool and optimize queries failed to resolve the performance issues.
- ▪They ultimately decided to implement a read-through cache layer to handle search queries more efficiently.
Opening excerpt (first ~120 words) tap to expand
try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3942461) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Lillian Dube Posted on May 25 It Was 2024 When We Tried to Outsmart the Treasure Hunt Engine #webdev #programming #architecture #systems The Problem We Were Actually Solving We needed to survive the Black Friday of game launches without throwing hardware at the problem. The treasure hunt engine is peak write-amplification: every coin placement and every search query mutates state and then broadcasts an event to hundreds of listening clients.
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