Great Stack to Doesn't Work #3 — Redis: "99% Cache Hit Ratio, System Down"
The article discusses the challenges faced when using Redis, particularly when it appears to function well but still causes system failures. It highlights the importance of understanding Redis's single-threaded nature and the impact of long-running commands on performance. Additionally, it provides tips on optimizing Redis usage, such as avoiding certain commands and utilizing pipelining and Lua scripting for better efficiency.
- ▪Redis can show a 99% cache hit ratio while still causing API failures due to long-running commands blocking the event loop.
- ▪Commands like KEYS and certain O(N) operations can stall the entire system, leading to significant performance issues.
- ▪Pipelining can reduce network latency by batching commands, but it does not ensure atomicity, which can be achieved using Lua scripts.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 2891163) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Mehmet TURAÇ Posted on May 30 Great Stack to Doesn't Work #3 — Redis: "99% Cache Hit Ratio, System Down" #redis #backend #devops #discuss Great Stack to Doesn't Work (4 Part Series) 1 Great Stack to Doesn't Work #1 — PostgreSQL: "I Added an Index and It Got Slower" 2 Great Stack to Doesn't Work #2 — Kafka: "Where Did My Messages Go?" 3 Great Stack to Doesn't Work Bonus: SQL vs NoSQL: Which One in 2026? 4 Great Stack to Doesn't Work #3 — Redis: "99% Cache Hit Ratio, System Down" A…
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