Top Tweets for #ConsistentHashing

Do you know how companies scale their cache for millions of users? Today I learned how caching + consistent hashing power large distributed systems. Key takeaways from the session: → Cache stores frequently accessed data in fast memory to avoid expensive DB queries. → Use Redis as a cache layer and apply read-through caching to fetch from DB only on cache miss. → Use TTL to avoid stale data and start with a “magic number” that can later be tuned using real usage data. → When cache storage is full, apply eviction strategies like LRU to remove less useful data. → To scale caching servers without huge data reshuffling, use consistent hashing, which keeps data movement minimal when servers are added or removed. System design lesson of the day: Good architecture is not about avoiding problems. It is about reducing their impact at scale. 🚀 #SytemDesign