Look-aside pattern vs Write-Through. LRU Eviction explained. Persistence trade-offs (RDB vs AOF). Single-threaded nature of Redis.
Fast by name. Partitioning around a Pivot. Why is it the standard library choice despite O(N²) worst case?
Tired of naming classes? Writing CSS directly inside HTML sounds ugly, but it became the world standard. Why?
Establishing TCP connection is expensive. Reuse it for multiple requests.
Why does my server crash? OS's desperate struggle to manage limited memory. War against Fragmentation.
Here's what I've come to understand after working through Redis in depth:
Redis is more than a cache. Data structure store, message broker, session manager, distributed lock... it's versatile.
No single correct caching strategy. Read-heavy? Cache-Aside. Consistency critical? Write-Through. Write performance matters? Write-Behind. Context-dependent.
Memory management is key. Proper LRU, LFU, TTL configuration ensures efficient memory usage.
RDB + AOF combination is best for persistence. RDB for fast backups, AOF for data safety.
Single-threading is a double-edged sword. Guarantees atomicity but O(N) commands freeze everything.
Always watch for Thundering Herd. Cache expiration can crash your DB. Use locking or early expiration.
Leverage data structures like Sorted Set and HyperLogLog. Solves problems like leaderboards and unique counting elegantly.
Need high availability? Use Sentinel or Cluster. But overkill for small projects.
Biggest takeaway from studying this: Redis saves systems when used correctly, complicates them when used wrong.
I hope this writeup helps someone working through the same questions.
