Why Database Utilization Remains High Despite Adding a Cache
By
Siddharth Pandey
Summary
This article explains why adding a cache in front of a database doesn't always solve high utilization problems. It argues that cache hit rate is not a configurable setting but emerges from the working set size relative to memory and the skewness of access patterns. The article introduces Paperstack, a free system design simulator that visualizes these dynamics by letting users sketch architectures and watch utilization metrics update live.
Source
bskyWhy Database Utilization Remains High Despite Adding a Cachecstu.ioKey quotes
· 3 pulledYou deployed a cache in front of your database three weeks ago. The DB is still running at 90% utilization.
Cache hit rate is not something you configure. It emerges from two things: how much of your working set fits in memory, and how skewed your access patterns are.
Paperstack is a free system design simulator that makes this visible. Sketch an architecture, press play, watch utilization numbers and node colors update live.
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