Robonito · SDE II, Engineering Team

Server Side Caching Mechanism

Implemented a server-side caching layer with Redis to reduce latency, improve response times, and serve accurate data through a carefully designed eviction policy.

The Challenge

Frequent reads were increasing server latency and placing unnecessary load on the backend, but the cache still had to return accurate data and avoid serving stale responses when underlying records changed.

Engineering Approach

Introduced a Redis-backed caching layer on the server side to keep frequently requested data close to the application.
Designed an eviction policy that balanced freshness, accuracy, and memory usage so cached values could be invalidated predictably.
Stored and reused high-traffic responses to reduce repeated computation and lower latency for common requests.
Aligned cache invalidation with data updates so the system continued to serve correct results after changes in the source of truth.

Impact

Reduced latency for repeated requests by serving data from Redis instead of recomputing it on every call.
Improved backend efficiency while maintaining accurate responses through a controlled eviction and invalidation strategy.