Optimizing High-Volume REST APIs Using Redis Caching and Spring Boot (With Load Testing Code) (opens in new tab)

High-volume REST APIs can easily become bottlenecked by database access, leading to high latency and poor throughput. Even after optimizing SQL queries and adding indexes, a database call might take hundreds of milliseconds, still far slower than a competitor’s 50 ms response that leverages caching. In-memory caching offers orders of magnitude faster data access. Traditional databases measure response times in milliseconds, while Redis operations complete in microseconds. By storing frequentl...