Comparing ETS and Redis for Performance Optimization

In this blog post, the author provides insight into the performance improvements achieved by profiling a system in production and identifying key bottlenecks. By utilizing Erlang's profiling tools and a Linux profiler called perf, the author was able to collect performance data without impacting live workloads. After analyzing the data, he discovered inefficiencies with the binary_to_term function and compared the performance of ETS and Redis. The results showed that switching to an ETS-based caching approach after optimizing yielded substantial CPU savings. The post includes detailed steps on data collection, analysis, and experimentation that led to these optimizations, highlighting the significant benefits of employing ETS for in-memory caching in certain scenarios.