Rails Performance Optimization Resources

Slow Rails applications rarely have one universal fix. The bottleneck may be repeated Active Record queries, a PostgreSQL plan that no longer fits the data, expensive Ruby work, overloaded background jobs, excessive allocations, or time spent in an external service. Effective Rails performance optimization starts by measuring the affected workload and locating where the time or capacity is actually going.

This page collects my practical Ruby on Rails performance articles and case studies in one place. The lists below are generated from content tagged with both Ruby on Rails and Performance, so newly published material appears here automatically.

What these Rails performance resources cover

The technical guides explain how to investigate specific problems, including N+1 queries, PostgreSQL query plans, counting large datasets, and profiling Ruby call stacks. The case studies document changes made in real codebases, with the original bottleneck, implementation approach, validation method, and upstream source where the work is public.

Use the guides when you are investigating the problem yourself. Use the case studies to see how similar issues were measured and corrected in existing applications. Results from one workload should not be treated as a promise for another: data shape, traffic, infrastructure, and application behavior all affect the outcome.

A reliable optimization process is straightforward even when the diagnosis is not: define one user-visible symptom, capture a comparable baseline, profile the complete path, implement the smallest well-supported change, and measure again. Query count, request latency, database execution time, queue latency, throughput, allocations, and memory are useful metrics only when they match the problem being solved.