performance

Large CSV exports should not allocate huge strings. Use ActionController::Live to stream rows. Include a heartbeat and handle client disconnects gracefully. This is real-world Rails ops code.

N+1 queries are the silent performance killer in Rails apps—they're easy to introduce during rapid development and expensive to diagnose in production. The Bullet gem monitors queries during development and test runs, raising alerts when it detects mi

Unbounded Promise.all is a great way to overload your DB (or a third-party API). I use a small concurrency limiter so I can process batches efficiently while keeping backpressure. This is especially useful for migrations, backfills, and webhook replay

Serializing complex ActiveRecord objects to JSON can consume significant CPU time, especially when rendering collections with nested associations. Fragment caching stores rendered JSON fragments in Redis keyed by a cache key that includes the record's

If you store flags/settings in JSONB, query performance hinges on indexing. Partial indexes are a great compromise: index only the rows that matter for the hot path (e.g., enabled flags).

The default http.Client is deceptively easy to misuse. I always set a request timeout (either via client.Timeout for simple cases or context.WithTimeout per request) and I tune the Transport so we reuse connections aggressively without leaking idle so

Android performance optimization ensures smooth 60fps UI and efficient resource usage. I use Android Profiler to monitor CPU, memory, network, and energy. Layout Inspector identifies overdraw and deep view hierarchies. Systrace captures system-level t

For high-throughput endpoints that serialize JSON or build strings repeatedly, allocations can become a real cost. sync.Pool is a pragmatic tool for reusing temporary buffers without manual free lists. The key is to treat pooled objects as ephemeral:

Turbo can preload pages on hover (or on touchstart) which makes navigation feel instantaneous. I use data-turbo-preload on links that are likely to be clicked (like list item titles). The server still controls caching and ETags, so it remains safe and

If you have a “top list” that’s expensive to compute, a materialized view is a clean approach. Refresh concurrently on a schedule to keep reads fast without blocking.

For pages with expensive secondary data (audit trail, related entities), keep initial render fast and lazy-load a details frame only when the user asks. This is a clean performance pattern for admin pages.

Performance work is hard when you’re guessing what’s in your bundle. The bundle analyzer turns it into a visual diff: you can see which dependencies are big and whether code splitting is working. I gate it behind an env var like ANALYZE=true so it’s o