performance

Avoid writing rows when nothing changed—especially in batch jobs. Check changed? or compute the would-be update and skip if identical. This reduces bloat and autovacuum pressure.

Hotwire doesn’t replace caching—it makes it more valuable because you’re sending HTML frequently. I use fragment caching inside list partials and keep cache keys stable with cache blocks. The pattern is: cache each row by record, and cache the list wr

Spinners hide layout shifts and make an app feel slow even when it isn’t. Skeletons preserve layout and give users a sense of progress without jumping content around. I keep skeleton components simple and match the shape of the final UI. One practical

Synthetic performance tests don’t always match what real users experience. Web Vitals reporting gives you field data (CLS, LCP, INP, etc.). I collect vitals on the client and POST them to a lightweight endpoint, then aggregate on the backend. Sampling

Not every part of a page needs to load immediately. For heavy panels (analytics charts, audit logs), I use a Turbo Frame with src and a tiny Stimulus controller that sets the src when the element becomes visible via IntersectionObserver. This avoids f

GraphQL endpoints can be abused with huge queries that are expensive to parse and execute. Persisted queries let clients send a hash (e.g. sha256:...) instead of the full query, and the server only executes queries it recognizes. This reduces payload

When adding a new query path, run EXPLAIN in CI or a smoke task to catch missing indexes before production. You don’t need full query plans everywhere—just guard the hot paths.

Offset pagination falls apart as soon as rows are inserted or deleted between page fetches—users see duplicates or missing items. Cursor pagination fixes that with stable ordering and ‘seek’ queries. I use a compound cursor that includes both the prim

Offline-first is hard, but caching static assets is an easy win for repeat visits. I keep the service worker scope narrow and cache only versioned assets (hashed filenames) so I don’t accidentally serve stale HTML or API responses. The most common fai

Creating a new TCP/TLS connection for every request is slow and it adds load on both sides. For high-traffic services calling a small set of upstreams, keep-alive reduces latency and CPU dramatically. I configure an https.Agent with sensible maxSocket

Avoid loading whole records when you only need to know if something exists. exists? is good; for complex joins, a scoped select(1).limit(1) can be clearer and keeps the DB workload low.

GraphQL makes it very easy to accidentally create N+1 query explosions. DataLoader batches requests for the same resource during a single tick and gives you per-request caching. The trick is scoping: loaders must be per-request, not global singletons,