performance

Inserting thousands of records one-by-one is prohibitively slow due to the overhead of individual INSERT statements. The activerecord-import gem provides bulk insert capabilities that compile multiple records into a single multi-row INSERT, dramatical

Structured logs are great, but at high QPS they can become their own outage: too much IO, too much storage, and noisy dashboards. zap includes a sampler that allows you to keep early logs and then sample at a fixed rate. I like this for “successful re

Set a rough query budget per request in dev/test and alert when exceeded. This is a pragmatic way to keep performance regressions visible without requiring a full APM setup.

For Postgres search beyond trivial ILIKE, maintain a tsvector column and a GIN index. Update it via trigger or application logic. This keeps search fast and predictable even as your dataset grows.

Row-by-row inserts are painfully slow for big ingests. Postgres COPY is a great bulk-ingestion tool, and in Node you can stream into COPY using libraries like pg-copy-streams. The important part is validating before you stream, because once you’re in

Search inputs that fire API requests on every keystroke create poor UX and waste server resources. Debouncing delays the search until typing pauses, reducing requests dramatically. I combine a controlled input component with a custom useDebounce hook

React.memo prevents unnecessary re-renders of components when props haven't changed. I wrap components in memo when they're expensive to render or receive the same props frequently. The component only re-renders if props differ via shallow comparison.

I enable strict loading when I want N+1 bugs to fail loudly during development instead of quietly shipping to production. In Enable strict_loading on associations, I mark the relationships that routinely get iterated (has_many :line_items and belongs_

Rust's inline assembly (asm! macro) lets you write assembly for performance-critical code or to access hardware features. It's an unstable feature (nightly only) and requires unsafe. I use it sparingly for SIMD intrinsics not exposed by std::arch, cry

Properly configured connection pools prevent ActiveRecord::ConnectionTimeoutError during traffic spikes while avoiding resource waste. The pool size should match your application's concurrency needs—for Puma with 5 threads per worker, I set pool: 5 in