rails

Sometimes exact counters aren’t worth the write cost. For high-traffic views, track increments in Redis and periodically aggregate into the DB. It’s an operational tradeoff that can dramatically reduce DB pressure.

Full reindexes can be long and fragile. Add checkpoints (last processed id), process in batches, and make it resumable. That turns a scary operation into a routine one.

Inventory systems are concurrency systems. Lock the row, verify available quantity, then write the reservation in the same transaction. It’s the simplest correct starting point.

Consistent error handling transforms debugging from guesswork into systematic troubleshooting. I use a rescue handler that catches exceptions globally and transforms them into a standard JSON structure containing an error code, human-readable message,

Eager loading associations with includes, preload, or eager_load is essential for avoiding N+1 queries that kill performance. When rendering a list of posts with their authors, Post.includes(:author) loads all authors in a second query rather than fir

With replicas, a user can create a record then immediately not see it due to replication lag. A simple mitigation is to pin subsequent reads to primary for a short window after writes.

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.

Undo is a great UX improvement for destructive actions. My approach is: on destroy, soft-delete the record (or keep enough data to restore), remove it from the list via turbo_stream.remove, and append a toast with an “Undo” link. Clicking “Undo” hits

Tags are user input, so normalize aggressively: downcase, strip, collapse whitespace, remove duplicates. Doing this at write time keeps search/filter logic clean and avoids messy edge cases.

Production debugging is about logs that are searchable. Emit JSON with consistent keys (requestid, memberid, duration). Even if you later add Lograge, this structure maps cleanly.

Rate limiting is essential protection against abuse and ensures fair resource distribution across API consumers. Rack::Attack with Redis backing provides a robust, shared state solution that works across multiple application servers. I define differen

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