Files
stack/packages/mosaic/framework/skills/vercel-react-best-practices/rules/server-cache-lru.md
T
fargo 1a822493ba format: apply repo prettier (3.8.1) to the folded skills tree
963 markdown files reformatted with the repository's pinned prettier so
pnpm format:check covers the folded tree like every other repo file.

The formatter's embedded-language pass also normalized code fences
(TS semicolons, closed HTML tags in examples, lowercased CSS hex colors,
one renumbered list that skipped an index). Alphanumeric token deltas vs
the fold commit were audited file-by-file; all are formatter-equivalent
markup normalizations plus the four sanitized skills.
2026-08-19 14:37:17 -05:00

1.3 KiB

title, impact, impactDescription, tags
title impact impactDescription tags
Cross-Request LRU Caching HIGH caches across requests server, cache, lru, cross-request

Cross-Request LRU Caching

React.cache() only works within one request. For data shared across sequential requests (user clicks button A then button B), use an LRU cache.

Implementation:

import { LRUCache } from 'lru-cache';

const cache = new LRUCache<string, any>({
  max: 1000,
  ttl: 5 * 60 * 1000, // 5 minutes
});

export async function getUser(id: string) {
  const cached = cache.get(id);
  if (cached) return cached;

  const user = await db.user.findUnique({ where: { id } });
  cache.set(id, user);
  return user;
}

// Request 1: DB query, result cached
// Request 2: cache hit, no DB query

Use when sequential user actions hit multiple endpoints needing the same data within seconds.

With Vercel's Fluid Compute: LRU caching is especially effective because multiple concurrent requests can share the same function instance and cache. This means the cache persists across requests without needing external storage like Redis.

In traditional serverless: Each invocation runs in isolation, so consider Redis for cross-process caching.

Reference: https://github.com/isaacs/node-lru-cache