dcaaef1011
Format: YYYY-MM-DD-description.md - 2026-01-19-infrastructure-deployment.md - 2026-01-19-backend-api-implementation.md (in progress) Co-Authored-By: Claude Sonnet 4.5 (1M context) <noreply@anthropic.com>
42 lines
1.3 KiB
Markdown
42 lines
1.3 KiB
Markdown
---
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title: Cross-Request LRU Caching
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impact: HIGH
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impactDescription: caches across requests
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tags: server, cache, lru, cross-request
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---
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## Cross-Request LRU Caching
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`React.cache()` only works within one request. For data shared across sequential requests (user clicks button A then button B), use an LRU cache.
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**Implementation:**
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```typescript
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import { LRUCache } from 'lru-cache'
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const cache = new LRUCache<string, any>({
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max: 1000,
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ttl: 5 * 60 * 1000 // 5 minutes
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})
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export async function getUser(id: string) {
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const cached = cache.get(id)
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if (cached) return cached
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const user = await db.user.findUnique({ where: { id } })
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cache.set(id, user)
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return user
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}
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// Request 1: DB query, result cached
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// Request 2: cache hit, no DB query
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```
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Use when sequential user actions hit multiple endpoints needing the same data within seconds.
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**With Vercel's [Fluid Compute](https://vercel.com/docs/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.
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**In traditional serverless:** Each invocation runs in isolation, so consider Redis for cross-process caching.
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Reference: [https://github.com/isaacs/node-lru-cache](https://github.com/isaacs/node-lru-cache)
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