tomevault-io React Performance Patterns (Local/Docker)
From Vercel Engineering, optimized for local installs and Docker deployments.
Priority Categories
| Priority | Category | Impact | Key Pattern |
|---|---|---|---|
| 1 | Eliminating Waterfalls | CRITICAL | Promise.all(), Suspense |
| 2 | Bundle Size | CRITICAL | Direct imports, next/dynamic |
| 3 | Server-Side Performance | HIGH | React.cache, LRU caching |
| 4 | Client-Side Data | MEDIUM-HIGH | SWR dedup |
| 5 | Re-render Optimization | MEDIUM | Memoized subtrees, transitions |
| 6 | Rendering Performance | MEDIUM | content-visibility |
Critical Patterns
Eliminate Waterfalls (Priority 1)
// WRONG - sequential
const data1 = await fetchA();
const data2 = await fetchB();
// RIGHT - parallel
const [data1, data2] = await Promise.all([fetchA(), fetchB()]);
// RIGHT - stream slow data
<Suspense fallback={<Skeleton />}>
<SlowComponent />
</Suspense>
Reduce Bundle Size (Priority 2)
// WRONG - barrel import (pulls entire library)
import { FileText } from 'lucide-react';
// RIGHT - direct import
import FileText from 'lucide-react/dist/esm/icons/file-text';
// RIGHT - dynamic import for heavy components
import dynamic from 'next/dynamic';
const PDFViewer = dynamic(() => import('./PDFViewer'), { ssr: false });
Server Caching (Priority 3)
import { cache } from 'react';
const getData = cache(async (id: string) => await db.get(id));
Local/Docker Focus
- Optimize for cold-start and steady-state responsiveness over SEO
- Use in-process caches (server process persists)
- Avoid sequential awaits even for local APIs
- Defer non-critical work until after render
- Minimize RSC props to reduce hydration overhead
Full Reference
Complete guide: .claude/skills/react-patterns/SKILL.md
Condensed guide: .claude/skills/react-patterns/REACT_PATTERNS.md
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