Building scalable React applications in 2025

After years of building React applications for startups and enterprises alike, we've learned a few things about what works at scale — and what doesn't.

The problem with "just React"

React is excellent at what it does: building user interfaces. But a UI library alone doesn't give you:

• State management at scale — prop drilling quickly becomes unmanageable
• Data fetching patterns — useEffect spaghetti is real
• Code organization — "just put it in components" stops working at 100+ files
• Performance optimization — re-renders compound quickly

Architecture patterns that actually work

1. Feature-based folder structure

Stop organizing by file type. Start organizing by feature.

src/
├── features/
│   ├── auth/
│   │   ├── components/
│   │   ├── hooks/
│   │   ├── api/
│   │   └── index.ts
│   ├── dashboard/
│   └── settings/
├── shared/
│   ├── components/
│   ├── hooks/
│   └── utils/
└── app/

This pattern scales because:

• Related code lives together
• Features can be developed in isolation
• Dependencies between features are explicit

2. Server-first data fetching

With React Server Components and Next.js App Router, the paradigm has shifted. Fetch data on the server, stream to the client.

// app/dashboard/page.tsx
async function DashboardPage() {
  const data = await fetchDashboardData();
 
  return (
    <Suspense fallback={<DashboardSkeleton />}>
      <Dashboard data={data} />
    </Suspense>
  );
}

Benefits:

• No loading spinners for initial data
• Reduced JavaScript bundle size
• Better SEO out of the box

3. Strategic state management

Not everything needs to be global. We use a tiered approach:

The key insight: most "global state" is actually server cache.

Performance at scale

Measure first

Before optimizing, measure. We use:

• React DevTools Profiler for component-level performance
• Lighthouse for overall page performance
• Custom metrics in production (Core Web Vitals)

Common wins

1. Memoization — but only where profiling shows it helps
2. Code splitting — dynamic imports for heavy components
3. Image optimization — Next.js Image component, WebP format
4. Virtual lists — for large data sets (react-virtual)

Key takeaways

1. Organize by feature, not by type — your future self will thank you
2. Server-first data fetching — embrace React Server Components
3. Right-size your state management — most state is server cache
4. Measure before optimizing — intuition is often wrong

Want to discuss your React architecture? Get in touch — we love talking about this stuff.