This is where companies test whether you can build something that works fast for 10 users and also survives 1 million users.
Performance = speed
Scalability = growth without breaking
Let’s break this down properly.
✅ 5.1 Performance Optimization
🔹 1️⃣ Lazy Loading
Lazy loading means loading resources only when needed.
Instead of loading everything at once, load components dynamically.
Example (React):
const Dashboard = React.lazy(() => import("./Dashboard"));
This reduces initial bundle size.
Best for:
- Large dashboards
- Route-based pages
- Heavy components
🔹 2️⃣ Code Splitting
Breaking large JavaScript bundles into smaller chunks.
Without code splitting:
👉 One huge JS file
👉 Slow initial load
With code splitting:
👉 Load only what is needed
Most modern frameworks like React, Next.js, Vite support this automatically.
🔹 3️⃣ Tree Shaking
Tree shaking removes unused code during build time.
Example:
import { debounce } from "lodash";
Instead of importing entire lodash library.
Bundlers like:
- Webpack
- Vite
- Rollup
Automatically remove unused exports.
Important:
👉 Only works with ES Modules (import/export)
🔹 4️⃣ Bundle Optimization
Strategies:
- Remove unused dependencies
- Analyze bundle size (Webpack bundle analyzer)
- Use dynamic imports
- Avoid heavy libraries unnecessarily
- Compress images
Interview Tip:
If you can explain how to reduce bundle from 5MB to 1MB → strong impression.
🔹 5️⃣ Gzip / Brotli Compression
These compress files before sending to browser.
Without compression:
👉 1MB file sent fully
With compression:
👉 ~200KB transferred
Difference:
- Gzip → older, widely supported
- Brotli → better compression, modern browsers
Server config enables it.
🔹 6️⃣ CDN Usage
CDN = Content Delivery Network
Instead of serving files from one server:
👉 Files are distributed globally
User from Asia → nearest Asia server
User from US → nearest US server
Benefits:
- Faster load
- Reduced latency
- Better availability
Examples:
- Cloudflare
- AWS CloudFront
- Akamai
✅ 5.2 Handling Large Data
When data grows, naive solutions break.
🔹 1️⃣ Pagination
Instead of:
GET /products
Use:
GET /products?page=1&limit=10
Only fetch small chunk.
Best for:
- Admin dashboards
- Tables
- APIs
🔹 2️⃣ Infinite Scroll
Load more data when user scrolls down.
Example:
- Social media feeds
Uses:
- Scroll event
- Intersection Observer API
🔹 3️⃣ Virtual Scrolling (Very Important)
Rendering 10,000 DOM elements = slow.
Virtual scrolling renders only visible items.
Libraries:
- react-window
- react-virtualized
Example concept:
If screen shows 20 items → render only 20
Even if list has 50,000 items.
Huge performance improvement.
🔹 4️⃣ Debounce Search
Without debounce:
Every key press → API call
With debounce:
Wait 300ms before calling API.
Reduces:
- Server load
- API spam
- Rate limiting issues
🔹 5️⃣ Server-Side Filtering
Instead of:
fetch all products → filter in frontend
Do:
GET /products?category=electronics
Backend handles filtering.
Benefits:
- Less data transfer
- Faster frontend
- Better scalability
✅ 5.3 High Availability Concepts
This is more backend/system design oriented.
🔹 1️⃣ Horizontal Scaling
Two types of scaling:
Vertical Scaling
Increase server power:
- More RAM
- More CPU
Limit: hardware bound
Horizontal Scaling
Add more servers.
Instead of:
1 server handling 10k users
Use:
5 servers handling 2k each
More scalable.
🔹 2️⃣ Load Balancing
When multiple servers exist → need load balancer.
Load balancer:
- Distributes traffic evenly
- Prevents overload
- Detects failed servers
Flow:
User → Load Balancer → Server A/B/C
Common tools:
- Nginx
- AWS ELB
- HAProxy
🔹 3️⃣ Caching
Caching reduces repeated computation.
Types of Caching
1️⃣ Browser Cache
Static assets stored locally.
2️⃣ CDN Cache
Static content cached globally.
3️⃣ Server Cache
Store data in memory.
Example:
- Redis
- Memcached
4️⃣ Database Cache
Query result caching.
Why Caching Matters?
Without cache:
1000 users → 1000 DB queries
With cache:
1000 users → 1 DB query
Huge performance gain.
🧠 Interview-Level Thinking
They may ask:
❓ How would you handle 1 million users?
Strong answer:
- Use horizontal scaling
- Add load balancer
- Enable CDN
- Use caching (Redis)
- Optimize DB queries
- Use pagination
- Compress responses
- Monitor performance
❓ Why app is slow in production?
You should check:
- Bundle size
- Network waterfall
- API latency
- DB indexing
- Caching
- Memory leaks
🎯 Final Understanding
If you understand:
- Lazy loading & code splitting
- Compression & CDN
- Pagination & virtual scroll
- Horizontal scaling
- Load balancing
- Caching strategies
You are thinking beyond coding.
You are thinking like a system engineer.
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