Project 14: Performance Optimization Challenge

Performance directly affects user experience and business results. Slow sites lose users - Amazon found that every 100ms of delay costs 1% of sales. Learning optimization makes your applications competitive.

This project teaches you how to find and fix bottlenecks. Most developers can build features, but finding why something is slow requires different skills. You'll learn profiling, measuring, and data-driven optimization.

You'll understand the whole stack - database queries, server processing, network transfer, and browser rendering. Optimization requires knowing where time is spent so you can focus your efforts where they matter most.

Performance matters. Slow apps lose users. This project teaches you how to find bottlenecks and fix them. These skills are highly valued because they directly impact user experience and business success.

You'll learn to use profiling tools to measure performance. Guessing what's slow doesn't work - you need to measure. Then you'll learn specific techniques to make things faster.

This project covers both backend optimization (database queries, caching) and frontend optimization (bundle size, lazy loading). Real applications need both sides to be fast.

Take an intentionally slow application and optimize it using various techniques including database query optimization, caching strategies, lazy loading, code splitting, and CDN integration. Learn how to profile applications and make data-driven optimization decisions.

Use profiling tools to find performance issues

Optimize database queries effectively

Implement caching strategies correctly

Reduce bundle sizes and load times

Improve perceived performance

Measure performance improvements quantitatively

Database: Reduce query time from 2s to under 200ms

API: Reduce endpoint response from 1.5s to under 300ms

Frontend: Reduce bundle size from 1MB to under 300KB

Page Load: First Contentful Paint under 1.5s

Interactivity: Time to Interactive under 3s

Images: Lazy load below fold images

Add database indexes on frequently queried fields

Use query projections to select only needed fields

Implement Redis caching for hot data

Use database connection pooling

Enable gzip compression for responses

Optimize N+1 queries with proper joins or batching

Implement pagination for large result sets

Implement code splitting with React.lazy

Lazy load images with Intersection Observer

Use React.memo to prevent unnecessary rerenders

Debounce search and filter inputs

Virtualize long lists with react-window

Optimize images (WebP format, proper sizing)

Preload critical resources

Defer non-critical JavaScript

Use Chrome DevTools Performance tab

Run Lighthouse audits before and after

Profile database queries with explain()

Use React Profiler to find slow components

Monitor bundle size with webpack-bundle-analyzer

Track API response times with logging

Document all performance metrics

Create performance budget and stick to it

Implement cache invalidation strategy

Balance caching with data freshness

Optimize without breaking functionality

Set up monitoring to catch regressions

Make tradeoffs between optimization techniques

Database queries execute in under 200ms

API endpoints respond in under 300ms

Initial JavaScript bundle under 300KB

First Contentful Paint under 1.5s

Time to Interactive under 3s

Lighthouse score above 90

All optimizations documented with before/after metrics

Study Chrome DevTools performance profiling

Learn MongoDB explain() for query analysis

Research React performance optimization patterns

Explore web.dev for modern web performance

Look into Core Web Vitals metrics