Performance Optimization

Overview

Measure before optimizing. Performance work without measurement is guessing — and guessing leads to premature optimization that adds complexity without improving what matters. Profile first, identify the actual bottleneck, fix it, measure again. Optimize only what measurements prove matters.

When to Use

• Performance requirements exist in the spec (load time budgets, response time SLAs)

• Users or monitoring report slow behavior

• Core Web Vitals scores are below thresholds

• You suspect a change introduced a regression

• Building features that handle large datasets or high traffic

When NOT to use: Don't optimize before you have evidence of a problem. Premature optimization adds complexity that costs more than the performance it gains.

Core Web Vitals Targets

Metric

Good

Needs Improvement

Poor

LCP (Largest Contentful Paint)

≤ 2.5s

≤ 4.0s

4.0s

INP (Interaction to Next Paint)

≤ 200ms

≤ 500ms

500ms

CLS (Cumulative Layout Shift)

≤ 0.1

≤ 0.25

0.25

The Optimization Workflow

1. MEASURE  → Establish baseline with real data

2. IDENTIFY → Find the actual bottleneck (not assumed)

3. FIX      → Address the specific bottleneck

4. VERIFY   → Measure again, confirm improvement

5. GUARD    → Add monitoring or tests to prevent regression

Step 1: Measure

Two complementary approaches — use both:

• Synthetic (Lighthouse, DevTools Performance tab): Controlled conditions, reproducible. Best for CI regression detection and isolating specific issues.

• RUM (web-vitals library, CrUX): Real user data in real conditions. Required to validate that a fix actually improved user experience.

Frontend:

# Synthetic: Lighthouse in Chrome DevTools (or CI)

# Chrome DevTools → Performance tab → Record

# Chrome DevTools MCP → Performance trace

# RUM: Web Vitals library in code

import { onLCP, onINP, onCLS } from 'web-vitals';

onLCP(console.log);

onINP(console.log);

onCLS(console.log);

Backend:

# Response time logging

# Application Performance Monitoring (APM)

# Database query logging with timing

# Simple timing

console.time('db-query');

const result = await db.query(...);

console.timeEnd('db-query');

Where to Start Measuring

Use the symptom to decide what to measure first:

What is slow?

├── First page load

│   ├── Large bundle? --> Measure bundle size, check code splitting

│   ├── Slow server response? --> Measure TTFB in DevTools Network waterfall

│   │   ├── DNS long? --> Add dns-prefetch / preconnect for known origins

│   │   ├── TCP/TLS long? --> Enable HTTP/2, check edge deployment, keep-alive

│   │   └── Waiting (server) long? --> Profile backend, check queries and caching

│   └── Render-blocking resources? --> Check network waterfall for CSS/JS blocking

├── Interaction feels sluggish

│   ├── UI freezes on click? --> Profile main thread, look for long tasks (>50ms)

│   ├── Form input lag? --> Check re-renders, controlled component overhead

│   └── Animation jank? --> Check layout thrashing, forced reflows

├── Page after navigation

│   ├── Data loading? --> Measure API response times, check for waterfalls

│   └── Client rendering? --> Profile component render time, check for N+1 fetches

└── Backend / API

    ├── Single endpoint slow? --> Profile database queries, check indexes

    ├── All endpoints slow? --> Check connection pool, memory, CPU

    └── Intermittent slowness? --> Check for lock contention, GC pauses, external deps

Step 2: Identify the Bottleneck

Common bottlenecks by category:

Frontend:

Symptom

Likely Cause

Investigation

Slow LCP

Large images, render-blocking resources, slow server

Check network waterfall, image sizes

High CLS

Images without dimensions, late-loading content, font shifts

Check layout shift attribution

Poor INP

Heavy JavaScript on main thread, large DOM updates

Check long tasks in Performance trace

Slow initial load

Large bundle, many network requests

Check bundle size, code splitting

Backend:

Symptom

Likely Cause

Investigation

Slow API responses

N+1 queries, missing indexes, unoptimized queries

Check database query log

Memory growth

Leaked references, unbounded caches, large payloads

Heap snapshot analysis

CPU spikes

Synchronous heavy computation, regex backtracking

CPU profiling

High latency

Missing caching, redundant computation, network hops

Trace requests through the stack

Step 3: Fix Common Anti-Patterns

#### N+1 Queries (Backend)

// BAD: N+1 — one query per task for the owner

const tasks = await db.tasks.findMany();

for (const task of tasks) {

  task.owner = await db.users.findUnique({ where: { id: task.ownerId } });

}

// GOOD: Single query with join/include

const tasks = await db.tasks.findMany({

  include: { owner: true },

});

#### Unbounded Data Fetching

// BAD: Fetching all records

const allTasks = await db.tasks.findMany();

// GOOD: Paginated with limits

const tasks = await db.tasks.findMany({

  take: 20,

  skip: (page - 1) * 20,

  orderBy: { createdAt: 'desc' },

});

#### Missing Image Optimization (Frontend)

<!-- BAD: No dimensions, no format optimization -->

<img src="/hero.jpg" />

<!-- GOOD: Hero / LCP image — art direction + resolution switching, high priority -->

<!--

  Two techniques combined:

  - Art direction (media): different crop/composition per breakpoint

  - Resolution switching (srcset + sizes): right file size per screen density

-->

<picture>

  <!-- Mobile: portrait crop (8:10) -->

  <source

    media="(max-width: 767px)"

    srcset="/hero-mobile-400.avif 400w, /hero-mobile-800.avif 800w"

    sizes="100vw"

    width="800"

    height="1000"

    type="image/avif"

  />

  <source

    media="(max-width: 767px)"

    srcset="/hero-mobile-400.webp 400w, /hero-mobile-800.webp 800w"

    sizes="100vw"

    width="800"

    height="1000"

    type="image/webp"

  />

  <!-- Desktop: landscape crop (2:1) -->

  <source

    srcset="/hero-800.avif 800w, /hero-1200.avif 1200w, /hero-1600.avif 1600w"

    sizes="(max-width: 1200px) 100vw, 1200px"

    width="1200"

    height="600"

    type="image/avif"

  />

  <source

    srcset="/hero-800.webp 800w, /hero-1200.webp 1200w, /hero-1600.webp 1600w"

    sizes="(max-width: 1200px) 100vw, 1200px"

    width="1200"

    height="600"

    type="image/webp"

  />

  <img

    src="/hero-desktop.jpg"

    width="1200"

    height="600"

    fetchpriority="high"

    alt="Hero image description"

  />

</picture>

<!-- GOOD: Below-the-fold image — lazy loaded + async decoding -->

<img

  src="/content.webp"

  width="800"

  height="400"

  loading="lazy"

  decoding="async"

  alt="Content image description"

/>

#### Unnecessary Re-renders (React)

// BAD: Creates new object on every render, causing children to re-render

function TaskList() {

  return <TaskFilters options={{ sortBy: 'date', order: 'desc' }} />;

}

// GOOD: Stable reference

const DEFAULT_OPTIONS = { sortBy: 'date', order: 'desc' } as const;

function TaskList() {

  return <TaskFilters options={DEFAULT_OPTIONS} />;

}

// Use React.memo for expensive components

const TaskItem = React.memo(function TaskItem({ task }: Props) {

  return <div>{/* expensive render */}</div>;

});

// Use useMemo for expensive computations

function TaskStats({ tasks }: Props) {

  const stats = useMemo(() => calculateStats(tasks), [tasks]);

  return <div>{stats.completed} / {stats.total}</div>;

}

#### Large Bundle Size

// Modern bundlers (Vite, webpack 5+) handle named imports with tree-shaking automatically,

// provided the dependency ships ESM and is marked `sideEffects: false` in package.json.

// Profile before changing import styles — the real gains come from splitting and lazy loading.

// GOOD: Dynamic import for heavy, rarely-used features

const ChartLibrary = lazy(() => import('./ChartLibrary'));

// GOOD: Route-level code splitting wrapped in Suspense

const SettingsPage = lazy(() => import('./pages/Settings'));

function App() {

  return (

    <Suspense fallback={<Spinner />}>

      <SettingsPage />

    </Suspense>

  );

}

#### Missing Caching (Backend)

// Cache frequently-read, rarely-changed data

const CACHE_TTL = 5 * 60 * 1000; // 5 minutes

let cachedConfig: AppConfig | null = null;

let cacheExpiry = 0;

async function getAppConfig(): Promise<AppConfig> {

  if (cachedConfig &#x26;&#x26; Date.now() < cacheExpiry) {

    return cachedConfig;

  }

  cachedConfig = await db.config.findFirst();

  cacheExpiry = Date.now() + CACHE_TTL;

  return cachedConfig;

}

// HTTP caching headers for static assets

app.use('/static', express.static('public', {

  maxAge: '1y',           // Cache for 1 year

  immutable: true,        // Never revalidate (use content hashing in filenames)

}));

// Cache-Control for API responses

res.set('Cache-Control', 'public, max-age=300'); // 5 minutes

Performance Budget

Set budgets and enforce them:

JavaScript bundle: < 200KB gzipped (initial load)

CSS: < 50KB gzipped

Images: < 200KB per image (above the fold)

Fonts: < 100KB total

API response time: < 200ms (p95)

Time to Interactive: < 3.5s on 4G

Lighthouse Performance score: ≥ 90

Enforce in CI:

# Bundle size check

npx bundlesize --config bundlesize.config.json

# Lighthouse CI

npx lhci autorun

See Also

For detailed performance checklists, optimization commands, and anti-pattern reference, see references/performance-checklist.md.

Common Rationalizations

Rationalization

Reality

"We'll optimize later"

Performance debt compounds. Fix obvious anti-patterns now, defer micro-optimizations.

"It's fast on my machine"

Your machine isn't the user's. Profile on representative hardware and networks.

"This optimization is obvious"

If you didn't measure, you don't know. Profile first.

"Users won't notice 100ms"

Research shows 100ms delays impact conversion rates. Users notice more than you think.

"The framework handles performance"

Frameworks prevent some issues but can't fix N+1 queries or oversized bundles.

Red Flags

• Optimization without profiling data to justify it

• N+1 query patterns in data fetching

• List endpoints without pagination

• Images without dimensions, lazy loading, or responsive sizes

• Bundle size growing without review

• No performance monitoring in production

• React.memo and useMemo everywhere (overusing is as bad as underusing)

Verification

After any performance-related change:

• Before and after measurements exist (specific numbers)

• The specific bottleneck is identified and addressed

• Core Web Vitals are within "Good" thresholds

• Bundle size hasn't increased significantly

• No N+1 queries in new data fetching code

• Performance budget passes in CI (if configured)

• Existing tests still pass (optimization didn't break behavior)