performance-optimization

Optimizes application performance across frontend, backend, queries, and databases. Use when performance requirements exist, when you suspect performance regressions, when Core Web Vitals or load times need improvement, when N+1 query patterns need fixing, or when profiling reveals bottlenecks.

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name:performance-optimizationdescription:Optimizes application performance across frontend, backend, queries, and databases. Use when performance requirements exist, when you suspect performance regressions, when Core Web Vitals or load times need improvement, when N+1 query patterns need fixing, or when profiling reveals bottlenecks.

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

    MetricGoodNeeds ImprovementPoor
    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:

    SymptomLikely CauseInvestigation
    Slow LCPLarge images, render-blocking resources, slow serverCheck network waterfall, image sizes
    High CLSImages without dimensions, late-loading content, font shiftsCheck layout shift attribution
    Poor INPHeavy JavaScript on main thread, large DOM updatesCheck long tasks in Performance trace
    Slow initial loadLarge bundle, many network requestsCheck bundle size, code splitting

    Backend:

    SymptomLikely CauseInvestigation
    Slow API responsesN+1 queries, missing indexes, unoptimized queriesCheck database query log
    Memory growthLeaked references, unbounded caches, large payloadsHeap snapshot analysis
    CPU spikesSynchronous heavy computation, regex backtrackingCPU profiling
    High latencyMissing caching, redundant computation, network hopsTrace 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 && 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

    RationalizationReality
    "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)