Frontend Bundle Performance Analysis
Analyze JavaScript bundle size, identify heavy dependencies, and optimize for Core Web Vitals.
Overview
Large JavaScript bundles are the leading cause of poor Core Web Vitals scores. This workflow helps you analyze your bundle, identify the heaviest dependencies, and calculate the impact of optimization decisions.
Step-by-Step Implementation
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Quick Summary
JS bundle bloat is the #1 cause of poor LCP and INP scores. Visualize the bundle to find the heaviest modules, look up alternative packages with smaller footprints, and trim ruthlessly, every 100KB shaved is roughly 0.1s of LCP on a mid-range mobile device.
Key Takeaways
- Always profile compressed (gzip/brotli) size, minified-only numbers overstate real network cost by 2–3×.
- Common culprits: moment.js (replace with date-fns/Day.js), lodash full-import (use per-method), unused polyfills.
- Code splitting + lazy loading (`React.lazy`, `dynamic import()`) defers non-critical bundles to interaction time.
- Tree-shaking only works for ESM modules with no side effects, CommonJS dependencies often defeat it.
- Bundle size and runtime cost are different, a 5KB regex package can cost more CPU than a 50KB UI library.
When to use it
- Diagnosing why LCP is >2.5s despite the page looking simple.
- Justifying the cost of replacing a popular-but-heavy library (moment.js → date-fns).
- Auditing dependency creep after a year of feature work added incrementally.
- Setting bundle-size budgets in CI (`size-limit`, `bundlewatch`) to prevent silent regressions.
Common Mistakes
- Importing the entire library (`import _ from 'lodash'`) instead of named methods (`import map from 'lodash/map'`).
- Adding a 200KB date library for a single `formatDate()` call.
- Treating tree-shaking as automatic, many libraries (especially CommonJS ones) defeat it.
- Optimizing the bundle and ignoring the cost of runtime work (heavy hydration, large client state).
Frontend Bundle Performance Analysis, Frequently Asked
What's a good JS bundle-size budget for a marketing page?
Under 100KB (gzip) for first-load JS is excellent, under 200KB acceptable, over 500KB a problem. For SPAs: <300KB first-load is the realistic ceiling for good LCP.
Webpack vs Vite vs Turbopack for bundle analysis?
Vite (with `rollup-plugin-visualizer`) and Webpack (with `webpack-bundle-analyzer`) both produce great visualizations. Turbopack is faster for dev but its production analysis tooling is still maturing.
Does lazy loading hurt SEO?
Not if you're using SSR/SSG (Next.js, Astro, Remix), the initial render still has all critical content. CSR-only + lazy chunks can hurt SEO if Googlebot doesn't wait for the lazy modules.