Core Code
Core Code Modern Dev Handbook
REACT Contents
React Fundamentals
React Architecture Overview JSX and Rendering Model Component Design Principles Props and Data Flow State Management with useState Side Effects with useEffect Event Handling Patterns Conditional Rendering Strategies Lists, Keys, and Reconciliation Forms and Controlled Components Component Composition Lifting State and Shared State Basic Routing with React Router Failure Modes in Beginner React Apps
React + TypeScript
Typing Functional Components Typing Props and Children useState and Type Inference useReducer with Type Safety Typing Event Handlers Generic Components Utility Types in React Discriminated Unions for UI State Strict Mode and Null Safety API Response Typing Strategies Form Typing Patterns Avoiding any and Unsafe Casts Type-Safe Context API Failure Modes in React + TypeScript
React Advanced Patterns
Custom Hooks Architecture Context vs Prop Drilling Tradeoffs Compound Components Pattern Controlled vs Uncontrolled Abstractions Render Props and Pattern Alternatives State Machines in React Performance Optimization Playbook Memoization Strategies Code Splitting and Lazy Loading Error Boundaries and Recovery Portal Architecture Large Scale Folder Structure Testing Strategy: Unit and Integration Common React Anti Patterns
React Production
CSR vs SSR vs SSG Hydration and Mismatch Failures Next.js Architecture Overview App Router Deep Dive Authentication Patterns Token Storage Security Role Based UI Control API Integration Patterns Rate Limiting and UI Resilience Frontend Security Checklist XSS in Modern React Observability in Frontend Bundle Optimization Production Incident Playbook
Distributed Systems
Distributed System Fundamentals CAP Theorem in Practice Consistency Models Replication Strategies Leader Election Concepts Consensus Algorithms Overview Event Driven Architectures Message Queues and Delivery Guarantees Idempotency Patterns Saga Pattern Circuit Breakers Backpressure and Flow Control Observability in Distributed Systems Failure Scenarios and Postmortems

Bundle Optimization

Control bundle size with budgets, dependency discipline, and split points. Learn how to detect bloat sources, prevent client boundary expansion, and ship measurable improvements without breaking caching.
On this page

Bundle Optimization Goals

  • Reduce initial JS cost for faster first interaction.
  • Keep long term performance stable with budgets and gates.
  • Prevent regressions caused by accidental heavy imports.

Primary Bloat Sources

  • Large third party libraries imported into critical routes.
  • Shared barrel exports pulling extra code into client bundles.
  • Client boundary expansion: importing server only modules into client components.
  • Multiple versions of the same dependency in the tree.

Operational Controls

  • Set bundle size budgets per route group.
  • Track changes per pull request and fail on large regressions.
  • Lock dependency versions and audit additions.
  • Prefer small focused packages over large frameworks for single functions.

Split Strategy

  • Split by route and heavy feature boundaries.
  • Lazy load rarely used admin and settings areas.
  • Defer non critical widgets and analytics to after interaction.

Tree Shaking Discipline

  • Prefer ESM imports for tree shaking.
  • Avoid importing entire libraries when only one function is needed.
  • Watch for side effect imports that disable tree shaking.

Cache Friendly Deploys

  • Use content hashed asset filenames for long term caching.
  • Keep entry chunks stable to improve cache reuse.
  • Avoid unnecessary chunk churn from inconsistent import patterns.

Failure Modes

  • Small code change causes large bundle increase due to barrel export pull in.
  • Client only code accidentally imports server modules and expands bundle.
  • Chunk duplication due to inconsistent imports and version conflicts.
  • Over splitting creates many requests and waterfall loading.

Optimization Checklist

  • Budgets exist and are enforced in CI.
  • Heavy dependencies are isolated behind lazy boundaries.
  • Imports are direct and avoid pulling entire libraries.
  • Duplicate dependency versions are removed.
  • Route level splitting is aligned with user journeys.
Production Incident Playbook →