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

CAP Theorem in Practice

CAP is a tradeoff under partition: choose between consistency and availability per operation. Learn how real systems mix modes, define SLAs, and avoid cache leaks and split brain during incidents.
On this page

What CAP Actually Says

  • When a network partition happens, you must trade between consistency and availability.
  • Partition tolerance is not optional in distributed systems.
  • CAP is about behavior under partition, not normal operation.

Operational Interpretation

  • Consistency: reads reflect the latest acknowledged write or a valid ordering.
  • Availability: every request receives a response without waiting for unreachable nodes.
  • Under partition: you either reject some operations or serve potentially stale or divergent data.

Per Operation Choices

  • Read path can be more available than write path.
  • Some operations can tolerate staleness, others cannot.
  • Strong consistency is often required for money movement and permissions.

Common Patterns

  • CP systems: reject writes during partition to preserve consistency.
  • AP systems: accept writes and reconcile later, using conflict resolution.
  • Hybrid: use CP for critical metadata, AP for high volume events.

Quorums as a Dial

  • Quorum reads and writes can increase consistency but reduce availability during failures.
  • Lower quorum increases availability but can serve stale reads.
  • Production rule: define quorum policy per dataset and operation.

Failure Modes

  • Split brain due to weak leader election or stale leases.
  • Cache shows wrong authorization decisions when stale data is used.
  • Read your writes breaks when reads route to replicas with lag.
  • Reconciliation produces conflicts without a defined policy.

Incident Playbook

  • Detect partition: rising timeouts, asymmetric reachability, replica lag spike.
  • Freeze critical writes if needed to prevent divergence.
  • Reduce load with backoff, circuit breakers, and load shedding.
  • Confirm leadership and membership view before resuming full traffic.

Production Checklist

  • Define which operations require strong consistency.
  • Document behavior under partition: reject, degrade, or reconcile.
  • Test partition scenarios and validate recovery steps.
  • Monitor leader health, quorum success rate, and replica lag.
Consistency Models →