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

Consensus Algorithms Overview

Consensus provides agreement on a single value or log despite failures. Learn the problems it solves, quorum assumptions, safety vs liveness, and what Raft and Paxos style systems guarantee in production.
On this page

What Consensus Solves

  • Agree on a leader and membership changes.
  • Replicate an ordered log of commands safely.
  • Provide a single source of truth for critical metadata.

Safety vs Liveness

  • Safety: nothing bad happens, no two leaders commit conflicting logs.
  • Liveness: something good eventually happens, the system makes progress.
  • Production rule: safety is non negotiable, liveness depends on timing and failure assumptions.

Quorum Basics

  • Consensus typically requires a majority quorum.
  • Majority intersection prevents two different quorums from committing conflicting decisions.
  • With 2f + 1 nodes, the system can tolerate f failures while maintaining safety.

Log Replication Model

  • Client submits command to leader.
  • Leader appends to log and replicates to followers.
  • Once a quorum acknowledges, entry is committed.
  • Committed entries are applied to a deterministic state machine.

Raft vs Paxos High Level

  • Raft emphasizes understandability with leader election and log replication steps.
  • Paxos family focuses on proving safety properties under asynchronous networks.
  • In practice, both implement quorum based agreement with similar guarantees.

Operational Concerns

  • Write latency depends on quorum round trips.
  • Membership changes must be handled safely to avoid losing quorum.
  • Snapshots and log compaction are required for long running clusters.

Failure Modes

  • Election storms due to aggressive timeouts and unstable networks.
  • Disk latency spikes cause followers to fall behind and reduce throughput.
  • Misconfigured membership change reduces fault tolerance and breaks availability.
  • Split brain behavior if quorum rules are violated by implementation or operators.

Production Checklist

  • Majority quorum is enforced for commits.
  • Election timeouts tuned for real latency and pauses.
  • Snapshots and compaction are configured and monitored.
  • Node health signals include disk, network, and replication lag.
Event Driven Architectures →