System Design Patterns

Master common system design patterns used in building scalable distributed systems.

Showing 9 of 9 questions
Easy: 0 Medium: 0 Hard: 0
QUESTIONDIFFICULTY
Load Balancing Strategies
Design and implement different load balancing algorithms including round-robin, least connections, and weighted distribution
Easy
Caching Patterns
Implement various caching strategies including cache-aside, write-through, write-back, and refresh-ahead patterns
Easy
Database Sharding
Design a database sharding strategy for horizontal scaling with consistent hashing and data distribution
Medium
Event-Driven Architecture
Design an event-driven system using message queues, event sourcing, and CQRS patterns
Medium
Microservices Communication
Design communication patterns between microservices including synchronous REST, asynchronous messaging, and gRPC
Medium
Circuit Breaker Pattern
Implement a circuit breaker pattern to handle failures gracefully in distributed systems
Medium
Saga Pattern
Design distributed transactions using the Saga pattern with choreography and orchestration approaches
Hard
Distributed Consensus
Implement distributed consensus algorithms like Raft or Paxos for maintaining consistency across nodes
Hard
Multi-Region Deployment
Design a globally distributed system with multi-region deployment, data replication, and disaster recovery
Hard

Overview

System design patterns are reusable solutions to common problems in software architecture. Understanding these patterns is crucial for building scalable, reliable, and maintainable distributed systems.

Key Concepts

  • Scalability Patterns: Techniques for horizontal and vertical scaling
  • Reliability Patterns: Ensuring system availability and fault tolerance
  • Performance Patterns: Optimizing system performance and latency
  • Data Patterns: Managing data consistency and replication
  • Communication Patterns: Inter-service communication strategies

Common Pattern Categories

Scalability

  • Load Balancing
  • Database Sharding
  • Caching Strategies
  • Content Delivery Networks (CDN)

Reliability

  • Circuit Breaker
  • Retry with Exponential Backoff
  • Bulkhead Pattern
  • Health Checks

Data Management

  • Event Sourcing
  • CQRS (Command Query Responsibility Segregation)
  • Database Replication
  • Saga Pattern

Communication

  • API Gateway
  • Service Mesh
  • Message Queue
  • Pub/Sub Pattern

Practice Tips

  1. Understand Trade-offs: Every pattern has pros and cons
  2. Real-world Examples: Study how companies like Netflix, Amazon, and Google use these patterns
  3. Hands-on Practice: Implement patterns in small projects
  4. CAP Theorem: Understand consistency, availability, and partition tolerance trade-offs

Resources