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0 System Design Index

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🚀 System Design Index

System design patterns and architecture concepts essential for building scalable, reliable, and maintainable distributed systems.

Overview

System design is the process of defining the architecture, components, modules, interfaces, and data for a system to satisfy specified requirements. This section covers fundamental patterns and concepts used in modern distributed systems.

Core Concepts

Load Balancing

Communication Patterns

Authentication

Resources

Learning Path

Follow this sequence for optimal understanding:

  1. Load Balancing: 1 Load Balancing Algorithms - Understand traffic distribution
  2. Communication: 2 Inter-Process Communication (IPC) - Learn process communication
  3. Authentication: 3 Single Sign-On (SSO) - Master centralized auth
  4. Resources: 4 System Design Resources - Explore additional materials

Key Concepts

Scalability Patterns

Horizontal Scaling

  • Add more machines to handle load
  • Requires load balancing
  • Better fault tolerance
  • More complex to implement

Vertical Scaling

  • Add more resources to existing machine
  • Simpler to implement
  • Hardware limitations
  • Single point of failure

Caching

  • Reduce database load
  • Improve response times
  • Cache invalidation challenges
  • Multiple caching layers

Database Sharding

  • Partition data across multiple databases
  • Improve query performance
  • Complex to implement
  • Rebalancing challenges

Reliability Patterns

Redundancy

  • Eliminate single points of failure
  • Active-active or active-passive
  • Data replication
  • Geographic distribution

Health Checks

  • Monitor service availability
  • Automatic failover
  • Circuit breakers
  • Graceful degradation

Retry Logic

  • Handle transient failures
  • Exponential backoff
  • Idempotency considerations
  • Maximum retry limits

Rate Limiting

  • Prevent system overload
  • Protect against abuse
  • Fair resource allocation
  • Multiple rate limit tiers

Communication Patterns

Synchronous

  • Request-response model
  • HTTP/REST APIs
  • gRPC
  • Direct coupling

Asynchronous

  • Message queues
  • Event-driven architecture
  • Pub/sub patterns
  • Loose coupling

Service Mesh

  • Service-to-service communication
  • Load balancing and discovery
  • Security and observability
  • Traffic management

Data Patterns

Database Types

  • Relational (SQL) - ACID transactions
  • NoSQL - Flexible schema, horizontal scaling
  • Key-Value - Simple, fast lookups
  • Document - JSON-like documents
  • Graph - Relationship-focused

Data Consistency

  • Strong consistency - Always up-to-date
  • Eventual consistency - Eventually up-to-date
  • CAP theorem - Consistency, Availability, Partition tolerance

Data Replication

  • Master-slave replication
  • Multi-master replication
  • Read replicas
  • Cross-region replication

AWS System Design Components

Compute

Load Balancing

  • ALB - Layer 7 load balancing
  • NLB - Layer 4 load balancing

Networking

Data Streaming

  • Kinesis - Real-time data streaming

Infrastructure

Security

Design Principles

Scalability

  • Design for horizontal scaling
  • Use stateless services when possible
  • Implement caching strategically
  • Partition data effectively

Reliability

  • Eliminate single points of failure
  • Implement health checks and monitoring
  • Use multiple availability zones
  • Plan for disaster recovery

Performance

  • Optimize database queries
  • Use CDNs for static content
  • Implement efficient caching
  • Choose appropriate data structures

Security

  • Defense in depth
  • Principle of least privilege
  • Encrypt data in transit and at rest
  • Regular security audits

Cost Optimization

  • Right-size resources
  • Use auto scaling
  • Leverage spot instances
  • Monitor and optimize continuously

Maintainability

  • Clear documentation
  • Consistent naming conventions
  • Modular architecture
  • Automated testing

Common Architecture Patterns

Microservices

  • Small, independent services
  • Each service owns its data
  • Communicate via APIs
  • Independent deployment

Event-Driven

  • Services react to events
  • Loose coupling
  • Asynchronous processing
  • Scalable and resilient

Serverless

  • No server management
  • Pay per execution
  • Auto-scaling
  • Event-driven

Monolithic

  • Single deployable unit
  • Simpler to develop initially
  • Tighter coupling
  • Harder to scale

System Design Interview Topics

Common Questions

  1. Design a URL shortener
  2. Design a social media feed
  3. Design a distributed cache
  4. Design a rate limiter
  5. Design a notification system
  6. Design a chat application
  7. Design a file storage system
  8. Design a search engine

Approach

  1. Clarify requirements - Functional and non-functional
  2. Estimate scale - Users, requests, storage
  3. High-level design - Major components
  4. Deep dive - Detailed component design
  5. Identify bottlenecks - Performance, scalability
  6. Discuss trade-offs - Different approaches

Prerequisites

AWS Services

  • EC2 - Compute foundation
  • ECS - Container orchestration
  • AWS Services - Additional services

Implementation

  • IaaC - Automate infrastructure
  • Linux - System administration

Learning Resources

Books

  • Designing Data-Intensive Applications (Martin Kleppmann)
  • System Design Interview (Alex Xu)
  • Building Microservices (Sam Newman)
  • Site Reliability Engineering (Google)

Online Resources

  • ByteByteGo - System design content
  • System Design Primer (GitHub)
  • AWS Architecture Center
  • High Scalability blog

Practice

  • Design real-world systems
  • Review architecture of popular services
  • Participate in system design discussions
  • Build and deploy distributed systems

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