Comprehensive System Design Guide

Aug 19, 2024

System Design Tutorial Overview

This tutorial provides a comprehensive guide to system design, focusing on scalability, reliability, data handling, and high-level architecture. It prepares you for system design interviews by covering core concepts, real-world examples, and practical strategies.

Key Concepts Covered

  • High-Level Architecture
  • Computer System Basics
  • Data Storage
  • RAM and Cache
  • CPU Functionality
  • Continuous Integration and Continuous Deployment (CI/CD) Pipeline
  • Load Balancing
  • Logging and Monitoring
  • Debugging
  • System Design Principles

Computer System Basics

Data Representation

  • Binary System: Computers use binary (0s and 1s).
  • Bits and Bytes: 1 Byte = 8 bits.

Storage Types

  • Disk Storage: Non-volatile, maintains data without power (HDD vs SSD).
  • RAM: Volatile, fast access for active data.
  • Cache: Smaller/faster than RAM, reduces average data access time.

CPU

  • Function: Fetches, decodes, executes instructions.
  • Compilation: Converts high-level code to machine code.

System Architecture and Operations

CI/CD Pipeline

  • Automates code deployment using Jenkins or GitHub Actions.

Load Balancing

  • Uses tools like Nginx to distribute user requests evenly across servers.

Data Storage

  • External Storage: Separate from production servers.

Monitoring and Alerting

  • Logging systems and alerting services for error detection.
  • Use tools like PM2 and Sentry for backend/frontend monitoring.

System Design Principles

Key Principles

  • Scalability: Growth with user base.
  • Maintainability: Future development.
  • Efficiency: Resource optimization.

Fault Tolerance

  • Planning for failures, building robust/resilient applications.

CAP Theorem

  • Consistency: All nodes same data.
  • Availability: System always operational.
  • Partition Tolerance: System works despite network partitions.

Availability Metrics

  • Five 9’s: Aim for 99.999% uptime.
  • SLO/SLA: Performance and availability goals/contracts.

Database Design

Types of Databases

  • Relational: SQL, tables, ACID properties.
  • NoSQL: Schema-less, flexible (key-value, document, graph).

Scaling Techniques

  • Vertical Scaling: Increasing resources of a single server.
  • Horizontal Scaling: Adding more servers (sharding, replication).

Performance Optimization

  • Caching: Use Redis for frequent queries.
  • Indexing: Speed up data retrieval.
  • Query Optimization: Minimize joins, use query analyzers.

Networking Basics

IP Addresses

  • IPv4: 32-bit, limited.
  • IPv6: 128-bit, expanded.

Protocols

  • HTTP: Stateless, request-response.
  • DNS: Domain name to IP address translation.
  • TCP/UDP: Reliable/unreliable data transport.

Proxy Servers

  • Forward Proxy: Intermediary for clients.
  • Reverse Proxy: Intermediary for servers, hides server identity.

Load Balancers

  • Strategies: Round Robin, Least Connections, IP Hashing.

API Design

API Types

  • REST: Stateless, HTTP methods.
  • GraphQL: Flexible queries, avoids over-fetching.
  • gRPC: Protocol buffers, efficient communication.

Best Practices

  • Versioning: Maintain backward compatibility.
  • Rate Limiting: Prevent DDoS attacks.
  • CORS: Control API access.

Caching and CDN

  • Browser, Server, Database Caching: Improve performance.
  • CDN: Geographically distributed servers for static content.

Conclusion

This comprehensive tutorial covers crucial aspects of system design, giving insights into architecture, database management, networking, and API development. Mastery of these concepts will aid in excelling at system design interviews.