Comprehensive System Design Guide

Sep 10, 2024

System Design Roadmap: Basics to Advanced

Importance of System Design

  • Vital for software engineers managing large-scale applications.
  • Necessitates understanding of scalable and reliable systems.

Phase 1: Fundamentals of System Design

Low-Level Design (LLD)

  • Concepts: Object-Oriented Programming (OOP), SOLID principles.
  • Design Patterns: Creational, Structural, Singleton, Factory (8-10 types).
  • UML Diagrams: Class, Sequence, Activity.

High-Level Design (HLD)

  • Architectural Patterns: Monolithic, Microservices, Event-driven.
  • Design Principles: Scalability, Reliability.

Databases and Storage

  • Database Design Principles: Normalization, Denormalization, Indexing.
  • Trends: NoSQL vs Relational Databases.
  • Theoretical Concepts: CAP Theorem (Consistency, Availability, Partitioning).

Networking Basics

  • Protocols: TCP/IP, HTTP/HTTPS.
  • Concepts: Load balancers, CDN, Web Sockets.
  • Example Pipeline: DNS, TCP/IP, HTTPS, Load balancer.

Phase 2: Intermediate System Design

Scalability and Reliability

  • Scalability Techniques: Horizontal/Vertical scaling, Sharding, Partitioning, Caching.
  • Reliability: Redundancy, Replication, Fault Tolerance, Data Backup.

API Design

  • Principles: RESTful API, GraphQL.
  • Considerations: When to use GraphQL, Versioning, Documentation, Rate Limiting.

Security

  • Concepts: Authentication, Authorization, Secure API design.
  • Importance: Brand value impact of security breaches.

Phase 3: Advanced System Design

Microservices

  • Principles: Service Discovery, Inter-service Communication (e.g., Eureka).

Event-driven Systems

  • Tools: Kafka, RabbitMQ.
  • Patterns: CQRS.

Real-time Systems

  • Concepts: Web Sockets, SSE, Real-time Messaging Systems.

Distributed Systems

  • Challenges: Handling transactions in systems with many microservices.
  • Performance: Consensus algorithms, fault tolerance.

Case Studies and Design Patterns

  • Exercise: Apply design patterns, avoid anti-patterns (e.g., Over-engineering, Spaghetti Code).
  • Case Studies: URL Shortener, Social Media, E-commerce, Video Streaming.

Tools and Techniques

Monitoring and Observability

  • Tools: Prometheus, Grafana, Splunk, ELK Stack.

CI/CD

  • Setup: Frequent, reliable deployments.
  • Deployment Strategies: Reverting in case of issues.

Additional Tools

  • Docker, Kubernetes, Service Mesh.

Best Practices

  • Continuous learning and adaptation to industry trends.
  • Keeping systems reliable and scalable through updated knowledge of tools and practices.

Note: Stay updated with industry trends and tools to improve system design skills.