This guide provides a comprehensive overview of system design concepts, principles, patterns, and examples.

Table of Contents

  1. What is System Design?
  2. Key Principles of System Design
  3. System Design Process
  4. Scalability
  5. High Availability
  6. Load Balancing
  7. Caching
  8. Database Design
  9. Sharding
  10. Replication
  11. Indexes
  12. Message Queues
  13. CAP Theorem
  14. Design Patterns
  15. Common System Design Questions
  16. Best Practices

1. What is System Design?

System design is the process of defining the architecture, components, modules, interfaces, and data flow of a system to meet specific requirements. It involves:

  • Understanding user requirements.
  • Designing for scalability, reliability, and maintainability.
  • Optimizing for performance and cost.

2. Key Principles of System Design

  • Scalability: Handle increasing traffic or data growth.
  • Reliability: Ensure the system remains functional during failures.
  • Maintainability: Simplify debugging, updates, and feature additions.
  • Efficiency: Optimize resource utilization and response time.
  • Security: Protect data and resources from unauthorized access.

3. System Design Process

  1. Requirements Gathering:

    • Clarify functional requirements (e.g., features, user actions).
    • Identify non-functional requirements (e.g., scalability, latency, availability).

  2. High-Level Design:

    • Define the system’s overall architecture.
    • Identify components like databases, servers, APIs, etc.

  3. Component Design:

    • Focus on individual components (e.g., user service, payment service).
    • Define APIs and data contracts.

  4. Data Flow and Communication:

    • Define how components interact (e.g., REST, gRPC, message queues).

  5. Database Design:

    • Select appropriate storage solutions (SQL, NoSQL).

  6. Scaling Strategies:

    • Add load balancers, caching, sharding, etc.

4. Scalability

Scalability is the ability of a system to handle increased load.

  1. Vertical Scaling:

    • Add more resources (CPU, RAM) to a single server.
    • Limited by hardware constraints.

  2. Horizontal Scaling:

    • Add more servers to distribute the load.
    • Use load balancers to route traffic.

Example: A web app with 1M users requires additional servers to handle increased traffic.

5. High Availability

High Availability (HA) ensures minimal downtime.

  1. Redundancy:

    • Duplicate critical components (e.g., databases, servers).

  2. Failover:

    • Automatically switch to backup components in case of failure.

  3. Distributed Systems:

    • Use multiple data centers to ensure availability.

Example: Use a primary database with a secondary replica as a failover mechanism.

6. Load Balancing

Load Balancers distribute traffic across multiple servers.

  1. Types of Load Balancing:

    • DNS Load Balancing: Use DNS records to route traffic.
    • Hardware Load Balancers: Dedicated devices (e.g., F5, Citrix).
    • Software Load Balancers: NGINX, HAProxy.

  2. Algorithms:

    • Round Robin
    • Least Connections
    • Weighted Distribution

Example: An e-commerce site routes traffic to multiple web servers using NGINX.

7. Caching

Caching stores frequently accessed data for quick retrieval.

  1. Types of Caches:

    • Client-Side Cache: Stored in the browser (e.g., cookies, local storage).
    • Server-Side Cache: Stored in the backend (e.g., Redis, Memcached).

  2. Cache Invalidation:

    • Time-Based: Set expiration times.
    • Write-Through: Update the cache on data write.

Example: Use Redis to cache user session data to reduce database load.

8. Database Design

  1. Relational Databases:

    • Use SQL (e.g., MySQL, PostgreSQL).
    • Best for structured data.

  2. NoSQL Databases:

    • Document stores (e.g., MongoDB).
    • Key-value stores (e.g., DynamoDB).

  3. Schema Design:

    • Normalize to avoid redundancy.
    • Denormalize for performance.

9. Sharding

Sharding splits a database into smaller pieces (shards) to handle large data volumes.

  1. Horizontal Sharding:

    • Split rows into shards.

  2. Vertical Sharding:

    • Split columns into shards.

Example: User data split by region (e.g., US shard, EU shard).

10. Replication

Replication creates copies of data for reliability and read performance.

  1. Primary-Secondary Replication:

    • One primary database, multiple read replicas.

  2. Multi-Master Replication:

    • Multiple databases handle writes.

Example: Use read replicas to handle read-heavy workloads.

11. Indexes

Indexes speed up database queries by creating lookups for data.

  1. Single-Column Index: Index one column.
  2. Composite Index: Index multiple columns.

Example: Index user_id for faster searches.

12. Message Queues

Message Queues decouple components and enable asynchronous communication.

  1. Examples: RabbitMQ, Kafka, SQS.
  2. Use Cases:
    • Task scheduling.
    • Event-driven systems.

13. CAP Theorem

A distributed system can provide only two of the following:

  1. Consistency: All nodes see the same data.
  2. Availability: System responds to all requests.
  3. Partition Tolerance: System works despite network splits.

Example: Choose consistency over availability for banking systems.

14. Design Patterns

  1. Microservices:

    • Split a system into independent services.

  2. Event-Driven Architecture:

    • Use events to trigger actions.

  3. CQRS (Command Query Responsibility Segregation):

    • Separate read and write operations.

  4. Rate Limiting:

    • Control API usage to prevent abuse.

15. Common System Design Questions

  1. Design a URL shortener (e.g., Bitly).
  2. Design a scalable chat application (e.g., WhatsApp).
  3. Design a video streaming service (e.g., YouTube).
  4. Design an e-commerce system (e.g., Amazon).
  5. Design a ride-sharing app (e.g., Uber).

16. Best Practices

  1. Start with requirements and constraints.
  2. Use diagrams to explain your architecture.
  3. Justify trade-offs (e.g., SQL vs. NoSQL).
  4. Consider scalability and fault tolerance.
  5. Review and refine your design.