What are the 4 stages of system design?

The 4 stages of system design typically refer to the key phases that help you systematically approach designing a scalable and efficient system. These stages provide a structured way to analyze, plan, and implement a system that meets both functional and non-functional requirements. Here's an overview of the four key stages:

1. Requirements Gathering and Clarification

Purpose:

• To understand the problem you're solving and to ensure you have a clear idea of what the system needs to do. This involves gathering both functional and non-functional requirements.

Key Steps:

• Ask Clarifying Questions: Gain clarity on the scope of the system. What are the features the system needs to support? What’s the expected traffic load?
• Identify Functional Requirements: What core features and functionalities should the system offer? For example, in a URL shortener, the system should create short URLs and handle redirections.
• Understand Non-Functional Requirements: Understand the constraints related to scalability, availability, latency, and performance. For example, what level of uptime is expected? What is the maximum acceptable response time for users?
• Estimate Traffic: Get a sense of the number of requests per second, peak traffic loads, read/write ratios, etc. This helps you design a system that scales accordingly.

Example:

• Designing a messaging app: Ask about expected user traffic, data storage requirements, message latency requirements, and the balance between real-time messaging vs. persistent message storage.

2. High-Level Design

Purpose:

• To define the architecture of the system and identify the major components that interact with each other. At this stage, you’re creating a blueprint of the system’s structure without diving too deep into implementation details.

Key Steps:

• Identify Core Components: Break the system down into components like the frontend, backend services, databases, caching layers, load balancers, etc.
• Define Data Flow: Explain how data moves between these components. For example, how do user requests flow from the frontend to the backend and how is data stored or retrieved from the database?
• Draw a High-Level Diagram: Use a diagram (either on a whiteboard or a virtual tool like Miro) to visually represent the components and their interactions. Make sure to highlight key components like databases, APIs, caches, and external services.

Example:

• For a URL shortener:
  • Components: Client (user interface), backend API (URL generation), database (store URL mappings), cache (frequently accessed URLs), and load balancer.
  • Data Flow: User sends a long URL to the API → API checks if the URL exists in the cache → If not found, a new short URL is generated and stored in the database → Cache the result and return the short URL to the user.

3. Detailed Design (Component-Level Design)

Purpose:

• To dive deeper into the individual components of the system. This stage involves designing the specifics of each part of the system, such as database schema, caching strategies, and load balancing techniques. You also address system bottlenecks and trade-offs.

Key Steps:

• Database Design: Choose between SQL and NoSQL databases based on the requirements. Define how data will be stored, queried, and indexed.

  • Partitioning and Sharding: If dealing with large-scale data, decide how to partition or shard the data for better scalability.
  • Replication: Discuss replication strategies to ensure data availability and fault tolerance.

• Caching Strategy: Define how caching will be used to reduce database load and improve performance. Choose between write-through, write-back, or lazy-loading caches. Plan for cache invalidation.

• Load Balancing: Choose a load-balancing strategy (e.g., round-robin, least connections) and explain how it distributes traffic across multiple servers to ensure high availability.

• Data Flow Optimization: Fine-tune how data flows between components. Ensure that the system can handle bottlenecks such as high write traffic, high latency, or frequent cache misses.

Example:

• For a social media feed system:
  • Database: Design the database to store user posts, comments, likes, and connections. Use a sharded NoSQL database to handle large-scale data.
  • Cache: Use a caching layer (e.g., Redis) to store the most recent or popular posts for faster feed generation.
  • Load Balancing: Use a load balancer to distribute requests for feed generation across multiple backend services.

4. Scalability, Trade-offs, and Optimization

Purpose:

• To focus on scaling the system, handling edge cases, and making trade-offs between performance, reliability, and cost. This stage helps refine the system for optimal performance in real-world scenarios.

Key Steps:

• Scalability Planning: Discuss how the system can scale to handle more users or increased traffic. Consider adding more servers (horizontal scaling), sharding databases, or increasing read/write throughput with replication.

• Trade-offs: Explain the trade-offs between consistency and availability (CAP theorem), latency vs. throughput, or cost vs. performance. For example, favoring eventual consistency might allow the system to scale more easily, but some user actions might take time to reflect across the system.

• Fault Tolerance and Availability: Ensure that the system can handle failures, such as database or server crashes. Implement backup and recovery strategies, failover mechanisms, and replication to prevent data loss.

• Bottleneck Identification: Identify potential bottlenecks and suggest optimizations. For example, if the database becomes a bottleneck, propose sharding or moving certain data into a cache.

Example:

• For a video streaming service:
  • Scalability: Use a content delivery network (CDN) to serve videos closer to the user, reducing latency and load on the main servers.
  • Trade-offs: Use eventual consistency for view counts or user recommendations, prioritizing availability over consistency.
  • Fault Tolerance: Replicate video metadata across regions to ensure the service continues if one region goes down.

Conclusion

By following these 4 stages of system design, you can systematically approach a system design interview and present a well-thought-out solution. Each stage ensures that you’ve addressed the most critical aspects of designing a scalable, reliable, and efficient system.

Key Takeaways:

1. Requirements Gathering: Clarify both functional and non-functional requirements.
2. High-Level Design: Outline the core components and their interactions.
3. Detailed Design: Dive into specifics like database schema, caching, and load balancing.
4. Scalability and Trade-offs: Address scalability, handle bottlenecks, and make trade-offs between performance, availability, and cost.