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How to Design a System from Scratch: A Comprehensive Guide

Mustufa khan's photo
Mustufa khan
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5 min read

Designing a system from scratch is a crucial skill for software engineers. It involves systematically breaking down a problem into manageable components while ensuring the design is scalable, efficient, and reliable. Below is a step-by-step approach to designing a system, suitable for interviews and real-world projects.

Step 1: Clarify Requirements

The first step is to understand what you're building. Focus on both functional and non-functional requirements.

Key Questions to Ask:

  1. Functional Requirements:

    • What are the core features of the system?

      • Example: For a URL shortener, should it only shorten URLs, or also track analytics like click rates?

  2. Non-Functional Requirements:

    • Scalability: How many users and requests are expected? What’s the peak traffic?

    • Availability: Should the system be highly available? What is the acceptable downtime?

    • Latency: What is the desired response time?

  3. Constraints:

    • Budget: Are there cost limitations for infrastructure or third-party services?

    • Timeline: Are there deadlines for delivery?

    • Technology: Are there any technology preferences or restrictions?

Step 2: Define the API Contract

Define how the system will interact with clients or other systems. This ensures clarity on the input, output, and functionality.

Examples:

  1. For a URL Shortener:

    • POST /shorten - Accepts a URL and returns a shortened version.

    • GET /{shortURL} - Redirects to the original URL.

  2. For a Real-Time Chat Application:

    • POST /messages - Send a message.

    • GET /messages - Fetch recent messages for a user.

Step 3: High-Level Design (HLD)

Define the broad architecture and key components of the system.

Key Steps:

  1. Break Down the System into Components:

    • Identify key modules or subsystems.

      • Example: For Twitter:

        • User Service: Manages profiles.

        • Tweet Service: Handles tweets and feeds.

        • Notification Service: Alerts users about mentions.

  2. Choose Architectural Patterns:

    • Monolithic Architecture: Tightly coupled components, suitable for small systems.

    • Microservices Architecture: Independent, loosely coupled services for scalability.

  3. Define the Data Flow:

    • Map out how data flows between clients, servers, and databases.

      • Example: A user request → Load Balancer → Application Server → Database.

  4. Sketch a High-Level Diagram:

    • Include components like load balancers, application servers, databases, and caches.

    • Show interactions and data flow between components.

Step 4: Identify the Core Challenges

Focus on the unique challenges posed by the system and plan solutions for them.

Examples:

  • Scalability: How will the system handle millions of requests?

    • Solution: Use horizontal scaling and load balancing.

  • Data Storage: Should you use SQL or NoSQL? Sharding or replication?

  • Latency: How will you ensure low response times?

    • Solution: Use caching.

  • Consistency: Do you prioritize consistency or availability? (CAP theorem)

Step 5: Low-Level Design (LLD)

Detail the inner workings of each component.

Key Areas:

  1. Database Schema:

    • Design tables or collections for data storage.

      • Example: For a URL shortener:

        • Table: URLs

          • shortURL: Primary Key.

          • originalURL: The full URL.

          • timestamp: Time of creation.

  2. APIs:

    • Specify endpoints, input/output formats, and response codes.

      • Example: Use JSON for REST APIs.

  3. Algorithms:

    • Define logic for specific tasks.

      • Example: For a URL shortener, use a hashing algorithm to generate unique short URLs.

  4. Data Structures:

    • Choose appropriate structures for the use case.

      • Example: Use a Trie for autocomplete features.

Step 6: Plan for Scalability

Scalability ensures the system can handle increasing loads efficiently.

Techniques:

  1. Load Balancing:

    • Use tools like Nginx or AWS ELB to distribute traffic evenly.

  2. Caching:

    • Store frequently accessed data in caches (e.g., Redis).

      • Example: Cache user profiles to reduce database load.

  3. Database Partitioning:

    • Sharding: Divide data across multiple databases.

      • Example: Partition users by geographic region.

  4. Replication:

    • Create read replicas for handling more read requests.

Step 7: Ensure Reliability and Fault Tolerance

Design the system to handle failures gracefully.

Approaches:

  1. Data Replication:

    • Store copies of data in multiple servers or regions.

    • Example: Use AWS RDS with Multi-AZ deployment.

  2. Retries and Circuit Breakers:

    • Implement retries for transient failures and circuit breakers for prolonged issues.

  3. Monitoring and Alerts:

    • Use tools like Prometheus and Grafana to monitor system performance.

    • Set up alerts for downtime or performance degradation.

Step 8: Security

Incorporate security measures to protect the system and user data.

Best Practices:

  1. Authentication and Authorization:

    • Use OAuth2 or JWT for secure access control.

  2. Encryption:

    • Encrypt data in transit (SSL/TLS) and at rest.

  3. Rate Limiting:

    • Prevent abuse by limiting API calls per user/IP.

  4. Input Validation:

    • Prevent SQL injection and XSS by validating inputs.

Step 9: Trade-offs and Alternatives

Every design decision comes with trade-offs. Be ready to justify your choices.

Common Trade-offs:

  • SQL vs NoSQL databases.

  • Caching for speed vs consistency.

  • Microservices vs monolithic architecture.

How to Think:

  • What are the pros and cons of each approach?

  • How do they impact scalability, latency, or cost?

Step 10: Diagram the Final Design

Create a detailed system diagram using tools like Lucidchart or a whiteboard.

Key Points to Include:

  • All components labeled clearly.

  • Data flow between components.

  • Solutions to address potential bottlenecks.

Step 11: Optimize and Iterate

Before finalizing, ensure the design meets all requirements.

Checklist:

  1. Are there any bottlenecks?

  2. Have you accounted for edge cases?

  3. Is the system over-engineered? Simplify where possible.

Step 12: Discuss Testing and Deployment

Testing and deployment ensure the system is robust and ready for users.

Testing:

  • Unit tests for individual components.

  • Integration tests for end-to-end functionality.

Deployment:

  • Use CI/CD pipelines for automated builds and deployments.

  • Consider blue/green or canary deployments for safer rollouts.

Example Walkthrough: URL Shortener

Scenario: Design a URL Shortener.

  1. Requirements:

    • Functional: Shorten URLs, redirect users, track usage stats.

    • Non-functional: Handle 1M requests/day, <100ms latency.

  2. API Contract:

    • POST /shorten and GET /{shortURL}.

  3. HLD:

    • Load balancer, app servers, database, caching.

  4. LLD:

    • Schema for URL storage, hash algorithm for short URLs.

  5. Scalability:

    • Cache popular URLs, shard by short URL prefix.

  6. Security:

    • Validate inputs, rate-limit abusive users.
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