1. Problem Statement (5 minutes)

Interviewer: “Design a scalable e-commerce website similar to Amazon or eBay.”

2. Requirements Clarification (5-10 minutes)

Candidate: “Thank you for the problem. Before we dive into the design, I’d like to clarify some requirements to ensure we’re on the same page.”

2.1 Functional Requirements

  • “Can you confirm the core features we need to support?”
    • User registration and authentication
    • Product catalog with search and filtering
    • Shopping cart functionality
    • Order placement and payment processing
    • Order tracking and history
    • User reviews and ratings

2.2 Non-functional Requirements

  • “What are our scalability expectations?”
    • Interviewer: “The system should handle millions of users and products.”
  • “What are our reliability and availability targets?”
    • Interviewer: “We’re aiming for 99.99% uptime.”
  • “Are there any specific performance requirements?”
    • Interviewer: “Page load times should be under 2 seconds.”

2.3 Scale

  • “Can you provide some numbers to help gauge the scale?”
    • Daily Active Users (DAU): 5 million
    • Total products: 100 million
    • Average orders per day: 500,000

2.4 Additional Considerations

  • “Do we need to consider international users?”
    • Interviewer: “Yes, the system should support multiple languages and currencies.”
  • “Are there any specific security requirements?”
    • Interviewer: “We need to ensure PCI DSS compliance for payment processing.”

3. High-Level Design (15-20 minutes)

Candidate: “Based on these requirements, let’s start with a high-level design of our e-commerce system.”

[Draw a diagram with the following components]

  1. Clients (Web browsers, Mobile apps)
  2. Content Delivery Network (CDN)
  3. Load Balancers
  4. Web Servers
  5. Application Servers
  6. Caching Layer
  7. Databases (Relational and NoSQL)
  8. Search Service
  9. Payment Service
  10. Message Queue
  11. Order Processing Service
  12. Notification Service

3.1 Explain Data Flow

“Let me walk you through a typical user scenario:

  1. User accesses the website through a browser or mobile app.
  2. Static content is served from the CDN.
  3. Dynamic requests go through load balancers to web servers.
  4. Web servers interact with application servers for business logic.
  5. Application servers query the cache for frequently accessed data.
  6. If not in cache, data is fetched from databases.
  7. Search queries are handled by a dedicated search service.
  8. Orders are placed in a message queue for asynchronous processing.
  9. Payment requests are sent to a separate, secure payment service.
  10. After order processing, notifications are sent to users.”

3.2 Discuss Trade-offs

“This design offers scalability and separation of concerns. However, it introduces complexity in managing multiple services. We’ll need to carefully handle data consistency across services.”

4. Detailed Component Design (15-20 minutes)

4.1 Data Storage

“For our database design, we’ll use a combination of relational and NoSQL databases:

  • Relational DB (e.g., PostgreSQL) for user data, product info, and orders.
  • NoSQL DB (e.g., MongoDB) for product catalog and user sessions.
  • We’ll shard our databases based on user_id and product_id to handle the large scale.”

4.2 APIs

“Key API endpoints would include:

  • /api/products: GET, POST, PUT, DELETE for product management
  • /api/cart: GET, POST, PUT for shopping cart operations
  • /api/orders: GET, POST for order management
  • We’ll use RESTful design and implement rate limiting to prevent abuse.”

4.3 Search Functionality

“For efficient search:

  • We’ll use Elasticsearch for full-text search capabilities.
  • Product data will be indexed in Elasticsearch for fast retrieval.
  • We’ll implement autocomplete using a trie data structure for real-time suggestions.”

4.4 Caching Strategy

“To improve performance:

  • We’ll use Redis for caching.
  • Cache product details, user sessions, and frequently accessed data.
  • Implement a write-through cache for consistency.
  • Use cache aside for less frequently updated data.”

5. Scalability and Performance (10-15 minutes)

5.1 Identify Bottlenecks

“Potential bottlenecks include:

  1. Database reads/writes during high traffic (e.g., flash sales).
  2. Payment processing during checkout.
  3. Search functionality for large product catalogs.”

5.2 Propose Optimizations

“To address these:

  1. Implement read replicas and database sharding.
  2. Use a queue-based system for payment processing to handle traffic spikes.
  3. Optimize search with proper indexing and caching of common search results.”

5.3 Load Balancing

“We’ll use consistent hashing for load balancing to ensure even distribution and minimize redistribution when scaling.”

6. Fault Tolerance and Reliability

6.1 Redundancy

“We’ll implement:

  • Multiple availability zones for all components.
  • Hot standby for critical services like payment processing.”

6.2 Data Replication

“We’ll use:

  • Multi-master replication for databases to ensure high availability.
  • Asynchronous replication to maintain performance while ensuring eventual consistency.”

6.3 Disaster Recovery

“We’ll implement:

  • Regular backups to a separate geographic region.
  • Practice failover scenarios to ensure RTO < 1 hour and RPO < 5 minutes.”

7. Security Considerations

“To ensure security:

  • Implement HTTPS everywhere.
  • Use OAuth 2.0 for authentication.
  • Tokenize sensitive data, especially for payment information.
  • Regular security audits and penetration testing.”

8. Additional Considerations

“Some additional points to consider:

  • Implement an A/B testing framework for continuous improvement.
  • Use analytics to track user behavior and optimize the platform.
  • Consider a microservices architecture for future scalability and maintainability.”