System Design Interview PDF: A Complete Roadmap & Checklist for Preparation

6. Putting Theory into Practice: Designing a Scalable E-Commerce Platform

Even the most thorough “System Design Interview PDF” or roadmap wouldn’t be complete without a practical example.

Let’s walk through how to design a large-scale e-commerce platform, step by step. This exercise will help you see how all the concepts we’ve covered—from databases and caching to reliability and microservices—fit together in a real-world scenario.

By systematically addressing each component, you’ll gain both the knowledge and confidence to handle similar design questions in an interview.

6.1 Step 1: Clarify Requirements

Before diving into architecture, it’s essential to clarify the functional and non-functional requirements. Ask your interviewer (or yourself) questions like:

1. Functional Requirements
   • User Profiles and Authentication: Users must be able to create accounts, log in securely, and manage profiles.
   • Product Catalog: The platform should support listing thousands (or even millions) of products with detailed descriptions, images, pricing, and reviews.
   • Shopping Cart & Checkout: Users need to add items to a cart and complete a purchase using multiple payment options.
   • Order Management: Track orders from placement to delivery, sending notifications along the way.
2. Non-Functional Requirements
   • Scalability: The system should handle seasonal spikes (e.g., Black Friday), potentially millions of concurrent users.
   • Reliability: Minimize downtime, ensuring the site remains up 99.99% of the time.
   • Low Latency: Quick page loads and minimal checkout friction.
   • Security: Protect user data, encrypt payments, and guard against fraud.

Having these requirements in mind guides every architectural decision. It also demonstrates to interviewers that you know how to extract detailed specs—an essential skill for real-world engineering.

6.2 Step 2: High-Level Architecture

Start with a bird’s-eye view of the system:

1. Client Layer
   • Web and mobile clients connect via HTTPS or secure mobile SDKs.
   • A load balancer (e.g., NGINX, AWS ELB) distributes incoming traffic across multiple instances.
2. Application Layer (Microservices)
   • User Service: Handles user registration, login, authentication.
   • Product Catalog Service: Manages product listings, categories, and search queries.
   • Shopping Cart Service: Tracks items in a user’s cart, updates quantities, handles cart sessions.
   • Order Service: Processes new orders, payment confirmations, and shipping details.
   • Payment Service: Interacts with third-party payment gateways (e.g., Stripe, PayPal).
   • Notification Service: Sends email/SMS notifications about order updates.
3. Database & Storage
   • Relational Databases (e.g., MySQL, PostgreSQL) for critical transactional data like orders and payments.
   • NoSQL Databases (e.g., MongoDB) for product catalogs or user reviews, if you need flexible schemas or high read throughput.
   • Caching Layer (e.g., Redis) for fast retrieval of frequently accessed data, such as top-selling items or user session data.
   • Blob Storage (e.g., AWS S3) for product images and other large media files.
   • CDN for delivering images and static content globally at low latency.
4. Communication & APIs
   • REST or gRPC for synchronous communication between user-facing services.
   • Message Queue (e.g., RabbitMQ, Kafka) for asynchronous tasks like sending email notifications, updating analytics dashboards, or re-stocking inventory.

6.3 Step 3: Scalability & Reliability

An e-commerce platform must be prepared for unpredictable traffic surges—especially during holiday seasons or promotional events.

1. Horizontal Scaling
   • Spin up additional instances of services behind your load balancer to handle higher loads.
   • Use auto-scaling policies in cloud environments (AWS, Azure, GCP) to match traffic demands.
2. Database Scaling
   • Master-Slave Replication: Writes go to the master, reads are served by the slave(s).
   • Partitioning (Sharding): Split data by region or user ID to handle large datasets.
   • Caching: Store frequently read data (like popular product listings) in Redis or Memcached.
3. Reliability Techniques
   • Active-Passive Failover: Keep backup instances ready in another region or availability zone.
   • Circuit Breakers & Health Checks: If a microservice fails, automatically reroute traffic or temporarily downgrade service.
   • Retry Logic: For payment or order services, implement retries for transient failures.

6.4 Step 4: Security & Payment Processing

Handling financial transactions is a core part of any online store, so security must be top-notch.

1. Authentication & Authorization
   • Use OAuth, JWT, or custom tokens to manage user sessions.
   • Secure all endpoints with HTTPS/TLS to protect data in transit.
2. Payment Gateway Integration
   • Offload sensitive payment details to trusted third-party gateways (Stripe, PayPal) to reduce compliance burden.
   • Store minimal user payment data (like last four digits of a credit card) to comply with regulations (e.g., PCI DSS).
3. Fraud Detection
   • Implement rules-based or machine learning solutions to spot suspicious orders or account activity.
   • Use a separate Fraud Service that analyzes order patterns and flags high-risk transactions.

6.5 Step 5: Monitoring & Observability

For a large-scale system, continuous monitoring is crucial. If a microservice slows down, you’ll want to know before customers start abandoning carts.

1. Metrics & Logging
   • Collect metrics (CPU usage, memory, response times) for each service.
   • Use centralized logging (ELK stack, Datadog, Splunk) for quick troubleshooting.
2. Alerts & Dashboards
   • Set up alerts for high error rates, latency spikes, or sudden traffic drops.
   • Maintain real-time dashboards for system health (e.g., number of pending orders, average checkout times).

6.6 Step 6: Example Interview Flow

Interviewer: “Can you design a scalable e-commerce platform that can handle holiday traffic spikes?”
You: “Certainly! First, I’ll clarify the main requirements…”

1. Clarify Requirements: “We expect millions of daily active users, need secure payment processing, and real-time order tracking. Our user base is global, so we also need multi-region support.”
2. Draw a High-Level Diagram: Show how you’d handle load balancing, user authentication, microservices, databases, caching, and asynchronous messaging.
3. Discuss Data Flows: Explain how a request moves from the user to the load balancer, then through each microservice, ending in the database or payment gateway.
4. Highlight Key Trade-Offs: For instance, using a NoSQL store for product catalogs vs. a relational database for order transactions.
5. Address Failure Scenarios: “What happens if the Payment Service goes down? We can use a message queue to queue payments until the service recovers, or we could switch to a backup provider.”
6. Mention Security: Show you understand encryption, token-based authentication, and PCI compliance.
7. Summarize: Restate the key components, justify design choices, and tie it all back to the requirements.

6.7 Tying It Back to the Checklist

Recall the Ultimate System Design Interview Checklist from Section 6. Notice how each point applies to our e-commerce example:

1. Define Requirements & Constraints – We clarified functional (cart, catalog, checkout) and non-functional (scalability, security) needs.
2. High-Level Design – We drew a holistic architecture with microservices, load balancers, and databases.
3. Database Choice & Schema – We used a combination of relational databases for orders and NoSQL for product catalogs.
4. Scalability & Caching – We introduced horizontal scaling and caching layers for peak traffic.
5. Microservices & Communication – Our design separated out the User, Product, Order, and Payment services, communicating via REST or message queues.
6. Reliability & Fault Tolerance – We planned for failover, redundancy, and auto-scaling policies.
7. Security & Monitoring – Payment data is handled securely, and system health is monitored closely with metrics and alerts.
8. Performance & Optimization – CDNs, caching, and efficient read/write partitioning were considered.
9. Trade-Offs & Alternatives – We discussed why certain technologies (SQL vs. NoSQL, monolith vs. microservices) were chosen.
10. Time Check & Summary – In a real interview, ensure you cover the entire design within the allocated time.