E-commerce Platform System Design Example

High-Level System Design

1. Architecture Overview:

   • Microservices Architecture: Separate services for user management, product catalog, inventory, etc., to ensure scalability and flexibility.
   • Load Balancer: Distributes user requests across multiple servers to handle high traffic efficiently.
   • Database:
     • Relational DB (e.g., PostgreSQL): For structured data such as user profiles, orders, and transactions.
     • NoSQL DB (e.g., MongoDB): For product catalog, reviews, and other semi-structured data.
   • Content Delivery Network (CDN): To cache and deliver static assets like product images and CSS files.

2. Key Components and Their Interactions:

   • User Management System:
     • Handles user registration, login/logout, and session management.
     • Implements JWT for authentication and secure APIs.
   • Product Catalog:
     • Stores and indexes product details such as titles, descriptions, images, and prices.
     • Uses Elasticsearch for fast and efficient search and filtering.
   • Shopping Cart:
     • A user-specific service with a temporary store for selected products.
     • Syncs with the inventory system to validate stock availability.
   • Checkout System:
     • Handles order validation, calculates taxes/shipping, and integrates with the payment gateway.
   • Payment Gateway:
     • Supports secure transactions (credit cards, UPI, wallets).
     • Ensures PCI DSS compliance for data security.
   • Order Management System:
     • Manages the lifecycle of an order: placement, shipping, and returns.
     • Integrates with third-party logistics for delivery tracking.
   • Recommendation Engine:
     • Implements machine learning models to suggest products based on browsing and purchase history.
   • Inventory Management:
     • Tracks stock levels and triggers alerts for low inventory.
     • Syncs with the product catalog to prevent overselling.
   • Search Service:
     • Utilizes full-text search engines (e.g., Elasticsearch) for user queries.
   • Content Delivery Network (CDN):
     • Speeds up delivery of product images, videos, and other static assets.

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Low-Level Design for Selected Components

1. Shopping Cart Service:

   • Database Schema:

     CREATE TABLE ShoppingCart (
       cart_id SERIAL PRIMARY KEY,
       user_id INT NOT NULL,
       product_id INT NOT NULL,
       quantity INT NOT NULL,
       added_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
     );
     

   • APIs:

     • Add Item to Cart: Validates product availability and adds it to the cart.
     • Update Quantity: Adjusts quantity and validates stock.
     • Remove Item from Cart: Deletes product from the cart.

2. Product Search:

   • Indexing:
     • Use Elasticsearch to index product details like name, category, price, and description.

   • Query Structure:

     • Support keyword search, price range filters, and sorting (e.g., relevance, popularity).

     {
       "query": {
         "bool": {
           "must": [
             { "match": { "name": "laptop" } }
           ],
           "filter": [
             { "range": { "price": { "gte": 30000, "lte": 60000 } } }
           ]
         }
       }
     }
     

3. Recommendation Engine:

   • Algorithm:
     • Use collaborative filtering or content-based filtering models.
   • Data Pipeline:
     • Collect clickstream data, purchase history, and user ratings.
     • Use tools like Apache Kafka and Apache Spark for data streaming and processing.

4. Payment System:

   • Flow:
     • Client sends payment details → API Gateway forwards to the payment provider → Provider validates and processes payment.
   • Security:
     • Encrypt sensitive data with TLS.
     • Tokenize card details for future use (PCI DSS compliance).

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Challenges and Solutions

1. Scalability During Peak Sales:

   • Solution: Use autoscaling and distributed systems to handle traffic spikes.
   • Implement read replicas in databases to reduce bottlenecks.

2. Ensuring Secure Transactions:

   • Solution: Enforce strong encryption, tokenization, and adhere to compliance standards like PCI DSS.
   • Integrate fraud detection systems to monitor suspicious activities.

3. Maintaining Accurate Inventory Data:

   • Solution: Use event sourcing for real-time updates to stock levels.
   • Implement locking mechanisms to avoid race conditions in multi-user scenarios.

4. Handling Millions of Search Queries Efficiently:

   • Solution: Use Elasticsearch for full-text search and horizontal scaling.
   • Cache popular search results using Redis or Memcached.

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Final System Workflow Example

1. User logs in (User Management System authenticates via JWT).
2. User searches for a product (Search Service retrieves data from Elasticsearch).
3. User adds items to the cart (Shopping Cart Service syncs with Inventory Management).
4. User proceeds to checkout (Checkout System validates and calculates order details).
5. User pays via Payment Gateway (transaction is secured and logged).
6. Order is placed (Order Management System tracks progress).
7. Recommendation Engine suggests similar products.