An e-commerce backend handles product catalogs, shopping carts, order processing, payment integration, and inventory management. It’s one of the most common and complex system design problems — combining CRUD operations, transactional integrity, real-time stock updates, and payment processing.

E-commerce backends present unique challenges:

• Transactional integrity — Money and inventory must be accurate
• Concurrent access — Two users buying the last item simultaneously
• Catalog performance — Millions of products, fast faceted search
• Order lifecycle — Complex state machine with multiple services

Build a product catalog API:

• Products have: name, description, price, category, variants (size/color), images
• GET /products — paginated list with category filter, price sort, search
• GET /products/:id — single product with all variants
• GET /categories — category tree
• Add proper indexes for common queries (category, price range)

Build a shopping cart with checkout:

• POST /cart — add item (with variant selection)
• PUT /cart/:itemId — update quantity
• DELETE /cart/:itemId — remove item
• POST /checkout — create order, charge payment, clear cart
• Checkout uses a transaction: validate stock → charge → confirm order
• Handle the “last item” race condition

Build an order management system:

• Order states: pending → confirmed → processing → shipped → delivered
• Orders can be cancelled (before shipped) or returned (after delivery)
• GET /orders — user’s order history
• GET /admin/orders — all orders with filters (by status, date range)
• Admin can update order status
• Event-driven: order status changes trigger email notifications

Service	Responsibility	Technology
Product Service	Catalog, search, categories	MongoDB (flexible schema)
Cart Service	Temporary cart management	Redis (fast, TTL-based)
Order Service	Order processing, lifecycle	PostgreSQL (ACID)
Payment Service	Stripe integration	BullMQ (async, retries)
Inventory Service	Stock tracking	PostgreSQL + Redis
Notification Service	Emails, SMS	BullMQ worker

1. What database technology is best suited for a product catalog with flexible attributes?

• A) PostgreSQL (rigid schema)
• B) MongoDB (flexible schema) ✅
• C) Redis
• D) SQLite

2. How would you handle the “last item in stock” race condition when two users buy simultaneously?

• A) Optimistic locking with version check ✅
• B) Let both succeed
• C) Use a queue (too slow)
• D) Reject all concurrent purchases

3. What pattern is ideal for processing order payments asynchronously?

• A) HTTP callback
• B) Message queue with retries ✅
• C) Polling every second
• D) Inline payment processing

4. Why is Redis ideal for shopping cart storage?

• A) Relational queries
• B) Fast reads/writes with TTL-based expiration ✅
• C) Complex join operations
• D) Full-text search

5. What ensures data integrity during checkout (order creation + payment + inventory deduction)?

• A) Async processing
• B) Database transactions (ACID) ✅
• C) WebSocket notifications
• D) Redis caching

Answer Key: 1-B, 2-A, 3-B, 4-B, 5-B

• Working with Databases — Data modeling, transactions
• Message Queues — Async order processing
• Authentication — JWT for user sessions
• Caching — Product catalog caching
• Building REST APIs — API design patterns