Start by clarifying functional and non-functional requirements, then sketch a high-level architecture covering core services like product catalog, cart, and order management. Dive into data modeling and trade-offs for scalability, consistency, and availability, aligning with Amazon's leadership principles.
Pro tip: Emphasize decoupling services and using asynchronous communication to handle scale and failures gracefully, as Amazon values operational excellence and customer obsession.
Ask questions to define scope: user types, key features (search, cart, checkout, payments), scale (users, products, orders), and non-functional needs (latency, availability, consistency).
Outline major components: client apps, API gateway, microservices (product, cart, order, payment, inventory), databases, caches, and message queues. Draw a simple diagram.
Define core entities (User, Product, Order, Cart) and their relationships. Choose appropriate data stores (e.g., DynamoDB for cart, RDS for orders) and discuss sharding, replication, and consistency.
Pick 1-2 critical flows (e.g., checkout, inventory update) and discuss scalability, fault tolerance, and consistency trade-offs (e.g., eventual consistency vs. strong consistency).
Summarize key decisions, mention monitoring, logging, and metrics (e.g., latency, error rates), and suggest future improvements.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.