Spent the first few minutes just sketching out the class hierarchy before even thinking about concurrency.
Start by clarifying requirements and constraints, then design the core classes (Document, Tag, TagManager) with thread-safety in mind. Explain your concurrency strategy (e.g., fine-grained locking, concurrent collections) and discuss trade-offs between consistency, performance, and scalability.
Pro tip: Demonstrate awareness of Amazon's leadership principles by discussing how your design handles high concurrency and scales, and by explicitly calling out trade-offs (e.g., lock contention vs. consistency).
Ask about expected read/write ratios, consistency requirements, and scale to tailor the design. Confirm whether operations like adding/removing tags and searching by tags need to be thread-safe.
Define Document, Tag, and a manager (e.g., TagManager or DocumentStore) that maintains mappings. Consider whether Tag should be a separate entity or just a string, and how documents and tags relate (many-to-many).
Decide on synchronization mechanisms: synchronized methods, ReentrantReadWriteLock, ConcurrentHashMap, or immutable objects. Explain how you'll ensure atomicity for compound operations (e.g., adding a tag to a document and updating indexes).
Discuss deadlock avoidance, lock granularity, and performance under contention. Consider using read-write locks to allow concurrent reads, and mention alternatives like optimistic concurrency or lock-free data structures.
Outline the classes with their key fields and methods, annotating thread-safety guarantees. For example, Document with addTag/removeTag, TagManager with getDocumentsByTag, and how they synchronize.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Start by clarifying requirements and scale, then design the high-level architecture separating browsing (read-heavy, low consistency) and purchasing (write-heavy, strong consistency) workflows. Dive into data models, APIs, and trade-offs for scalability, availability, and consistency, and wrap up with bottleneck analysis and mitigation strategies.
Pro tip: Explicitly call out that browsing and purchasing have different consistency and latency requirements, and propose using separate data stores or read replicas for browsing to avoid impacting purchase transactions. This shows you understand real-world trade-offs at Amazon scale.
Ask questions to understand functional and non-functional requirements: expected traffic (e.g., millions of users), read/write ratio, consistency needs, and availability targets. Define core entities like books, users, carts, and orders.
Sketch a diagram with separate services for browsing (catalog, search) and purchasing (cart, order, payment). Use load balancers, CDN for static assets, and microservices for scalability.
Choose databases: NoSQL (e.g., DynamoDB) for product catalog and user sessions for scalability, and relational (e.g., Aurora) for orders and payments for ACID transactions. Discuss caching (Redis) and read replicas.
Define RESTful APIs for browsing (GET /books, GET /books/{id}) and purchasing (POST /cart, POST /orders). Discuss idempotency, rate limiting, and integration with payment gateways and inventory systems.
Explain how to scale each component (horizontal scaling, sharding, caching), ensure availability (multi-AZ, replication), and handle failures (circuit breakers, retries). Discuss trade-offs like consistency vs. latency.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.