The prompt is intentionally vague and they want you to ask clarifying questions before touching the design.
Start by clarifying requirements and scope (e.g., single vs. multi-restaurant carts, real-time inventory, payment integration), then design a scalable, event-driven architecture that handles the cart lifecycle from creation to fulfillment. Focus on data consistency, idempotency, and low-latency updates, while discussing trade-offs and failure handling.
Pro tip: Emphasize idempotency and eventual consistency for cart mutations and checkout, as these are critical in distributed systems to avoid duplicate orders and ensure a smooth user experience.
Ask questions to understand functional and non-functional requirements, such as cart persistence, multi-device support, inventory checks, and expected scale. Define boundaries like whether carts are per restaurant or per user, and how fulfillment integrates.
Sketch the main components: API gateway, cart service, inventory service, pricing service, order service, and payment service. Choose a data store (e.g., Redis for active carts, DynamoDB for persistence) and communication patterns (sync REST for reads, async events for updates).
Define the cart state machine (created, active, checked out, abandoned) and the data model (cart ID, user ID, items, quantities, prices, status). Explain how to handle item additions, updates, and removals with idempotent operations.
Describe the checkout process: validate cart, lock inventory, calculate final price, process payment, and create order. Use idempotency keys to prevent duplicate orders and handle failures with retries and compensating transactions.
Discuss partitioning (e.g., by user ID), caching, and eventual consistency for cart updates. Address trade-offs between consistency and availability, and how to handle concurrent updates and race conditions.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Pretty natural once I had the requirements scoped.
Start by clarifying the requirements and access patterns, then propose a logical data model with separate tables for carts, cart items, and products. Explain how you would index to support the most frequent queries efficiently, and discuss trade-offs like consistency vs. availability and SQL vs. NoSQL choices.
Pro tip: Mention that you would consider using a composite index on (user_id, status) for active carts and (cart_id, product_id) for cart items, and highlight that you would avoid over-indexing to keep write performance acceptable.
Ask about expected read/write ratio, data volume, consistency needs, and the most common queries (e.g., fetch active cart, add/remove items, checkout).
Propose entities: User, Cart, CartItem, Product. Define relationships and key attributes, ensuring carts can be active or completed.
Decide between relational (e.g., PostgreSQL) or NoSQL (e.g., DynamoDB) based on scale and access patterns, and define tables/collections with appropriate primary keys.
Create indexes to support frequent queries: composite index on (user_id, status) for active carts, and index on cart_id for fetching items. Consider covering indexes for read-heavy paths.
Address write amplification from indexes, caching strategies (e.g., Redis for active carts), and how to handle cart expiration or archival.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Start by clarifying the requirements and constraints, such as consistency needs and scale. Then, propose a layered strategy: optimistic concurrency control with versioning at the application level, backed by database transactions and appropriate isolation levels. Finally, discuss trade-offs and alternatives like pessimistic locking or CRDTs for specific scenarios.
Pro tip: Mention that you would first try to avoid conflicts by designing the system to minimize shared mutable state, such as using a single writer per cart or partitioning by user. This shows you think about prevention, not just resolution.
Ask about consistency requirements (strong vs. eventual), expected concurrency level, and whether the cart is per-user or shared. This determines the appropriate solution.
Decide between optimistic and pessimistic approaches. For carts, optimistic concurrency with version numbers is often suitable due to low contention.
Use database transactions with appropriate isolation levels (e.g., serializable or snapshot isolation) and version checks in update statements to prevent lost updates.
Define conflict resolution: retry on version mismatch, merge changes, or notify the user. Ensure idempotent operations to avoid duplicate updates.
Compare with pessimistic locking (higher contention, lower throughput) and CRDTs (eventual consistency, complex merges). Choose based on business needs.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Correctness at checkout is the crux of the whole problem.
Start by framing the problem as a distributed transaction requiring idempotency and consistency. Propose a design that uses a unique checkout token or idempotency key to ensure exactly-once order creation, and validate cart state (e.g., items in stock, prices unchanged) within the same transaction or via a saga with compensating actions. Discuss trade-offs between strong consistency and availability, and how to handle failures and retries.
Pro tip: Emphasize that exactly-once is achieved through idempotent operations and deduplication, not by trying to prevent retries. Mention that you would use a database unique constraint on the idempotency key to enforce it at the storage layer.
Ask about scale, consistency requirements, and failure scenarios. Confirm that 'exactly once' means the order is created once even with retries, and that cart state must be valid (e.g., items available, prices correct) at conversion.
Generate a unique idempotency key (e.g., UUID) when the user initiates checkout. Store this key with the order attempt and use it to deduplicate requests. The client should send this key with every retry.
Within a transaction or using optimistic concurrency control, re-validate the cart: check inventory, prices, and promotions. If validation fails, abort and return an error; if it succeeds, proceed to order creation.
Use a database transaction to insert the order with the idempotency key as a unique constraint. If a duplicate key error occurs, fetch and return the existing order. This ensures exactly-once creation even with concurrent requests.
If order creation succeeds but downstream steps (e.g., payment) fail, use a saga pattern to compensate (e.g., cancel order, release inventory). Ensure the cart is not cleared until the order is confirmed.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.