Data Management and Api Design Questions
Designing how applications structure, expose, and consume data through APIs and backend systems. Covers API design principles for data endpoints, pagination, filtering and sorting, idempotency, versioning, rate limiting, schema design, normalization versus denormalization, consistency models, caching strategies, client side fetching patterns, and error handling. Includes considerations for data integrity across integrations, transactional boundaries, master data management, and how API decisions affect downstream consumers and performance.
EasyTechnical
0 practiced
Compare client fetching patterns—polling, long-polling, Server-Sent Events (SSE), WebSockets—for keeping UI data fresh. For a dashboard that needs updates every 5-15 seconds for thousands of users, which approach would you choose and why?
HardSystem Design
0 practiced
Design a multi-tenant database approach for a SaaS product expected to host up to 10k tenants with diverse data volume. Compare strategies: separate database per tenant, shared schema with tenant_id, and hybrid approaches. Discuss tenant isolation, cross-tenant analytics, backup/restore, and migration complexity.
EasyTechnical
0 practiced
List common API versioning strategies (URI versioning, header-based, content negotiation) and discuss pros and cons for public versus internal APIs. Include how you'd communicate deprecations and handle rollbacks when a versioned change causes client failures.
MediumTechnical
0 practiced
Implement an in-memory idempotency key store in Python with methods put(key, response, ttl_seconds) and get(key). It must be thread-safe, support TTL-based eviction (lazy or periodic), and return the previous response if the same key is seen. Provide considerations for concurrency and extension to multi-process deployments.
HardSystem Design
0 practiced
Design a saga-based approach (or orchestration alternative) for a travel booking flow involving flight, hotel, and car reservations. Cover orchestrator responsibilities, compensation actions for each service, idempotency of saga steps, persistence of saga state, timeouts, and how to allow manual intervention in case of partial failures.
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