State Management and Data Flow Architecture Questions

Design and reasoning about where and how data is stored, moved, synchronized, and represented across the full application stack and in distributed systems. Topics include data persistence strategies in databases and services, application programming interface shape and schema design to minimize client complexity, validation and security at each layer, pagination and lazy loading patterns, caching strategies and cache invalidation, approaches to asynchronous fetching and loading states, real time updates and synchronization techniques, offline support and conflict resolution, optimistic updates and reconciliation, eventual consistency models, and deciding what data lives on the client versus the server. Coverage also includes separation between user interface state and persistent data state, local component state versus global state stores including lifted state and context patterns, frontend caching strategies, data flow and event propagation patterns, normalization and denormalization trade offs, unidirectional versus bidirectional flow, and operational concerns such as scalability, failure modes, monitoring, testing, and observability. Candidates should be able to reason about trade offs between latency, consistency, complexity, and developer ergonomics and propose monitoring and testing strategies for these systems.

MediumTechnical

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Design a contract-testing approach to ensure data shape compatibility between frontend clients and backend services. Explain how to automate tests, run them in CI, and publish contract changes so SREs can monitor rollouts and catch breaking changes before production.

HardSystem Design

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Cross-region cache invalidation: propose a robust design to invalidate or refresh caches across many regions when an authoritative write occurs. Consider ordering, at-least-once delivery, network partitions, and minimizing user-visible stale windows.

MediumSystem Design

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Design a system to enforce idempotency for mutating API requests in a distributed microservice architecture. Discuss how clients provide idempotency keys, how servers deduplicate, how keys are garbage-collected, and how this affects state reconciliation and retries across service boundaries.

MediumTechnical

0 practiced

You maintain caches replicated across two regions. Describe how you would detect and remediate cache coherency issues where a write in region A doesn't properly invalidate region B's cache, causing stale reads. Include monitoring, automated remediation, and what design choices prevent such failures.

MediumTechnical

0 practiced

Problem-solving: propose a strategy to prevent and handle cache stampedes for a highly-contended key that expires periodically. Include techniques like request coalescing, probabilistic early recomputation, and prewarming, and describe how you'd verify these techniques in production.

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