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CAP Theorem and Consistency Models Questions

Understand the CAP theorem and how Consistency, Availability, and Partition Tolerance interact in distributed systems. Know different consistency models including strong consistency such as linearizability, eventual consistency, causal consistency, and session consistency, and how to apply them to different use cases. Be familiar with consensus protocols and distributed coordination primitives such as Raft and Paxos, quorum reads and writes, two phase commit and when to use them. Understand trade offs between consistency and availability under network partitions, patterns for hybrid approaches where different data uses different guarantees, and the product and developer experience implications such as latency, stale reads, and API contract clarity.

HardTechnical
0 practiced
Describe how 'read-your-writes' session consistency can be implemented using logical clocks. How would you ensure the approach works across a set of stateless front-end servers that proxy requests to regional databases?
MediumTechnical
0 practiced
Explain how vector clocks can be used for conflict detection and why they do not always provide a deterministic conflict resolution. Discuss how you would integrate vector clocks with application-level merge logic.
MediumSystem Design
0 practiced
Design an API contract for a write endpoint used by mobile clients where network partitions are common. The contract must make consistency guarantees explicit to client developers and include guidance on idempotency, retries, and expected latency. Provide key fields and statuses you would include in the API response.
MediumSystem Design
0 practiced
A distributed database offers tunable consistency where clients pick R and W at request time. How would you design a default client library that chooses sensible R/W values for common workloads (analytics, user-profiles, transactions) while exposing knobs for advanced users?
HardSystem Design
0 practiced
A global event-sourcing system must ensure total ordering of events for a given aggregate while remaining highly available. Propose an architecture that balances these requirements, explaining how you would enforce per-aggregate ordering and what happens during partitions.

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