Scale a key-value store with consistent hashing

Q: Scale a key-value store with consistent hashing

This is a System Design interview question from SoFi for Software Engineer roles. View the full question and solution on PracHub.

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Question

System Design: Scale a Key–Value Store with Consistent Hashing

Context

You have a single-server key–value store that must scale horizontally across many servers while maintaining high availability and low latency. Assume point lookups/updates by key (no multi-key transactions), and tunable consistency is acceptable.

Tasks

Partition keys with consistent hashing, using virtual nodes (vnodes). Explain the hash ring, token assignment, and how clients/gateways route requests.
Describe node joins and leaves: how they trigger minimal data movement and how rebalancing works.
Define replication and quorum choices: pick N (replication factor), R (read quorum), W (write quorum), and justify trade-offs.
Specify read/write paths: coordinator behavior, conflict/version handling, and read repair.
Explain failure detection, re-replication, and recovery: membership, hinted handoff, anti-entropy, and rebuild.
Address hot keys, skew, and load balancing.
Ensure data migration safety during ownership changes; describe monitoring and rolling upgrades.
Compare alternatives (e.g., directory service, range partitioning) and justify trade-offs.

Deliver a diagram-free written design that covers the above with clear assumptions, pitfalls, and metrics/SLOs.

Scale a key-value store with consistent hashing

System Design: Scale a Key–Value Store with Consistent Hashing

Context

Tasks

Solution (Locked)

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