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Distributed Systems Fundamentals
System & ML-System Design

Distributed Systems: Consistent Hashing, Replication, and Partitioning

TechnicalMedium~30 minDesigned by experts

About this interview

A technical interview on Distributed Systems Fundamentals, pitched at the medium level. A voice AI interviewer leads the conversation, adapts its questions to your answers, keeps you on topic, and afterward gives you honest, specific feedback on where you were strong and where to improve. Expect roughly 30 minutes.

What you'll be assessed on

Explain consistent hashing, virtual nodes, and how they minimize data movement during cluster changes
Describe replication strategies (leader-follower, quorum, leaderless) and their consistency guarantees
Reason through partition strategies (range vs. hash) and common pitfalls such as hot spots
Explain the role of gossip protocol and failure detectors in maintaining cluster membership

Topics covered

Consistent Hashing MotivationConsistent Hashing FundamentalsConsistent Hashing Ring MechanicsVirtual NodesConsistent Hashing InternalsPartition StrategiesPartition Hot SpotsReplication StrategiesReplication LagQuorum ConsistencyReplication + Consistent Hashing IntegrationConflict Detection and ResolutionFailure HandlingGossip Protocol and Failure Detection

A few sample questions

Just examples to set expectations - the real interview has many more and adapts to your responses.

Why does simple modulo hashing break down when you add or remove a server from a cluster?
What is synchronous versus asynchronous replication, and what does each guarantee about durability and read freshness after a write?
A node receives a heartbeat saying another node is down. Should it immediately mark that node as failed? What rule do systems like Cassandra use, and why?

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