Require N/2+1 nodes to agree on every operation, so the system stays consistent even when some nodes are down.
Set the write and read quorums. Watch whether they overlap.
Across N replicas, a write waits for W acks and a read queries R. If W + R > N, the two sets must share a node, so a read always sees the newest write. Tune W and R to trade write speed against read freshness.
Plain English: when you have 5 copies of the data, don't trust any single one. Require at least 3 of them to agree on every read and every write. That way you can lose any 2 machines and the survivors still tell the truth.
A consensus mechanism for distributed systems: an operation is considered successful only if a majority of nodes agree. Variants: read quorum (R), write quorum (W), total replicas (N). The classic rule R+W>N guarantees read-your-writes.
In a distributed system, nodes can fail or be partitioned. If you require all nodes to agree, any single failure halts you. If you require only one, you risk split-brain (two halves of a partition both claiming to be authoritative). A quorum strikes a balance: tolerate up to N/2 failures while staying consistent.
On write, send to N replicas; wait for W acks before returning success. On read, query R replicas; the value with the latest version wins. If R+W>N, any read overlaps with any write, so you always see the latest committed value. Used by Raft, Paxos, Dynamo, and Cassandra (with tunable consistency levels).
Cassandra writes typically use a quorum consistency level for the message store
ZooKeeper / etcd for ring membership uses quorum-based consensus
A 43-second network partition triggered 24 hours of data inconsistency.
A 43-second network partition between GitHub's US-East and US-West data centers caused MySQL clusters in both regions to elect themselves primary (split-brain). When the partition healed, both regions had accepted writes and now had divergent state. GitHub chose consistency over availability: they took the service degraded for 24+ hours while they manually reconciled the diverged writes across clusters. The lesson: CAP isn't a textbook curiosity. When the partition heals, you've already made the C-vs-A choice. Your reconciliation strategy IS your CAP choice expressed in code.
Quorum comes up in any discussion of replicated systems with no single leader (Cassandra, DynamoDB). The interviewer wants you to show you understand R+W>N: if your reads and writes each touch a majority, they always overlap and you never read stale data. Be ready to say how you'd tune W and R for your workload. Candidates lose points by conflating quorum with 'all replicas must respond,' which is not quorum, that's synchronous replication.