Distributed

etcd uses Raft to order changes to its replicated state. Replicas can temporarily lag; consensus does not mean every member holds identical bytes at every instant. A leader coordinates replication, while the voting majority determines progress. Keep election, commitment, local application, and client acknowledgment separate when diagnosing whether an operation succeeded. ...

Raft leader elections require a strict majority of the configured voting members. With fixed membership and one durable vote per server per term, two candidates cannot both win the same term: their majorities would overlap at a voter that cannot support both. This is an election guarantee, not a claim that every node always agrees about the current leader. ...

Gossip spreads information through repeated peer contact. It can tolerate some lost exchanges because surviving copies can be sent again. Eventual convergence still needs assumptions: relevant peers must become reachable, updates must remain available, and the merge rule must handle the states that can arise. Random contact alone does not guarantee agreement by a fixed deadline. ...

Consistent hashing limits placement changes when membership changes; it does not itself move data, make replicas agree, or distribute a hot key’s requests. In the classic clockwise ring, a key belongs to the first node point at or after its hash position, wrapping to the smallest point when necessary. ...

A vector records progress for each tracked participant. Comparing these counters distinguishes causal order from concurrency; the application still decides how to reconcile concurrent values. One timestamp is not enough A scalar timestamp can impose an order, but that order alone cannot prove causality. With stable participant identities and the usual event-clock rules, each process increments its own component for a local event. Receiving a message merges components by maximum and then increments the receiver’s component. These rules record information flow. They do not measure elapsed time or establish a physical-time ordering between machines that exchanged no information. ...

An idempotency key identifies one logical action only within a service’s defined scope and retention window. Reusing the same text is not a universal exactly-once guarantee. The service must associate that identity with the right principal and operation, coordinate competing attempts, and retain enough authoritative information to recognize the action later. ...