Why it matters
Consistent hashing is core distributed systems knowledge. It appears in load balancers, caches, and databases. Understanding it explains rebalancing behavior across many systems.
The architecture
Ring: values 0 to 2^32 - 1 (or similar). Both keys and node identifiers hash to positions on the ring. A key belongs to the first node clockwise from its position.
Adding a node: only keys between the new node and its predecessor move. Removing a node: keys move to the successor.
How it works end to end
Virtual nodes: each real node gets many (200-1000) virtual positions on the ring. This smooths distribution and lets you weight nodes (bigger nodes get more virtual positions).
Rendezvous hashing (HRW): alternative that computes hash(key, node) for each node and picks max. Simpler for small clusters, better distribution guarantees.
Applications: caching layers (avoid mass invalidation on scale change), distributed databases (partition assignment), load balancers (sticky sessions).