NOTE
1.9 Distributed Consistency
Why replicated distributed systems face consistency problems, how consistency models define observable guarantees, and how consensus algorithms help nodes agree on state.
This is a historical learning note and may contain outdated or incomplete understanding.
1. What Is Distributed Consistency?
Distributed consistency describes the guarantees a system provides when the same logical data is stored or processed across multiple nodes or replicas.
2. Why Does It Matter?
Distributed systems replicate data for fault tolerance and availability. Replication is not instantaneous: networks can be slow, messages can be reordered or lost, and nodes can fail. At a given moment, different replicas may therefore hold different versions of the same data.
A consistency model defines what differences clients are allowed to observe.