How does eventual consistency affect data in distributed cloud storage?

How does eventual consistency affect data in distributed cloud storage?

• A. Reads always reflect the most recent writes immediately.
• B. Consistency guarantees are strong and immediate.
• C. Reads may not reflect the most recent writes immediately; design for idempotency and conflict resolution in apps.
• D. Writes are never visible to other regions.

Answer: (C)

Eventual consistency means updates propagate to all replicas asynchronously. Reads may return stale data because the latest write hasn’t reached every replica yet. Because of that, an operation in one region might not be visible immediately in another region. The practical approach is to design applications to be idempotent and capable of conflict resolution, since concurrent writes can create diverging versions that must be reconciled. Over time, as updates propagate and conflicts are resolved, all replicas converge to the same state. This trade-off favors availability and fault tolerance across distributed systems, at the cost of immediate consistency.

Eventual consistency means updates propagate to all replicas asynchronously. Reads may return stale data because the latest write hasn’t reached every replica yet. Because of that, an operation in one region might not be visible immediately in another region. The practical approach is to design applications to be idempotent and capable of conflict resolution, since concurrent writes can create diverging versions that must be reconciled. Over time, as updates propagate and conflicts are resolved, all replicas converge to the same state. This trade-off favors availability and fault tolerance across distributed systems, at the cost of immediate consistency.