A company runs a Cloud Spanner database with a multi-region configuration. They notice that write latency is higher than expected for clients in a region far from the leader region. What action should be taken to reduce write latency?
This places the leader in the nearest region, reducing write latency for that region.
Why this answer
Changing the default leader option to 'NEAREST' allows Cloud Spanner to dynamically assign the leader replica to the region closest to the majority of write requests, reducing the network round-trip time for clients far from the original leader region. This directly addresses the high write latency caused by geographic distance, as writes must be confirmed by the leader before committing.
Exam trap
The trap here is that candidates confuse directed reads (which reduce read latency) with leader placement options (which reduce write latency), or incorrectly assume that reducing replicas or using follower reads can improve write performance.
How to eliminate wrong answers
Option A is wrong because reducing the number of replicas does not reduce write latency; it may actually increase latency by reducing read availability and fault tolerance, and writes still require leader confirmation. Option B is wrong because directed reads are used to route read requests to the nearest replica for lower read latency, but they do not affect write latency, as writes must still go through the leader. Option D is wrong because follower reads are a read-only feature that allows reads from non-leader replicas; writes cannot be performed on followers, so enabling follower reads for writes is technically invalid.