A company is running a MongoDB-compatible workload on Amazon DocumentDB. They are experiencing high write latency during peak hours. The current cluster has one instance (db.r5.large) with 100 GB storage. Which change is most likely to improve write performance?
A larger instance provides more CPU and memory, which can improve write performance.
Why this answer
Increasing the instance size to db.r5.xlarge provides more CPU and memory resources, which directly improves the cluster's ability to handle write operations under load. In Amazon DocumentDB, write performance is primarily bound by the instance's compute capacity (vCPUs and memory) for processing write requests and managing the storage engine's buffer cache. A larger instance reduces contention and allows more concurrent writes to be processed efficiently.
Exam trap
The trap here is that candidates often assume increasing storage or adding read replicas will improve write performance, but in DocumentDB, write throughput is limited by the primary instance's compute resources, not by storage size or read capacity.
How to eliminate wrong answers
Option A is wrong because increasing storage to 500 GB does not improve write throughput; DocumentDB storage is automatically scaled and write performance is not tied to storage size but to instance compute and I/O credits. Option B is wrong because enabling Multi-AZ deployment adds a standby replica for high availability but does not increase write capacity—the primary instance still handles all writes, and Multi-AZ can even add slight latency due to synchronous replication. Option D is wrong because adding a read replica in a different Availability Zone offloads read traffic but does not affect write performance on the primary instance; writes are still handled by the single primary instance.