CV0-004 Operations and Support Practice Question
A cloud engineer is investigating why a nightly batch job on Amazon EC2 takes far longer than expected. CloudWatch shows the instance's CPU and memory usage are low throughout the run, but the job performs many small reads against an Amazon EBS gp3 volume. The engineer wants to reduce the time the job spends waiting on storage. Which action should the engineer take?
⚠ Common exam trap
The trap here is seeing low CPU and assuming the fix is a bigger instance, when low CPU with high storage wait points to a volume IOPS limit instead.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Increase the provisioned IOPS and throughput settings of the gp3 volume to match the job's small-read workload.
The job is storage-bound, not compute-bound, and the read pattern is dominated by many small operations. On gp3, IOPS and throughput are provisioned separately from capacity, so raising the provisioned IOPS increases the rate of read operations the volume can sustain, cutting the wait time. Instance resizing, snapshot restore, and instance store do not correct the volume's operation rate.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Resize the instance to a larger instance type with more vCPUs so the job can issue more concurrent read requests.
Why it's wrong here
CPU and memory are already low, so the job is not compute-bound and adding vCPUs will not increase the number of I/O operations the volume can serve. The bottleneck is the storage device's operation rate, and a larger instance does not change the EBS volume's provisioned performance limits.
- ✗
Move the volume to an instance store device so reads are served from local NVMe storage.
Why it's wrong here
Instance store offers high performance but is ephemeral and is lost on stop, termination, or host failure, which is unacceptable for a job whose data must persist. It also requires the data to be copied, and the instance type must support instance store, so it is neither safe nor a direct fix for the provisioned IOPS limit.
- ✓
Increase the provisioned IOPS and throughput settings of the gp3 volume to match the job's small-read workload.
Why this is correct
gp3 volumes have independently configurable IOPS and throughput, and a workload dominated by many small reads is limited by IOPS rather than capacity. Raising provisioned IOPS lets the volume service more read operations per second, directly reducing the storage wait that is stretching the batch job's runtime while CPU and memory remain idle.
- ✗
Create a snapshot of the volume and restore it as a new volume, then reattach it to the instance.
Why it's wrong here
Snapshot and restore operations copy data and can be useful for migration or backup, but the resulting volume inherits the same performance configuration unless explicitly changed. This adds downtime and data movement without altering the IOPS ceiling, so the small-read wait would persist after the job resumes.
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official CompTIA exam blueprint
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