PAS-C01 Design of SAP Workloads on AWS Practice Question
An SAP system on AWS is experiencing high write latency on the database layer. The DB is running on an r5.8xlarge instance with EBS gp2 volumes. The SAP team notices that the EBS volume write queue depth is frequently above 16. What is the MOST likely cause and what change should be made?
⚠ Common exam trap
Candidates often assume high write queue depth always requires switching to provisioned IOPS (io1/io2) or gp3, when in fact simply increasing gp2 volume size to raise baseline IOPS is the most direct and cost-effective fix for a small gp2 volume.
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
✓
The volume is too small for the workload. Increase the volume size to gain baseline IOPS.
Gp2 volume baseline IOPS scales linearly with size (3 IOPS per GiB). An r5.8xlarge instance supports EBS optimization, so the bottleneck is not the instance. With a write queue depth frequently above 16, the gp2 volume is likely too small to provide sufficient baseline IOPS, causing the queue to back up. Increasing the volume size raises the baseline IOPS, reducing queue depth and write latency.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The instance type does not support EBS optimization. Switch to a network-optimized instance.
Why it's wrong here
r5 instances support EBS optimization.
- ✗
The EBS volume is not optimized for SAP. Use io1 with high provisioned IOPS.
Why it's wrong here
Not necessarily needed; size increase may suffice.
- ✓
The volume is too small for the workload. Increase the volume size to gain baseline IOPS.
Why this is correct
Larger gp2 volumes have higher baseline IOPS, reducing queue depth.
- ✗
The gp2 volume does not provide enough burst IOPS. Migrate to gp3.
Why it's wrong here
gp3 may not solve burst credit depletion issue.
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