PAS-C01 Design of SAP Workloads on AWS Practice Question
A company runs SAP Business Suite on an SAP HANA database on AWS. The database uses EBS gp2 volumes. The operations team notices high latency during peak hours. The metrics show that the volume queue depth is consistently above the recommended threshold. What is the MOST cost-effective change to reduce latency?
⚠ Common exam trap
Candidates often assume Provisioned IOPS (io1/io2) is always the solution for high latency, but they overlook the cost-effective burst capability of gp2 volumes when increased in size.
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 size of the existing EBS gp2 volume to a larger size.
Increasing the size of an existing gp2 volume is the most cost-effective solution because gp2 volumes have a baseline performance of 3 IOPS per GB, and they can burst up to 3,000 IOPS for volumes up to 1,000 GB. By increasing the volume size, you raise the baseline IOPS, which reduces the queue depth without incurring the higher per-GB cost of io1 or io2 volumes. This directly addresses the high latency caused by queue depth exceeding the recommended threshold during peak hours.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Migrate from gp2 to io2 EBS volumes with the same size.
Why it's wrong here
io2 is more expensive per GB; gp2 size increase is more cost-effective.
- ✗
Modify the volume to use Provisioned IOPS (io1) with a higher IOPS value.
Why it's wrong here
Provisioned IOPS incurs additional cost; increasing gp2 size is cheaper.
- ✗
Add an additional EBS volume and stripe the volumes using LVM.
Why it's wrong here
Adding a volume and striping with LVM increases total IOPS and throughput capacity, but it does not reduce latency when the existing volume queue depth is already high. The bottleneck is not insufficient aggregate performance; it is the per-volume I/O queue exceeding the gp2 burst balance or baseline, causing queuing delay. This option is tempting because LVM striping is effective for scaling throughput in workloads with balanced I/O distribution, such as sequential writes, where multiple volumes share the load.
- ✓
Increase the size of the existing EBS gp2 volume to a larger size.
Why this is correct
Larger gp2 volumes have higher baseline IOPS, reducing queue depth.
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