PAS-C01 Instance Sizing for SAP HANA Practice Question
A company runs its SAP ERP system on AWS using SAP HANA as the database. The HANA database is deployed on an EC2 instance with 488 GiB of memory. The system has been running for months, but recently the application team reported that some queries are taking significantly longer than usual. The operations team checks the CloudWatch metrics and sees that the database instance's CPU utilization is consistently above 90% during peak hours. They also notice that the EBS volume used for HANA data files has a read latency of over 20 ms. The volume is a gp3 volume with 16,000 IOPS. The instance type is an x1e.8xlarge. The team suspects that the instance is not optimized for the workload. What should they do to resolve the performance issue?
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
✓
Replace the instance with an x1e.16xlarge instance to increase CPU and memory capacity.
The x1e.8xlarge instance provides 4 vCPUs and 488 GiB of memory, which are insufficient for the workload causing consistently high CPU utilization. Upgrading to an x1e.16xlarge instance increases vCPUs to 8 and memory to 976 GiB, directly addressing the CPU bottleneck and memory pressure. The high EBS read latency may be a secondary effect of the overloaded instance, and additional capacity can help alleviate storage performance issues. Option A is incorrect because changing to gp2 with a larger size does not guarantee lower latency and does not address the CPU constraint. Option B is incorrect because increasing IOPS on the gp3 volume only addresses storage performance, not the compute bottleneck. Option D is incorrect because EBS optimization is enabled by default on x1e instances; there is no additional setting to toggle.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Change the EBS volume type to gp2 with a larger size.
Why it's wrong here
Changing to gp2 with a larger size does not guarantee lower read latency and does not address the high CPU utilization, which is the primary bottleneck.
- ✗
Increase the gp3 volume IOPS to 32,000 to reduce read latency.
Why it's wrong here
Increasing gp3 volume IOPS to 32,000 can reduce read latency, but this does not resolve the CPU constraint; the instance resources remain insufficient.
- ✓
Replace the instance with an x1e.16xlarge instance to increase CPU and memory capacity.
Why this is correct
Upgrading to x1e.16xlarge provides double the vCPUs and memory (976 GiB), directly addressing the CPU bottleneck and providing more memory for HANA, even though the stated 2 TB memory requirement cannot be met by any x1e instance. This is the best option among those provided.
- ✗
Enable EBS optimization on the EC2 instance.
Why it's wrong here
EBS optimization is already enabled by default on x1e instances, so toggling it would have no effect on the performance issue.
Visual reference
Quick reference
AWS S3 Storage Class Comparison
| Storage Class | Min Duration | Retrieval | Use Case |
|---|---|---|---|
| S3 Standard | None | Immediate | Frequently accessed data |
| S3 Standard-IA | 30 days | Immediate | Infrequent access, rapid retrieval |
| S3 One Zone-IA | 30 days | Immediate | Non-critical infrequent data |
| S3 Intelligent-Tiering | None | Immediate–hours | Unknown or changing access patterns |
| S3 Glacier Instant | 90 days | Milliseconds | Archive with instant retrieval |
| S3 Glacier Flexible | 90 days | Minutes–hours | Archive, flexible retrieval |
| S3 Glacier Deep Archive | 180 days | Hours | Long-term compliance archive |
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
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