- A
Replace the io2 volumes with larger gp3 volumes and increase the volume size to 8,000 GB to benefit from gp3 baseline performance.
Why wrong: gp3 does not provide consistent low-latency high-IOPS for SAP HANA; io2 is recommended.
- B
Split the /hana/data volume into multiple io2 volumes, configure them as a RAID 0 stripe, and attach each to a separate EBS-optimized connection. Increase total provisioned IOPS to 80,000 distributed across volumes.
RAID 0 across multiple volumes increases aggregate IOPS and throughput, leveraging multiple EBS connections and avoiding single-volume limits.
- C
Migrate to a larger instance type with higher EBS-optimized bandwidth and increase the volume IOPS to 80,000.
Why wrong: Does not address single-volume bottleneck; still limited by single volume queue depth.
- D
Increase the provisioned IOPS on the existing io2 volume to 80,000 IOPS to stay within the default limit.
Why wrong: Single volume may still be bottlenecked; also 80,000 IOPS may exceed per-instance bandwidth.
Solving EBS IOPS Saturation for SAP HANA on AWS
This PAS-C01 practice question tests your understanding of design of sap workloads on aws. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A company runs its SAP S/4HANA production workload on AWS using an 8xlarge instance with 2,000 GB of gp3 storage for /usr/sap and 6,000 GB of io2 Block Express with 64,000 IOPS for /hana/data and /hana/log. The system experiences intermittent performance degradation during peak hours, particularly for batch jobs that heavily write to the database. The SAP team reports that the database response time spikes from under 5 milliseconds to over 200 milliseconds during these periods. The AWS account has a default EBS IOPS limit of 80,000 per region. The current io2 volume is attached as a single volume. Which combination of actions would 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
Split the /hana/data volume into multiple io2 volumes, configure them as a RAID 0 stripe, and attach each to a separate EBS-optimized connection. Increase total provisioned IOPS to 80,000 distributed across volumes.
Option B is correct because splitting the /hana/data volume into multiple io2 volumes and configuring them as a RAID 0 stripe distributes I/O across multiple EBS-optimized connections, effectively increasing the available throughput and IOPS beyond the limits of a single volume attachment. This approach also allows the total provisioned IOPS to reach 80,000, which is the regional default limit, while each individual volume stays within its own IOPS ceiling, thus resolving the database response time spikes during peak batch write operations.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Replace the io2 volumes with larger gp3 volumes and increase the volume size to 8,000 GB to benefit from gp3 baseline performance.
Why it's wrong here
gp3 does not provide consistent low-latency high-IOPS for SAP HANA; io2 is recommended.
- ✓
Split the /hana/data volume into multiple io2 volumes, configure them as a RAID 0 stripe, and attach each to a separate EBS-optimized connection. Increase total provisioned IOPS to 80,000 distributed across volumes.
Why this is correct
RAID 0 across multiple volumes increases aggregate IOPS and throughput, leveraging multiple EBS connections and avoiding single-volume limits.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
Migrate to a larger instance type with higher EBS-optimized bandwidth and increase the volume IOPS to 80,000.
Why it's wrong here
Does not address single-volume bottleneck; still limited by single volume queue depth.
- ✗
Increase the provisioned IOPS on the existing io2 volume to 80,000 IOPS to stay within the default limit.
Why it's wrong here
Single volume may still be bottlenecked; also 80,000 IOPS may exceed per-instance bandwidth.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates assume increasing IOPS on a single volume or moving to a larger instance alone will solve the performance issue, ignoring the fundamental single-volume throughput and IOPS ceiling that requires striping across multiple volumes to scale.
Detailed technical explanation
How to think about this question
Under the hood, SAP HANA requires high IOPS and low latency for /hana/data and /hana/log, and a single EBS volume is limited by the maximum IOPS per volume (64,000 for io2) and the EBS-optimized instance bandwidth per connection. By using RAID 0 across multiple io2 volumes, each attached to separate EBS-optimized connections (which the instance supports), the workload can achieve aggregate IOPS up to the regional limit (80,000) and higher throughput, as the I/O is load-balanced across multiple paths. In real-world scenarios, this striping is a recommended AWS best practice for SAP HANA to avoid single-volume bottlenecks during peak batch processing.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A media company stores terabytes of video archives that are accessed once a year for audit purposes. Moving these objects to a cold storage tier (Azure Archive, S3 Glacier, or Google Nearline) costs a fraction of hot storage. Questions like this test whether you understand storage tiers, access frequency tradeoffs, and retrieval latency requirements.
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 |
What to study next
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FAQ
Questions learners often ask
What does this PAS-C01 question test?
Design of SAP Workloads on AWS — This question tests Design of SAP Workloads on AWS — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Split the /hana/data volume into multiple io2 volumes, configure them as a RAID 0 stripe, and attach each to a separate EBS-optimized connection. Increase total provisioned IOPS to 80,000 distributed across volumes. — Option B is correct because splitting the /hana/data volume into multiple io2 volumes and configuring them as a RAID 0 stripe distributes I/O across multiple EBS-optimized connections, effectively increasing the available throughput and IOPS beyond the limits of a single volume attachment. This approach also allows the total provisioned IOPS to reach 80,000, which is the regional default limit, while each individual volume stays within its own IOPS ceiling, thus resolving the database response time spikes during peak batch write operations.
What should I do if I get this PAS-C01 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Same concept, more angles
2 more ways this is tested on PAS-C01
These questions test the same concept from different angles. Work through them to make sure you can recognise it however the exam phrases it.
Variation 1. A company is running an SAP HANA database on AWS using an i3.16xlarge instance. The database storage is configured with multiple EBS gp2 volumes in a RAID 0 stripe to meet IOPS requirements. During a workload spike, the application experiences increased latency and the database performance degrades. The CloudWatch metrics show high Average Queue Length (avg_queue_len) on the EBS volumes but not 100% utilization of the CPU. Which design change is MOST likely to resolve the performance issue?
medium- ✓ A.Replace gp2 volumes with io2 Block Express volumes to provide consistent IOPS performance.
- B.Move the database to an i3en.24xlarge instance to increase network and EBS bandwidth.
- C.Enable EBS optimization on the existing instance to improve throughput.
- D.Add two additional gp2 volumes to the RAID 0 stripe to increase throughput.
Why A: The high Average Queue Length indicates that the EBS volumes are saturating their IOPS capacity, causing requests to queue up. gp2 volumes have a burst-bucket model that can exhaust credits under sustained high I/O, leading to throttled performance. io2 Block Express volumes provide consistent, provisioned IOPS without burst limitations, directly resolving the queuing issue without requiring instance or stripe changes.
Variation 2. An SAP HANA database on AWS is using EBS gp3 volumes with 3000 IOPS. The database team observes that the write latency is high during peak hours. The EBS volume is not exceeding its bandwidth limit. What is the most likely cause?
hard- A.The EBS volume is not attached as a dedicated EBS bandwidth volume.
- ✓ B.The EBS volume's IOPS limit is being reached, causing queuing.
- C.The EC2 instance's EBS bandwidth is saturated.
- D.The EC2 instance does not have EBS optimization enabled.
Why B: The correct answer is B because the observed high write latency during peak hours, despite the EBS volume not exceeding its bandwidth limit, indicates that the volume's IOPS limit of 3000 is being reached. When the IOPS limit is hit, the EBS volume queues I/O requests, which increases latency. This is a classic symptom of IOPS saturation rather than bandwidth saturation.
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Last reviewed: Jun 11, 2026
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