- A
Increase the minimum and maximum instance count in the Auto Scaling group
Why wrong: Static changes do not dynamically handle peak hours efficiently.
- B
Configure a step scaling policy based on memory utilization
Why wrong: Memory utilization is not the best metric for scaling SAP app servers.
- C
Replace the Application Load Balancer with a Network Load Balancer
Why wrong: This does not address application server capacity.
- D
Change the Auto Scaling policy to use a target tracking policy based on CPU utilization
CPU utilization is a more relevant metric for SAP application server load.
Question 752 of 1,733
PAS-C01 Design of SAP Workloads on AWS Practice Question
This PAS-C01 practice question tests your understanding of design of sap workloads on aws. This is a configuration task: choose the command set that satisfies every stated requirement. Small differences — like 'secret' vs 'password' or 'transport input ssh' vs 'all' — change whether the answer is correct. 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 is running SAP ERP on AWS and notices performance degradation during peak hours. The application servers are in an Auto Scaling group behind an Application Load Balancer. Which configuration change would best handle the increased load?
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
✓
Change the Auto Scaling policy to use a target tracking policy based on CPU utilization
D is correct because SAP ERP workloads are typically CPU-bound during peak hours, and a target tracking policy based on CPU utilization automatically adjusts the Auto Scaling group to maintain a target CPU metric (e.g., 70%), ensuring the application servers scale out proactively to handle increased load without manual intervention. This approach aligns with SAP's recommended scaling strategy on AWS, as it directly addresses the performance degradation caused by high CPU demand.
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.
- ✗
Increase the minimum and maximum instance count in the Auto Scaling group
Why it's wrong here
Static changes do not dynamically handle peak hours efficiently.
- ✗
Configure a step scaling policy based on memory utilization
Why it's wrong here
Memory utilization is not the best metric for scaling SAP app servers.
- ✗
Replace the Application Load Balancer with a Network Load Balancer
Why it's wrong here
This does not address application server capacity.
- ✓
Change the Auto Scaling policy to use a target tracking policy based on CPU utilization
Why this is correct
CPU utilization is a more relevant metric for SAP application server load.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
The trap here is that candidates often assume increasing instance limits (Option A) or using memory-based scaling (Option B) is sufficient, but the exam tests understanding that SAP ERP is CPU-bound and requires a dynamic, metric-driven scaling policy like target tracking to effectively handle peak loads.
Detailed technical explanation
How to think about this question
Target tracking policies in AWS Auto Scaling use a proportional-integral-derivative (PID) control algorithm to continuously adjust the desired capacity, aiming to keep the specified metric (e.g., CPU utilization) at or near the target value, which is more stable and responsive than step scaling for bursty SAP workloads. Under the hood, the policy calculates the required number of instances based on the difference between the actual metric and the target, smoothing out oscillations that could occur with simple threshold-based policies. In a real-world scenario, an SAP ERP system running on AWS with a target tracking policy based on CPU utilization can scale from 2 to 20 instances within minutes during a month-end closing process, preventing performance degradation without over-provisioning.
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
An e-commerce site experiences heavy traffic on Black Friday and near-zero traffic during off-peak weeks. Rather than provisioning permanent large VMs, the team uses auto-scaling groups that add capacity automatically under load and reduce it overnight. Questions like this test whether you understand elasticity, availability zones, and cloud compute scaling patterns.
What to study next
Got this wrong? Here's your next step.
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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: Change the Auto Scaling policy to use a target tracking policy based on CPU utilization — D is correct because SAP ERP workloads are typically CPU-bound during peak hours, and a target tracking policy based on CPU utilization automatically adjusts the Auto Scaling group to maintain a target CPU metric (e.g., 70%), ensuring the application servers scale out proactively to handle increased load without manual intervention. This approach aligns with SAP's recommended scaling strategy on AWS, as it directly addresses the performance degradation caused by high CPU demand.
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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Last reviewed: Jul 4, 2026
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