- A
Configure an Auto Scaling group with a scaling policy based on a custom CloudWatch metric for memory utilization.
Correct. An Auto Scaling group with a scaling policy based on a custom CloudWatch metric for memory utilization will automatically launch a new instance when memory exceeds 80%.
- B
Create a CloudWatch alarm that sends an email to the administrator to manually launch a new instance.
Why wrong: Incorrect. A CloudWatch alarm that sends an email only notifies the administrator; it does not automatically add instances, requiring manual intervention.
- C
Use an Auto Scaling group with a scaling policy based on CPU utilization.
Why wrong: Incorrect. Auto Scaling based on CPU utilization does not directly address high memory usage; memory issues may not be resolved by scaling on CPU.
- D
Use AWS Elastic Beanstalk to deploy the application server.
Why wrong: Incorrect. AWS Elastic Beanstalk is for deploying web applications, not a solution for adding application servers based on memory utilization in a custom SAP cluster.
Auto Scaling EC2 Instances Based on Memory Utilization
This PAS-C01 practice question tests your understanding of operations and maintenance. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. A key principle to apply: auto Scaling Group. 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.
An SAP administrator notices that the SAP application server is experiencing high memory utilization. The system uses a cluster of EC2 instances. What is the most cost-effective solution to automatically add an additional application server when memory exceeds 80%?
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
Configure an Auto Scaling group with a scaling policy based on a custom CloudWatch metric for memory utilization.
Option A is correct because Auto Scaling groups can use custom CloudWatch metrics (e.g., memory utilization) via the CloudWatch Agent to trigger scaling actions. This automates adding instances when memory exceeds 80% without manual intervention. Option B is incorrect because it only sends an email for manual action, which is not automatic nor cost-effective. Option C is incorrect because it scales based on CPU, not memory, so it does not address the memory issue. Option D is incorrect because Elastic Beanstalk is a PaaS service that abstracts infrastructure, but it does not provide a simple way to scale based on memory utilization, and it is not specifically designed for SAP application server clusters.
Key principle: Auto Scaling Group
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Configure an Auto Scaling group with a scaling policy based on a custom CloudWatch metric for memory utilization.
Why this is correct
Correct. An Auto Scaling group with a scaling policy based on a custom CloudWatch metric for memory utilization will automatically launch a new instance when memory exceeds 80%.
Related concept
Auto Scaling Group
- ✗
Create a CloudWatch alarm that sends an email to the administrator to manually launch a new instance.
Why it's wrong here
Incorrect. A CloudWatch alarm that sends an email only notifies the administrator; it does not automatically add instances, requiring manual intervention.
- ✗
Use an Auto Scaling group with a scaling policy based on CPU utilization.
Why it's wrong here
Incorrect. Auto Scaling based on CPU utilization does not directly address high memory usage; memory issues may not be resolved by scaling on CPU.
- ✗
Use AWS Elastic Beanstalk to deploy the application server.
Why it's wrong here
Incorrect. AWS Elastic Beanstalk is for deploying web applications, not a solution for adding application servers based on memory utilization in a custom SAP cluster.
Common exam traps
Common exam trap: answer the scenario, not the keyword
A common pitfall is assuming that CPU utilization is the only metric available for Auto Scaling. Memory utilization requires a custom CloudWatch metric, which must be published from the instances using the CloudWatch agent.
Detailed technical explanation
How to think about this question
Treat this as a scenario question. Identify the problem, the constraint, and the best action. Then compare each option against those facts.
KKey Concepts to Remember
- Auto Scaling Group
- Custom CloudWatch Metric
- CloudWatch Agent
- Memory Utilization Scaling Policy
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
Auto Scaling Group
Real-world example
How this comes up in practice
A startup's cloud architect reviews their monthly bill and notices costs are higher than expected for a long-running batch job. Switching from on-demand instances to Reserved Instances — or using Spot/Preemptible VMs — can reduce compute costs by up to 72 %. Questions like this test whether you understand the tradeoffs between commitment, flexibility, and cost across cloud pricing models.
What to study next
Got this wrong? Here's your next step.
Review auto Scaling Group, then practise related PAS-C01 questions on the same topic to reinforce the concept.
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FAQ
Questions learners often ask
What does this PAS-C01 question test?
Operations and Maintenance — This question tests Operations and Maintenance — Auto Scaling Group.
What is the correct answer to this question?
The correct answer is: Configure an Auto Scaling group with a scaling policy based on a custom CloudWatch metric for memory utilization. — Option A is correct because Auto Scaling groups can use custom CloudWatch metrics (e.g., memory utilization) via the CloudWatch Agent to trigger scaling actions. This automates adding instances when memory exceeds 80% without manual intervention. Option B is incorrect because it only sends an email for manual action, which is not automatic nor cost-effective. Option C is incorrect because it scales based on CPU, not memory, so it does not address the memory issue. Option D is incorrect because Elastic Beanstalk is a PaaS service that abstracts infrastructure, but it does not provide a simple way to scale based on memory utilization, and it is not specifically designed for SAP application server clusters.
What should I do if I get this PAS-C01 question wrong?
Review auto Scaling Group, then practise related PAS-C01 questions on the same topic to reinforce the concept.
What is the key concept behind this question?
Auto Scaling Group
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
Same concept, more angles
1 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. An SAP system is experiencing high CPU utilization on the application server. The administrator wants to automatically scale the EC2 instance based on CPU usage. Which AWS service should be used?
medium- A.Elastic Load Balancing
- ✓ B.AWS Auto Scaling
- C.AWS Lambda
- D.Amazon CloudWatch
Why B: Auto Scaling with scaling policies based on CloudWatch alarms can automatically adjust the number of instances. Option B is correct. Option A is wrong because Elastic Load Balancing distributes traffic, not scaling. Option C is wrong because Lambda can be used but is not the primary service for EC2 scaling. Option D is wrong because CloudWatch monitors but does not scale.
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Last reviewed: Jun 20, 2026
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