The answer is to enable the ECS service to publish custom CloudWatch metrics for memory utilization, then create a target tracking scaling policy based on that metric. This is correct because ECS Fargate does not natively emit memory utilization to CloudWatch; you must configure the task definition to send custom metrics via the CloudWatch agent or a script. Once the metric is available, Application Auto Scaling can use a target tracking policy to automatically adjust the desired task count, preventing out-of-memory errors during spikes. On the AWS Certified SAP on AWS Specialty PAS-C01 exam, this scenario tests your understanding of the distinction between CPU (which is built-in) and memory (which requires custom metrics) for Fargate auto scaling. A common trap is assuming the ECS service automatically provides memory metrics—it does not. Remember the mnemonic: “CPU is free, memory costs custom metrics.”
PAS-C01 Operations and Maintenance Practice Question
This PAS-C01 practice question tests your understanding of operations and maintenance. Match the stated requirement to the specific cloud service, access model, or configuration option — many options are valid in isolation but not for this scenario. 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 a web application on Amazon ECS with Fargate launch type. The application's memory utilization spikes periodically, causing tasks to be killed. The operations team wants to automatically scale the service based on memory usage. Which THREE steps are necessary to implement this?
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Create an Application Auto Scaling target tracking scaling policy based on memory utilization.
Option B is correct because Application Auto Scaling with a target tracking scaling policy allows the ECS service to automatically adjust its desired count based on a CloudWatch metric, such as memory utilization. This ensures the service scales out when memory usage spikes and scales in when it drops, preventing tasks from being killed due to OOM (out-of-memory) errors.
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.
✗
Attach an EC2 Auto Scaling group to the ECS service to handle capacity.
Why it's wrong here
Fargate manages underlying infrastructure; no EC2 needed.
✓
Create an Application Auto Scaling target tracking scaling policy based on memory utilization.
Read the scenario before looking for a memorised answer.
✗
Configure step scaling policies to add multiple tasks at once.
Why it's wrong here
Target tracking is simpler and sufficient; step scaling is optional.
✓
Create a CloudWatch alarm that triggers the scaling policy when memory exceeds a threshold.
Why this is correct
Alarm is required to send the metric breach to the scaling policy.
Related concept
Read the scenario before looking for a memorised answer.
✓
Enable the ECS service to publish custom CloudWatch metrics for memory utilization.
Why this is correct
Memory utilization is not published by default; must be enabled via the ECS agent.
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 confuse the need for EC2 Auto Scaling groups with Fargate, or assume step scaling is required for memory-based scaling, when in fact target tracking is the recommended and simpler approach for metric-based auto scaling.
Detailed technical explanation
How to think about this question
Under the hood, ECS services with Fargate publish memory utilization metrics to CloudWatch via the ECS agent (for EC2 launch type) or via the AWS-provided container insights. For Fargate, you must enable the 'EnableCloudWatchLogs' and 'EnableContainerInsights' settings to publish custom metrics like memory utilization. The target tracking policy then uses these metrics to calculate the desired task count using a proportional-integral-derivative (PID) control algorithm, ensuring smooth scaling without oscillation.
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.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Operations and Maintenance — This question tests Operations and Maintenance — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: Create an Application Auto Scaling target tracking scaling policy based on memory utilization. — Option B is correct because Application Auto Scaling with a target tracking scaling policy allows the ECS service to automatically adjust its desired count based on a CloudWatch metric, such as memory utilization. This ensures the service scales out when memory usage spikes and scales in when it drops, preventing tasks from being killed due to OOM (out-of-memory) errors.
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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This PAS-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the PAS-C01 exam.
Question Discussion
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