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Answer: Adopt a predictive scaling policy forecasting 60% CPU utilization, with pre-launch 30 minutes before jobs.
The best solution with the least operational overhead is to create a predictive scaling policy for the Auto Scaling group. Predictive scaling uses machine learning to forecast future traffic so that the correct number of EC2 instances can be pre-launched to handle the load efficiently, meeting the required CPU utilization target. Setting the policy to pre-launch instances 30 minutes before the jobs run aligns perfectly with the company's requirement to provision capacity in advance. Therefore, option C is the correct choice.
Author: LeetQuiz Editorial Team
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A company with weekly EC2 batch jobs in an Auto Scaling group seeks an automated solution to adjust capacity 30 minutes prior to job execution, given a consistent 60% CPU utilization. What is the most operationally efficient approach?
A
Implement a dynamic scaling policy based on CPU utilization at 60%.
B
Use a scheduled scaling policy with weekly timing, 30 minutes pre-execution.
C
Adopt a predictive scaling policy forecasting 60% CPU utilization, with pre-launch 30 minutes before jobs.
D
Set an EventBridge-triggered Lambda function to scale up at 60% CPU utilization.
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