Explanation:
AWS Compute Optimizer uses machine learning techniques to analyze historical utilization metrics and provides recommendations to optimize AWS compute resources, including Amazon EC2 instances, EBS volumes, and AWS Lambda functions. By reviewing the Compute Optimizer findings for EBS volumes, the SysOps administrator can efficiently identify over-provisioned volumes based on IOPS and throughput, and receive actionable recommendations without having to manually parse metrics or run custom benchmarking tools.
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Question 24. A company has users that deploy Amazon EC2 instances that have more disk performance capacity than is required. A SysOps administrator needs to review all Amazon Elastic Block Store (Amazon EBS) volumes that are associated with the instances and create cost optimization recommendations based on IOPS and throughput. What should the SysOps administrator do to meet these requirements in the MOST operationally efficient way?
A
Use the monitoring graphs in the EC2 console to view metrics for EBS volumes. Review the consumed space against the provisioned space on each volume. Identify any volumes that have low utilization.
B
Stop the EC2 instances from the EC2 console. Change the EC2 instance type for Amazon EBS-optimized. Start the EC2 instances.
C
Opt in to AWS Compute Optimizer. Allow sufficient time for metrics to be gathered. Review the Compute Optimizer findings for EBS volumes.
D
Install the fio tool onto the EC2 instances and create a .cfg file to approximate the required workloads. Use the benchmark results to gauge whether the provisioned EBS volumes are of the most appropriate type.
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