A Company Runs a Memory-Intensive Analytics Application Using On-Demand Amazon

question 767

Multiple Choice

A company runs a memory-intensive analytics application using on-demand Amazon EC2 C5 compute optimized instance. The application is used continuously and application demand doubles during working hours. The application currently scales based on CPU usage. When scaling in occurs, a lifecycle hook is used because the instance requires 4 minutes to clean the application state before terminating. Because users reported poor performance during working hours, scheduled scaling actions were implemented so additional instances would be added during working hours. The Solutions Architect has been asked to reduce the cost of the application. Which solution is MOST cost-effective?

• A) Use the existing launch configuration that uses C5 instances, and update the application AMI to include the Amazon CloudWatch agent. Change the Auto Scaling policies to scale based on memory utilization. Use Reserved Instances for the number of instances required after working hours, and use Spot Instances to cover the increased demand during working hours.
• B) Update the existing launch configuration to use R5 instances, and update the application AMI to include SSM Agent. Change the Auto Scaling policies to scale based on memory utilization. Use Reserved instances for the number of instances required after working hours, and use Spot Instances with on-Demand instances to cover the increased demand during working hours.
• C) Use the existing launch configuration that uses C5 instances, and update the application AMI to include SSM Agent. Leave the Auto Scaling policies to scale based on CPU utilization. Use scheduled Reserved Instances for the number of instances required after working hours, and use Spot Instances to cover the increased demand during working hours.
• D) Create a new launch configuration using R5 instances, and update the application AMI to include the Amazon CloudWatch agent. Change the Auto Scaling policies to scale based on memory utilization. Use Reserved Instances for the number of instances required after working hours, and use Standard Reserved Instances with On-Demand Instances to cover the increased demand during working hours.

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