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Answer: 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.
Answer D is the most cost-effective solution for the given scenario. Here's why: 1. **Instance Type**: The solution recommends using R5 instances, which are memory-optimized instances. Since the application is memory-intensive, R5 instances would be a better fit than the compute-optimized C5 instances mentioned in other options. This change aligns with the application's resource requirements, potentially improving performance and efficiency. 2. **Application AMI Update**: Including the Amazon CloudWatch agent in the AMI allows for better monitoring and management of the instances. CloudWatch can provide detailed metrics and alarms that can be used to trigger scaling actions based on memory utilization, which is more appropriate for a memory-intensive application than CPU-based scaling. 3. **Auto Scaling Policy**: Changing the Auto Scaling policy to scale based on memory utilization instead of CPU usage is crucial for this application. Since the application is memory-intensive, scaling based on memory usage will ensure that the application has enough memory to perform optimally, which can help address the performance issues reported by users during working hours. 4. **Instance Purchasing Strategy**: The solution suggests using Reserved Instances for the base capacity required after working hours. Reserved Instances provide significant cost savings over On-Demand Instances when used for a significant portion of the year. For the additional capacity needed during working hours, the solution recommends using Standard Reserved Instances combined with On-Demand Instances. This approach ensures that the company can handle the increased demand during peak hours without incurring the full cost of additional Reserved Instances. 5. **Lifecycle Hook**: The existing use of a lifecycle hook to allow instances to clean the application state before terminating is a good practice and is not affected by the change in the solution. It ensures that the application state is properly managed during the scaling-in process. By implementing these changes, the company can reduce costs while maintaining or improving the performance of their memory-intensive analytics application during peak demand periods.
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A company runs a memory-intensive analytics application using on- demand Amazon EC2 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 work 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.