Which solution will resolve these issues in the MOST operationally efficient way?
Replace the EC2 instances with T3 EC2 instances that run in an Auto Scaling group. Make the changes by using the AWS Management Console.
Modify the CloudFormation templates to run the EC2 instances in an Auto Scaling group. Increase the desired capacity and the maximum capacity of the Auto Scaling group manually when an increase is necessary.
Modify the CloudFormation templates. Replace the EC2 instances with R5 EC2 instances. Use Amazon CloudWatch built-in EC2 memory metrics to track the application performance for future capacity planning.
Modify the CloudFormation templates. Replace the EC2 instances with R5 EC2 instances. Deploy the Amazon CloudWatch agent on the EC2 instances to generate custom application latency metrics for future capacity planning.
Explanations:
While T3 instances are burstable and might handle occasional spikes in traffic, they may not provide the consistent performance required for a stateful application. Additionally, simply replacing instances without an Auto Scaling strategy could lead to performance issues as demand grows.
Modifying the CloudFormation templates to run instances in an Auto Scaling group is a step in the right direction, but manually increasing capacity as needed is not operationally efficient. This approach requires constant manual intervention and does not automatically respond to changing traffic patterns.
Although replacing instances with R5 instances may improve performance due to better memory handling, simply using built-in EC2 memory metrics from CloudWatch for future capacity planning is insufficient for immediate performance resolution. It does not provide operational efficiency in scaling to meet current demand.
This option offers a comprehensive solution. Replacing instances with R5 provides better memory capacity for a stateful application. Deploying the CloudWatch agent allows for custom latency metrics, enabling proactive monitoring and capacity planning, making the application more resilient and efficient in handling traffic.