A company's solutions architect is evaluating an AWS workload that was deployed several years ago. The application tier is stateless and runs on a single large Amazon EC2 instance that was launched from an AMI. The application stores data in a MySQL database that runs on a single EC2 instance. The CPU utilization on the application server EC2 instance often reaches 100% and causes the application to stop responding. The company manually installs patches on the instances. Patching has caused downtime in the past. The company needs to make the application highly available. Which solution will meet these requirements with the LEAST development me? A. Move the application tier to AWS Lambda functions in the existing VPC. Create an Application Load Balancer to distribute traffic across the Lambda functions. Use Amazon GuardDuty to scan the Lambda functions. Migrate the database to Amazon DocumentDB (with MongoDB compatibility. B. Change the EC2 instance type to a smaller Graviton powered instance type. Use the existing AMI to create a launch template for an Auto Scaling group. Create an Application Load Balancer to distribute traffic across the instances in the Auto Scaling group. Set the Auto Scaling group to scale based on CPU utilization. Migrate the database to Amazon DynamoDB. C. Move the application tier to containers by using Docker. Run the containers on Amazon Elastic Container Service (Amazon ECS) with EC2 instances. Create an Application Load Balancer to distribute traffic across the ECS cluster. Configure the ECS cluster to scale based on CPU utilization. Migrate the database to Amazon Neptune. D. Create a now AMI that is configured with AWS Systems Manager Agent (SSM Agent). Use the new AMI to create a launch template for an Auto Scaling group. Use smaller instances in the Auto Scaling group. Create an Application Load Balancer to distribute traffic across the instances in the Auto Scaling group. Set the Auto Scaling group to scale based on CPU utilization. Migrate the database to Amazon Aurora MySQL.