An enterprise runs 103 line-of-business applications on virtual machines in an on-premises data center. Many of the applications are simple PHP. Java, or Ruby web applications, are no longer…

Deploying 103 separate AWS Elastic Beanstalk environments, even single-instance ones, would likely provision dedicated resources for each application, leading to higher overall infrastructure costs than a consolidated container approach.

Using AWS SMS to create AMIs and then running each application on its own dedicated Amazon EC2 instance would result in a one-to-one mapping, leading to 103 separate EC2 instances, which is not the lowest cost option for many low-traffic applications.

Converting each application to a Docker image and deploying them to a small Amazon ECS cluster behind a load balancer enables multiple low-traffic applications to share underlying compute resources efficiently, which significantly reduces the total number of EC2 instances and associated infrastructure costs compared to dedicated instances per application.

Similar to option B, using VM Import/Export and running each application on a dedicated single-instance EC2 virtual machine would be a costly approach, as it would require 103 separate instances instead of consolidating them onto shared infrastructure.