AWS Certified Solutions Architect – Professional — Question 763

A company has PHP applications that run in containers and also has a MySQL database. The company wants to move the applications and the database from on premises to AWS. The company has millions of users and will need to manage shared application data between the containers.

The company needs a solution that will minimize operational overhead and cost. The solution also must be scalable and highly available.

Which solution will meet these requirements?

Answer options

• A. Deploy containers on Amazon Elastic Container Service (Amazon ECS). Set up the containers to run the tasks on Amazon EC2 instances. Choose Amazon Elastic File System (Amazon EFS) as the volume type. Deploy an Amazon RDS Multi-AZ DB instance with read replicas as the database solution.
• B. Deploy containers on Amazon Elastic Container Service (Amazon ECS). Set up the containers to run the tasks on AWS Fargate. Choose Amazon Elastic File System (Amazon EFS) as the volume type. Deploy Amazon Aurora Serverless as the database solution.
• C. Deploy containers on Amazon Elastic Kubernetes Service (Amazon EKS). Set up the containers to run the tasks on AWS Fargate. Choose Amazon S3 as the volume type. Deploy Amazon Aurora Serverless as the database solution.
• D. Deploy containers on Amazon Elastic Container Service (Amazon ECS). Set up the containers to run the tasks on AWS Fargate. Choose Amazon Elastic Block Store (Amazon EBS) as the volume type. Deploy Amazon Aurora Serverless as the database solution.

Correct answer: B

Explanation

Amazon ECS with AWS Fargate minimizes operational overhead by providing a serverless container platform where you do not need to manage EC2 instances. Amazon Elastic File System (Amazon EFS) is required because it supports concurrent read/write access from multiple containers to share application data, unlike Amazon EBS which is limited to single instances. Amazon Aurora Serverless completes the low-overhead, highly scalable architecture by automatically adjusting database capacity based on actual demand.