A company migrated an application to the AWS Cloud. The application runs on two Amazon EC2 instances behind an Application Load Balancer (ALB). Application data is stored in a MySQL database that runs on an additional EC2 instance. The application's use of the database is read-heavy. The application loads static content from Amazon Elastic Block Store (Amazon EBS) volumes that are attached to each EC2 instance. The static content is updated frequently and must be copied to each EBS volume. The load on the application changes throughout the day. During peak hours, the application cannot handle all the incoming requests. Trace data shows that the database cannot handle the read load during peak hours. Which solution will improve the reliability of the application?
Select one answer.
Marked answer: D
Community Discussion
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1
By containerizing the application using Amazon Elastic Container Service (Amazon ECS) and AWS Fargate, the company can easily scale the application up or down based on demand, reducing downtime during peak hours. Using an Amazon Elastic File System (Amazon EFS) for static content ensures that data is accessible from multiple containers, reducing the need to copy content to each individual container. Configuring AWS Application Auto Scaling on the ECS cluster allows automatic scaling based on CPU utilization or other custom metrics, ensuring that the application can handle increased load during peak hours. Migrating the database to Amazon Aurora MySQL Serverless v2 with a reader DB instance allows for horizontal scalability and eliminates the need for provisioning and managing database instances manually.
Chose D3
The question is not clear on the nature of application and assumes that the application is Linux based, all option would be incorrect if this was a windows app. Given the information D is the best bet.
