Q3 — AWS SAA-C03 Ch.1

Question 3 of 65 | ← Chapter 1

Q3. A solutions architect is designing the cloud architecture for a new application being deployed on AWS. The process should run in parallel while adding and removing application nodes as needed based on the number of jobs to be processed.The processor application is stateless.The solutions architect must ensure that the application is loosely coupled and the job items are durably stored.Which design should the solutions architect use?

• A. Create an Amazon SNS topic to send the jobs that need to be processed.Create an Amazon Machine Image (AMI) that consists of the processor application.Create a launch configuration that uses the AMI.Create an Auto Scaling group using the launch configuration.Set the scaling policy for the Auto Scaling group to add and remove nodes based on CPU usage
• B. Create an Amazon SQS queue to hold the jobs that need to be processed.Create an Amazon Machine Image (AMI) that consists of the processor application.Create a launch configuration that uses the AMI.Create an Auto Scaling group using the launch configuration.Set the scaling policy for the Auto Scaling group to add and remove nodes based on network usage
• C. Create an Amazon SQS queue to hold the jobs that needs to be processed.Create an Amazon Machine Image (AMI) that consists of the processor application.Create a launch template that uses the AMI.Create an Auto Scaling group using the launch template.Set the scaling policy for the Auto Scaling group to add and remove nodes based on the number of items in the SQS queue ✓
• D. Create an Amazon SNS topic to send the jobs that need to be processed.Create an Amazon Machine Image (AMI) that consists of the processor application.Create a launch template that uses the AMI.Create an Auto Scaling group using the launch template.Set the scaling policy for the Auto Scaling group to add and remove nodes based on the number of messages published to the SNS topic.

Correct Answer: C. Create an Amazon SQS queue to hold the jobs that needs to be processed.Create an Amazon Machine Image (AMI) that consists of the processor application.Create a launch template that uses the AMI.Create an Auto Scaling group using the launch template.Set the scaling policy for the Auto Scaling group to add and remove nodes based on the number of items in the SQS queue

Explanation

When designing a cloud architecture for an application that needs to run in parallel, adding and removing nodes based on the number of jobs to be processed, and ensuring loose coupling with durable storage for job items, let's analyze each option:A. This option uses Amazon SNS (Simple Notification Service) to send job notifications, but SNS is primarily designed for pub/sub messaging and is not well-suited for storing and durably queuing job items. The scaling policy based on CPU usage is not directly related to the number of jobs to be processed, which is the primary concern here.B. This option uses Amazon SQS (Simple Queue Service) to hold job items, which is a good choice for durable storage and queuing. However, the scaling policy based on network usage is not directly tied to the number of jobs in the queue, which is the more relevant metric for this use case.C. This option combines Amazon SQS for durable storage and queuing of job items with an Auto Scaling group that scales based on the number of items in the SQS queue. This directly addresses the requirement of adding and removing nodes based on the number of jobs to be processed. The use of a launch template (as opposed to a launch configuration) is also a good practice for more flexible and dynamic Auto Scaling groups.D. This option uses Amazon SNS, which, as mentioned earlier, is not well-suited for storing and queuing job items. The scaling policy based on the number of messages published to the SNS topic is also not relevant since the number of messages published does not necessarily reflect the number of jobs waiting to be processed.Conclusion:The most suitable design for the described requirements is:C. Create an Amazon SQS queue to hold the jobs that need to be processed. Create an Amazon Machine Image (AMI) that consists of the processor application. Create a launch template that uses the AMI. Create an Auto Scaling group using the launch template.