Amazon SAP-C02: Steps for infrastructure highly available and scale

Table of Contents

Question
Answer
Explanation
Reference

Question

A solutions architect is designing an application to accept timesheet entries from employees on their mobile devices. Timesheets will be submitted weekly, with most of the submissions occurring on Friday. The data must be stored in a format that allows payroll administrators to run monthly reports. The infrastructure must be highly available and scale to match the rate of incoming data and reporting requests. Which combination of steps meets these requirements while minimizing operational overhead? (Choose two.)

A. Deploy the application to Amazon EC2 On-Demand Instances with load balancing across multiple Availability Zones. Use scheduled Amazon EC2 Auto Scaling to add capacity before the high volume of submissions on Fridays.
B. Deploy the application in a container using Amazon Elastic Container Service (Amazon ECS) with load balancing across multiple Availability Zones. Use scheduled Service Auto Scaling to add capacity before the high volume of submissions on Fridays.
C. Deploy the application front end to an Amazon S3 bucket served by Amazon CloudFront. Deploy the application backend using Amazon API Gateway with an AWS Lambda proxy integration.
D. Store the timesheet submission data in Amazon Redshift. Use Amazon QuickSight to generate the reports using Amazon Redshift as the data source.
E. Store the timesheet submission data in Amazon S3. Use Amazon Athena and Amazon QuickSight to generate the reports using Amazon S3 as the data source.

Answer

B. Deploy the application in a container using Amazon Elastic Container Service (Amazon ECS) with load balancing across multiple Availability Zones. Use scheduled Service Auto Scaling to add capacity before the high volume of submissions on Fridays.
E. Store the timesheet submission data in Amazon S3. Use Amazon Athena and Amazon QuickSight to generate the reports using Amazon S3 as the data source.

Explanation

The combination of steps that meets these requirements while minimizing operational overhead are Option B and Option E.

B. Deploy the application in a container using Amazon Elastic Container Service (Amazon ECS) with load balancing across multiple Availability Zones. Use scheduled Service Auto Scaling to add capacity before the high volume of submissions on Fridays.
E. Store the timesheet submission data in Amazon S3. Use Amazon Athena and Amazon QuickSight to generate the reports using Amazon S3 as the data source.

Here is the explanation for each step:

Amazon ECS is a fully managed container orchestration service that makes it easy to deploy and manage containerized applications. By deploying the application in a container, the solutions architect can take advantage of the scalability and flexibility of ECS. Additionally, by using load balancing across multiple Availability Zones, the solutions architect can ensure that the application is highly available. Finally, by using scheduled Service Auto Scaling, the solutions architect can automatically add capacity to the application before the high volume of submissions on Fridays.

E. Store the timesheet submission data in Amazon S3. Use Amazon Athena and Amazon QuickSight to generate the reports using Amazon S3 as the data source.

Amazon S3 is a highly scalable and durable object storage service. By storing the timesheet submission data in S3, the solutions architect can ensure that the data is secure and available. Additionally, by using Amazon Athena, the solutions architect can easily query the data in S3 without having to create and manage a database. Finally, by using Amazon QuickSight, the solutions architect can easily create and share interactive reports based on the data in S3.

The other options are not as good a fit for this solution:

This option would require provisioning and managing Amazon EC2 instances, which would increase the operational overhead of the stack. Additionally, Amazon EC2 On-Demand Instances are not as scalable as Amazon ECS.

C. Deploy the application front end to an Amazon S3 bucket served by Amazon CloudFront. Deploy the application backend using Amazon API Gateway with an AWS Lambda proxy integration.

This option would require provisioning and managing an Amazon S3 bucket, an Amazon CloudFront distribution, and an Amazon API Gateway endpoint. Additionally, Amazon Lambda is not as scalable as Amazon ECS.

D. Store the timesheet submission data in Amazon Redshift. Use Amazon QuickSight to generate the reports using Amazon Redshift as the data source.

This option would require provisioning and managing an Amazon Redshift cluster, which would increase the operational overhead of the stack. Additionally, Amazon Redshift is not as scalable as Amazon S3.

Reference

Amazon AWS Certified Solutions Architect – Professional SAP-C02 certification exam practice question and answer (Q&A) dump with detail explanation and reference available free, helpful to pass the Amazon AWS Certified Solutions Architect – Professional SAP-C02 exam and earn Amazon AWS Certified Solutions Architect – Professional SAP-C02 certification.