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Answer: Deploy the application's front end to an Amazon S3 bucket served by Amazon CloudFront. Implement the application's backend using Amazon API Gateway with an AWS Lambda proxy integration., Store the timesheet submission data in Amazon S3. Generate the reports using Amazon Athena and Amazon QuickSight with Amazon S3 as the data source.
To meet the requirements for a highly available and scalable solution with minimal operational overhead, the optimal choices are C and E. Deploying the application's front end to an Amazon S3 bucket served by Amazon CloudFront (Option C) simplifies deployment and reduces operational overhead. Deploying the backend using Amazon API Gateway with an AWS Lambda proxy integration ensures scalability and minimal maintenance. Storing the timesheet submission data in Amazon S3 (Option E) provides a cost-effective, scalable storage solution. Using Amazon Athena and Amazon QuickSight to generate reports from Amazon S3 data ensures that payroll administrators can easily access and analyze the data.
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A solutions architect is tasked with designing an application for employees to submit timesheet entries via their mobile devices. The application will primarily receive submissions on Fridays, and the data must be stored in a format accessible for monthly payroll reports. The infrastructure must be highly available and capable of scaling to handle the influx of data and reporting requests. Which two steps, when combined, will fulfill these requirements while minimizing operational overhead?
A
Deploy the application on Amazon EC2 On-Demand Instances with load balancing across multiple Availability Zones. Implement scheduled Amazon EC2 Auto Scaling to increase capacity ahead of the anticipated high volume of submissions on Fridays.
B
Deploy the application using Amazon Elastic Container Service (Amazon ECS) with load balancing across multiple Availability Zones. Utilize scheduled Service Auto Scaling to increase capacity in preparation for the high volume of submissions on Fridays.
C
Deploy the application's front end to an Amazon S3 bucket served by Amazon CloudFront. Implement the application's backend using Amazon API Gateway with an AWS Lambda proxy integration.
D
Store the timesheet submission data in Amazon Redshift. Generate the reports using Amazon QuickSight with Amazon Redshift as the data source.
E
Store the timesheet submission data in Amazon S3. Generate the reports using Amazon Athena and Amazon QuickSight with Amazon S3 as the data source.