AWS Certified Solutions Architect – Associate (SAA-C03) — Question 888

A company is migrating its data processing application to the AWS Cloud. The application processes several short-lived batch jobs that cannot be disrupted. Data is generated after each batch job is completed. The data is accessed for 30 days and retained for 2 years.

The company wants to keep the cost of running the application in the AWS Cloud as low as possible.

Which solution will meet these requirements?

Answer options

• A. Migrate the data processing application to Amazon EC2 Spot Instances. Store the data in Amazon S3 Standard. Move the data to Amazon S3 Glacier Instant. Retrieval after 30 days. Set an expiration to delete the data after 2 years.
• B. Migrate the data processing application to Amazon EC2 On-Demand Instances. Store the data in Amazon S3 Glacier Instant Retrieval. Move the data to S3 Glacier Deep Archive after 30 days. Set an expiration to delete the data after 2 years.
• C. Deploy Amazon EC2 Spot Instances to run the batch jobs. Store the data in Amazon S3 Standard. Move the data to Amazon S3 Glacier Flexible Retrieval after 30 days. Set an expiration to delete the data after 2 years.
• D. Deploy Amazon EC2 On-Demand Instances to run the batch jobs. Store the data in Amazon S3 Standard. Move the data to Amazon S3 Glacier Deep Archive after 30 days. Set an expiration to delete the data after 2 years.

Correct answer: D

Explanation

Amazon EC2 On-Demand Instances are necessary because the batch jobs must not be disrupted, which rules out Spot Instances since they can be interrupted with short notice. To minimize storage costs, data should be stored in Amazon S3 Standard during the initial 30 days of active access, and then transitioned via lifecycle policies to Amazon S3 Glacier Deep Archive, which offers the lowest-cost storage for the remaining duration of the 2-year retention period.