AWS Certified Solutions Architect - Professional
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Ultimate access to all questions.
A company requires a cost-effective solution for running large batch-processing jobs on data stored in an Amazon S3 bucket. These jobs involve simulations, and the results are not time-sensitive, allowing the process to tolerate interruptions. Each job needs to process between 15-20 GB of data from the S3 bucket, with the output being stored in a separate S3 bucket for further analysis. Which solution provides the most cost-effective approach to meet these requirements?
A
Develop a serverless data pipeline using AWS Step Functions for orchestration and AWS Lambda functions with provisioned capacity to process the data.
B
Establish an AWS Batch compute environment incorporating Amazon EC2 Spot Instances, utilizing the SPOT_CAPACITY_OPTIMIZED allocation strategy.
C
Set up an AWS Batch compute environment with a mix of Amazon EC2 On-Demand Instances and Spot Instances, applying the SPOT_CAPACITY_OPTIMIZED allocation strategy for the Spot Instances.
D
Utilize Amazon Elastic Kubernetes Service (Amazon EKS) for running the processing jobs, employing managed node groups that include both Amazon EC2 On-Demand Instances and Spot Instances.