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AWS Certified Solutions Architect - Professional · AWS
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I was first voted for D since I wasn't sure terminating entire Cluster is a good option or even valid. here is why B is better option: Since the data is stored in EMRFS (which uses Amazon S3), you can safely terminate the entire cluster after job completion without losing data. And this is different than terminating primary nodes which are essential for cluster management and run critical services like YARN ResourceManager and HDFS NameNode. Configure your entire cluster to automatically terminate after a specified idle period. This ensures you don't pay for resources when the cluster is not processing data. it
Option B is correct because it keeps the master and core nodes on reliable On-Demand Instances, uses low-cost Spot Instances for task nodes, and terminates the entire cluster after processing, ensuring both stability and cost efficiency with additional savings from Compute Savings Plans.
We need a solution to minimize the compute costs. EMRFS stores the data on S3. There is no copy to store on EMR or HDFS. The mappings to the data aren't critical and there is no major time pressure to finish it as fast as possible even though it is a critical application. Thus B would give you the most savings and meet the SLAs.