Run interruptible batch simulations on AWS Batch with Spot Instances only
A company needs to run large batch-processing jobs on data that is stored in an Amazon S3 bucket. The jobs perform simulations. The results of the jobs are not time sensitive, and the process can withstand interruptions. Each job must process 15-20 GB of data when the data is stored in the S3 bucket. The company will store the output from the jobs in a different Amazon S3 bucket for further analysis. Which solution will meet these requirements MOST cost-effectively?
Community Votes
100% of anonymous learners picked answer B. Votes are pick records left by other test-takers — they are not the verified answer.
Community Insight
Spot Instances can be reclaimed with a two-minute notice, which is only acceptable because the jobs tolerate interruption, and the SPOT_CAPACITY_OPTIMIZED allocation strategy picks the Spot pools with the lowest interruption probability so jobs are not repeatedly reclaimed.
Large batch simulation jobs read 15 to 20 GB each from an S3 bucket and write results to a different bucket. The results are not time sensitive, the process tolerates interruption, and the priority is the lowest possible cost.
Mixing On-Demand and Spot capacity. A compute environment with both is useful when the work must always run, but here the work is interruptible and untimed, so On-Demand capacity adds cost for no benefit and the SPOT_CAPACITY_OPTIMIZED strategy applies to the Spot portion only.
Community Discussion (7 comments)
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Expert Analysis
Why the Answer Is Correct
The two explicit constraints, that results are not time sensitive and the process can withstand interruptions, are the preconditions for using Spot capacity. AWS Batch is the right service because each job processes 15 to 20 GB and needs a managed compute environment, and a compute environment made up only of Spot Instances gets the deep discount that On-Demand pricing cannot match. Specifying SPOT_CAPACITY_OPTIMIZED makes Batch choose the instance pools with the lowest chance of interruption, which reduces the likelihood that a long simulation is repeatedly reclaimed, and Batch checkpoints the job so it resumes on another instance.Why the Other Options Are Wrong
A: Provisioned concurrency for Lambda is designed for low-latency request handling, and a simulation processing 20 GB per job is not a fit for a fifteen-minute maximum execution limit, so this option cannot run the work at all. C: A compute environment with both On-Demand and Spot Instances provides guaranteed capacity, which costs more and is unnecessary when interruptions are acceptable. The SPOT_CAPACITY_OPTIMIZED strategy would still apply only to the Spot portion, leaving paid On-Demand capacity running. D: An EKS cluster with managed node groups requires the team to operate a Kubernetes cluster and tune node groups, and managed node groups do not give the Spot pricing benefit in the way a Batch compute environment does, so the operational and cost overhead is higher than Batch.Community Comment Notes
The community voted 100 to 0 for B, with the top-voted comment mapping the question's phrasing directly to the service choice, large batch jobs to AWS Batch, and not time sensitive and can withstand interruptions to Spot Instances. Another commenter linked the AWS blog on cost-effective batch processing with EC2 Spot and correctly noted why option C is wrong, since AWS Batch selects instance types that are large enough to meet the job requirements and the mixed strategy adds cost without benefit here.Official Reference
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