AWS Certified Solutions Architect Professional SAP-C02 Practice Question

A financial-services company runs Monte Carlo risk simulations overnight in a single AWS Region. The job launches up to 1,000 Linux instances for 6 hours. At least 100 instances must always be running to meet the service-level agreement, but the rest of the workload can tolerate Spot interruptions. The chief architect wants to minimize compute cost, obtain Spot capacity from pools that have the lowest interruption risk, and automatically replace any Spot Instances that receive a rebalance recommendation.

Which solution meets all of these requirements?

  • Use AWS Batch with a single Spot compute environment that specifies the SPOT_CAPACITY_OPTIMIZED allocation strategy and a desired vCPU count of 1,000. Batch will automatically provision the required capacity and handle any Spot interruptions.

  • Request an EC2 Spot Fleet for 1,000 instances across all Availability Zones using the lowest-price allocation strategy. Set OnDemandTargetCapacity to 100 and rely on a Lambda function to relaunch tasks if Spot Instances are interrupted.

  • Create an EC2 Auto Scaling group that uses a launch template for the simulation instances. Configure a mixed instances policy with OnDemandBaseCapacity set to 100, OnDemandPercentageAboveBaseCapacity set to 0, and SpotAllocationStrategy set to capacity-optimized. Enable Capacity Rebalancing for the group.

  • Deploy the workload in an EC2 Auto Scaling group that launches only Spot Instances with the lowest-price allocation strategy. Configure Capacity Rebalancing so the group starts new Spot Instances when interruptions occur.

AWS Certified Solutions Architect Professional SAP-C02
Design Solutions for Organizational Complexity
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