AWS Certified Solutions Architect Professional SAP-C02 Practice Question

Your company is modernizing an on-premises Java web application by containerizing it and deploying it on Amazon ECS with the EC2 launch type. The API is stateless and typically scales up to 15 tasks. To reduce compute cost, the architects want as many tasks as possible to run on Amazon EC2 Spot Instances while ensuring that at least two tasks always run on On-Demand Instances so the service remains available during Spot interruptions. The team also wants Application Auto Scaling target tracking on CPU utilization and wishes to minimize operational overhead. Which approach will meet these requirements MOST effectively?

  • Configure the ECS service with the DAEMON scheduling strategy on an On-Demand Auto Scaling group, then add a separate Spot Auto Scaling group so extra tasks can be scheduled automatically across both groups.

  • Use AWS Fargate and Fargate Spot capacity providers. Configure the service so that the FARGATE_SPOT capacity provider has base = 2 and weight = 1, and omit the On-Demand provider so that additional tasks run on Spot capacity.

  • Create two Auto Scaling groups: one that runs only On-Demand Instances and one that runs only Spot Instances. Create a capacity provider for each group, associate both with the ECS cluster, and configure the service with a capacityProviderStrategy where the On-Demand capacity provider has base = 2, weight = 1 and the Spot capacity provider has weight = 4.

  • Create a single Auto Scaling group that uses an EC2 MixedInstancesPolicy with 80 % Spot and 20 % On-Demand Instances, attach it to the ECS cluster, and set the service's launchType=EC2 without a capacity provider strategy.

AWS Certified Solutions Architect Professional SAP-C02
Accelerate Workload Migration and Modernization
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