A company is planning to deploy a new business analytics application that requires 10,000 hours of compute time each month. The compute resources can have flexible availability, but must be as cost-effective as possible. The company will also provide a reporting service to distribute analytics reports, which needs to run at all times.
How should the Solutions Architect design a solution that meets these requirements?

A. Deploy the reporting service on a Spot Fleet. Deploy the analytics application as a container in Amazon ECS with AWS Fargate as the compute option. Set the analytics application to use a custom metric with Service Auto Scaling.
B. Deploy the reporting service on an On-Demand Instance. Deploy the analytics application as a container in AWS Batch with AWS Fargate as the compute option. Set the analytics application to use a custom metric with Service Auto Scaling.
C. Deploy the reporting service as a container in Amazon ECS with AWS Fargate as the compute option. Deploy the analytics application on a Spot Fleet. Set the analytics application to use a custom metric with Amazon EC2 Auto Scaling applied to the Spot Fleet.
D. Deploy the reporting service as a container in Amazon ECS with AWS Fargate as the compute option. Deploy the analytics application on an On-Demand Instance and purchase a Reserved Instance with a 3-year term. Set the analytics application to use a custom metric with Amazon EC2 Auto Scaling applied to the On-Demand Instance.