Which solution will meet these requirements MOST cost-effectively?
Split the 12 instances across two Availability Zones in the chosen AWS Region. Run two instances in each Availability Zone as On-Demand Instances with Capacity Reservations. Run four instances in each Availability Zone as Spot Instances.
Split the 12 instances across three Availability Zones in the chosen AWS Region. In one of the Availability Zones, run all four instances as On-Demand Instances with Capacity Reservations. Run the remaining instances as Spot Instances.
Split the 12 instances across three Availability Zones in the chosen AWS Region. Run two instances in each Availability Zone as On-Demand Instances with a Savings Plan. Run two instances in each Availability Zone as Spot Instances.
Split the 12 instances across three Availability Zones in the chosen AWS Region. Run three instances in each Availability Zone as On-Demand Instances with Capacity Reservations. Run one instance in each Availability Zone as a Spot Instance.
Explanations:
Running two instances in each Availability Zone as On-Demand Instances with Capacity Reservations and four instances as Spot Instances does not guarantee the required availability during failures, especially for scheduled jobs. Capacity Reservations ensure high availability for On-Demand Instances but the Spot Instances can be interrupted, which is not acceptable for the scheduled jobs that must meet tight SLAs.
Running four On-Demand Instances with Capacity Reservations in one Availability Zone and the rest as Spot Instances in the other Availability Zones is not ideal. It introduces risk to availability, as Spot Instances can be terminated, impacting the scheduled jobs that need to meet SLAs. Additionally, having a single Availability Zone with the majority of On-Demand Instances creates a potential single point of failure.
Running On-Demand Instances with a Savings Plan and Spot Instances is not a cost-effective solution. Savings Plans are typically for long-term commitment, which is not aligned with the requirement of a consumption-based model with no long-term commitments. The Spot Instances, while cost-effective, cannot guarantee the required availability for scheduled jobs that have tight SLAs.
Running three On-Demand Instances with Capacity Reservations in each of three Availability Zones ensures high availability and fault tolerance for scheduled jobs. The Capacity Reservations provide guaranteed capacity for critical instances, ensuring that scheduled jobs meet SLAs. Spot Instances in each Availability Zone can handle user jobs, which are less time-sensitive and can tolerate delays. This solution meets the cost and high availability requirements effectively.