What solution will allow the batch jobs to complete as quickly as possible after being scheduled?
Schedule the jobs on an Amazon ECS cluster using the Amazon EC2 launch type. Use Service Auto Scaling to increase or decrease the number of running tasks to suit the number of running jobs.
Schedule the jobs directly on EC2 instances. Use Reserved Instances for the baseline minimum load, and use On-Demand Instances in an Auto Scaling group to scale up the platform based on demand.
Schedule the jobs on an Amazon ECS cluster using the Fargate launch type. Use Service Auto Scaling to increase or decrease the number of running tasks to suit the number of running jobs.
Schedule the jobs on an Amazon ECS cluster using the Fargate launch type. Use Spot Instances in an Auto Scaling group to scale the platform based on demand. Use Service Auto Scaling to increase or decrease the number of running tasks to suit the number of running jobs.
Explanations:
Using the EC2 launch type may lead to delays in job processing due to the need for EC2 instance provisioning and management. While Service Auto Scaling can help adjust the number of running tasks, it is not as efficient as using Fargate for immediate scaling and task management.
Scheduling jobs directly on EC2 instances introduces complexity in instance management and provisioning, potentially leading to longer job start times. Reserved Instances provide cost savings but do not offer flexibility for varying workloads, while On-Demand Instances may not scale quickly enough to meet immediate job demands.
Using the Fargate launch type allows for faster job scheduling and execution as it eliminates the need to manage EC2 instances. Fargate can scale automatically based on the number of tasks, providing the necessary resources immediately as jobs are submitted, thus ensuring quick completion.
While the Fargate launch type allows for quick job execution, using Spot Instances could lead to interruptions in running tasks, as Spot Instances can be terminated by AWS when the capacity is needed elsewhere. This unpredictability may hinder the reliability of completing batch jobs quickly.