How should a solutions architect design the architecture to meet these requirements?
Configure an Amazon Simple Queue Service (Amazon SQS) queue as a destination for the jobs. Implement the compute nodes with Amazon EC2 instances that are managed in an Auto Scaling group. Configure EC2 Auto Scaling to use scheduled scaling.
Configure an Amazon Simple Queue Service (Amazon SQS) queue as a destination for the jobs. Implement the compute nodes with Amazon EC2 instances that are managed in an Auto Scaling group. Configure EC2 Auto Scaling based on the size of the queue.
Implement the primary server and the compute nodes with Amazon EC2 instances that are managed in an Auto Scaling group. Configure AWS CloudTrail as a destination for the jobs. Configure EC2 Auto Scaling based on the load on the primary server.
Implement the primary server and the compute nodes with Amazon EC2 instances that are managed in an Auto Scaling group. Configure Amazon EventBridge (Amazon CloudWatch Events) as a destination for the jobs. Configure EC2 Auto Scaling based on the load on the compute nodes.
Explanations:
Scheduled scaling is not ideal for variable workloads since it does not adjust to real-time demand, limiting scalability and responsiveness.
Using an SQS queue as a job destination and scaling EC2 instances based on queue size ensures scalability and resilience, as the system adjusts to the current workload in real time.
CloudTrail is primarily for logging and tracking API calls, not for job distribution, making it unsuitable as a job destination. Also, scaling based on load on the primary server may not fully optimize scalability.
EventBridge (CloudWatch Events) is not designed for job queueing in compute architectures, and scaling based on compute node load may not effectively manage variable workload demands compared to queue-based scaling.