What should the solutions architect do to meet these requirements?

Explanations:

Increasing the minimum capacity would ensure that the Auto Scaling group maintains a certain number of EC2 instances at all times, which does not address the need for a faster scaling to the desired capacity before the batch jobs start. It may lead to unnecessary costs by having instances running that are not needed until the job begins.

Increasing the maximum capacity allows for more instances to be launched but does not solve the problem of scaling up quickly to the desired capacity at 1 AM. Without proper scaling triggers, it could still take time for the instances to launch and become available.

Configuring scheduled scaling to scale up to the desired compute level precisely at 1 AM ensures that the EC2 instances are available when the batch jobs start. This approach optimizes resource utilization and cost by scaling down after the jobs are completed.

Changing the scaling policy to add more EC2 instances during each scaling operation does not guarantee that the desired capacity is reached by 1 AM. This method could lead to unnecessary delays or overshooting the capacity, increasing costs without optimizing the schedule for the batch jobs.