Which solution meets these requirements?

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In: SAA-C03
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A company offers a food delivery service that is growing rapidly.Because of the growth, the company’s order processing system is experiencing scaling problems during peak traffic hours.The current architecture includes the following:• A group of Amazon EC2 instances that run in an Amazon EC2 Auto Scaling group to collect orders from the application• Another group of EC2 instances that run in an Amazon EC2 Auto Scaling group to fulfill ordersThe order collection process occurs quickly, but the order fulfillment process can take longer.Data must not be lost because of a scaling event.A solutions architect must ensure that the order collection process and the order fulfillment process can both scale properly during peak traffic hours.The solution must optimize utilization of the company’s AWS resources.

Which solution meets these requirements?

Use Amazon CloudWatch metrics to monitor the CPU of each instance in the Auto Scaling groups. Configure each Auto Scaling group’s minimum capacity according to peak workload values.

Use Amazon CloudWatch metrics to monitor the CPU of each instance in the Auto Scaling groups. Configure a CloudWatch alarm to invoke an Amazon Simple Notification Service (Amazon SNS) topic that creates additional Auto Scaling groups on demand.

Provision two Amazon Simple Queue Service (Amazon SQS) queues: one for order collection and another for order fulfillment. Configure the EC2 instances to poll their respective queue. Scale the Auto Scaling groups based on notifications that the queues send.

Provision two Amazon Simple Queue Service (Amazon SQS) queues: one for order collection and another for order fulfillment. Configure the EC2 instances to poll their respective queue. Create a metric based on a backlog per instance calculation. Scale the Auto Scaling groups based on this metric.

Explanations:

While monitoring CPU and setting minimum capacities can help, it doesn’t address the scaling needs of the fulfillment process which can have longer processing times and potential backlog issues.

This option suggests creating additional Auto Scaling groups on demand based on CPU metrics, which may not effectively handle the scaling needs of the fulfillment process. This approach also risks losing orders if traffic spikes suddenly.

While using SQS queues for order collection and fulfillment helps decouple the processes, it lacks a method to scale the Auto Scaling groups based on the actual workload or backlog in the queues, potentially leading to underutilization or bottlenecks.

This solution effectively decouples order collection and fulfillment using SQS queues. It allows each process to scale independently based on the backlog metrics calculated per instance, ensuring that both processes can handle peak loads efficiently and avoid data loss.

2026-03-15

2 Comments

  1. Theresa
    Author

    I infer that the answer is:
    Provision two Amazon Simple Queue Service (Amazon SQS) queues: one for order collection and another for order fulfillment. Configure the EC2 instances to poll their respective queue. Create a metric based on a backlog per instance calculation. Scale the Auto Scaling groups based on this metric.

  2. Hannah
    Author

    If I’m not mistaken, the answer is:
    Provision two Amazon Simple Queue Service (Amazon SQS) queues: one for order collection and another for order fulfillment. Configure the EC2 instances to poll their respective queue. Create a metric based on a backlog per instance calculation. Scale the Auto Scaling groups based on this metric.

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