A high-traffic e-commerce website experiences unpredictable traffic spikes. The backend uses an Auto Scaling group of EC2 instances processing orders from an SQS queue. During spikes, instances take 5 minutes to boot, causing order processing delays. How can the architect improve reliability and responsiveness?

Answer options:

Change the Auto Scaling group to use Target Tracking on CPU utilization.

Implement Step Scaling policies based on SQS queue depth (ApproximateNumberOfMessagesVisible).

Use AWS Lambda instead of EC2 for processing.

Increase the size of the EC2 instances in the Auto Scaling group.

How to approach this question

Identify the best scaling metric for worker nodes processing a queue.

B.Implement Step Scaling policies based on SQS queue depth (ApproximateNumberOfMessagesVisible).✓ Correct

For queue-processing workloads, scaling based on the number of messages in the queue is the most responsive approach.

Using CPU metrics for queue workers, which reacts too slowly.

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