A SysOps Administrator deployed an AWS Elastic Beanstalk worker node environment that reads messages from an auto-generated Amazon Simple Queue Service (Amazon SQS) queue and deleted them from the queue after processing. Amazon EC2 Auto Scaling scales in and scales out the number of worker nodes based on CPU utilization. After some time, the Administrator notices that the number of messages in the SQS queue are increasing significantly. Which action will remediate this issue?
A) Change the scaling policy to scale based upon the number of messages in the queue.
B) Decouple the queue from the Elastic Beanstalk worker node and create it as a separate resource.
C) Increase the number of messages in the queue.
D) Increase the retention period of the queue.

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The Answer of A SysOps Administrator deployed an AWS Elastic Beanstalk worker node environment that reads messages from an auto-generated Amazon Simple Queue Service (Amazon SQS) queue and deleted them from the queue after processing. Amazon EC2 Auto Scaling scales in and scales out the number of worker nodes based on CPU utilization. After some time, the Administrator notices that the number of messages in the SQS queue are increasing significantly. Which action will remediate this issue?
A) Change the scaling policy to scale based upon the number of messages in the queue.
B) Decouple the queue from the Elastic Beanstalk worker node and create it as a separate resource.
C) Increase the number of messages in the queue.
D) Increase the retention period of the queue.

A SysOps Administrator Deployed an AWS Elastic Beanstalk Worker Node