You work as a machine learning specialist for a social media software company. Your company produces social media apps such as interactive games and photo-sharing communities. Your machine learning team has created a machine learning model that produces recommendations via advertising in your apps, such as showing advertising for skiing trips to a user who follows a ski resort in the photo-sharing app. The production variant that your team has deployed experiences very wild swings in traffic volume over the course of any given day. Also, since the app is relatively new to the mobile community, it receives no traffic for some time periods. You have set up SageMaker automatic scaling policy for your production variant instances. However, you have noticed that scaling-in does not happen when your traffic reduces to nothing for a period of time. Why might this happen?

Answer options:

A.Scaling-in does not happen when there is no traffic. If traffic to your production variant becomes zero, SageMaker automatic scaling won’t scale in. SageMaker doesn`t emit metrics with a value of zero, so no CloudWatch events are triggered.
B.You are using a Step Scaling policy, and you have set the number of instances to deploy to a too high level.
C.You are using a Step Scaling policy, and you have set the number of instances to deploy to a too low level.
D.You are using a Target Tracking policy and you have set the target value for your metric too low.

Correct Answer: A
Option A is correct. When your production variant doesn’t receive any traffic, SageMaker does not emit any metrics. Therefore there is no target metric for CloudWatch to use as a trigger to initiate the scale as defined in your scaling policy.
Option B is incorrect. Even if you used a step scaling policy and set the number of instances to a high number, the policy won’t be triggered by CloudWatch because SageMaker does not emit any metrics when traffic is 0 to your production variant.
Option C is incorrect. Even if you used a step scaling policy and set the number of instances to a low number, the policy won’t be triggered by CloudWatch because SageMaker does not emit any metrics when traffic is 0 to your production variant.
Option D is incorrect. Even if you used a target tracking scaling policy and set the target value for your metric to a low value, the policy won’t be triggered by CloudWatch because SageMaker does not emit any metrics when traffic is 0 to your production variant.
References:
Please see the AWS SageMaker developer guide titled Prerequisites (https://docs.aws.amazon.com/sagemaker/latest/dg/endpoint-auto-scaling-prerequisites.html),
The Application Auto Scaling user guide titled Target tracking scaling policies for Application Auto Scaling (https://docs.aws.amazon.com/autoscaling/application/userguide/application-auto-scaling-target-tracking.html),
The Application Auto Scaling user guide titled Step scaling policies for Application Auto Scaling (https://docs.aws.amazon.com/autoscaling/application/userguide/application-auto-scaling-step-scaling-policies.html)