From the course: Machine Learning with SageMaker by Pearson

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SageMaker auto scaling demonstration

SageMaker auto scaling demonstration - Amazon SageMaker Tutorial

From the course: Machine Learning with SageMaker by Pearson

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SageMaker auto scaling demonstration

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Autoscaling in SageMaker will scale the number of instances running behind an endpoint. Specify a autoscaling policy, then you apply that to your variant on an endpoint, and then it will automatically scale the number of instances as required. I have this link in the lab documentation I have this link in the lab documentation. that takes you to the introduction to auto-scaling within SageMaker. There's several different ways to configure auto-scaling. You have the SDK, you have the command line interface, and you also have the web console. You can also do it with CloudFormation, as you can see over here, use AWS CloudFormation to create a scaling policy. We are going to do it with the web interface, the web console. I have a notebook in our lab directory that simply deploys a pre-trained model. The one unique thing that I'm doing here is giving it a static name so that I can then invoke or execute this predict.py application several times. So you can see I have six different windows…

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