From the course: Machine Learning with SageMaker by Pearson
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IAM demonstration - Amazon SageMaker Tutorial
From the course: Machine Learning with SageMaker by Pearson
IAM demonstration
I've mentioned the principle of least privilege a couple times throughout this course, and I want to give you a demonstration of how roles work, particularly within the SageMaker environment. The same concept works across other services as well. For example, you can attach a role to an EC2 instance and then any AWS API call that originates from that particular EC2 instance would be permitted or denied based on that role that is attached. So no service within AWS trusts any other service. So if you want, for example, a SageMaker notebook to talk to an S3 bucket to pull down some data, to do some training or pre-processing or whatever the case may be, you would need to explicitly permit that notebook instance to talk to S3 and you do that through roles. So let me give you a demonstration of that. Here in SageMaker, we don't need Studio. We're going to go into SageMaker Notebooks, and we're going to launch the SageMaker Notebook JupyterLab instance feature that is outside of SageMaker…
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