[MLS-C01] [IMPL and OPs] Security

Apply basic AWS security practices to machine learning solutions

Posted by Oscaner on August 8, 2022

SageMaker Instances

Jupyter Notebook

  • Your SageMaker infrastructure uses EC2 instances dedicated for your use
  • Can map your SageMaker resources to VPC so you can use your network controls
  • Control access to your jupyter notebooks and your hasted models through IAM
  • Can only access your SageMaker resources from within your VPC using your VPC Endpoints (Private Connectivity)
  • Encrypt your data at rest and in flight from your datasets on S3 to your notebooks and through to your hosted endpoints
  • You can use lifecycle configurations to harden the OS of your SageMaker EC2 instances or install agents
  • SageMaker is integrated with CloudWatch and CloudTrail for logging training job and hosted model activity as well as API calls

Jobs and Endpoints

  • Can map your training, tuning, and hosted model endpoint instances to VPC so you can use your network controls
  • Can restrict your training, tuning, and endpoint instances to resources within your VPC using your VPC Endpoints (Private Connectivity)

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