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58
Curated Reports
1705+
Controls Checked
3
Cloud Providers
5 min
To First Results
Machine Learning Best Practices
16 controls
5 services covered
Reviews SageMaker and Glue ML controls — VPC placement and network isolation, supported notebook platforms, disabled root access, endpoint redundancy, model deployment, and encryption.
What we check
SageMaker Notebook Instances7
- SageMaker Endpoint Config Production Redundant Instance Check
- No Direct Internet Access for SageMaker Notebook Instance
- SageMaker Notebook Instances Launched in a Non-Default VPC
- SageMaker Notebook Instance Root Access Disabled
- SageMaker Notebook Instance Encryption At-Rest Enabled
- SageMaker Notebook Instance in VPC
- SageMaker notebook instances should use a supported platform identifier
SageMaker Training Jobs4
- SageMaker Training Job Inter-Container Encryption Enabled
- SageMaker Training Job Network Isolation Enabled
- SageMaker Training Job Volume Encryption Enabled with KMS
- SageMaker Training Job has VPC Settings Enabled
SageMaker Models3
- SageMaker Model Network Isolation Enabled
- SageMaker Model VPC Settings Enabled
- SageMaker models should use private registry in VPC for multi-container inference pipelines
SageMaker Endpoints1
- SageMaker Endpoint Configuration Encrypted At-Rest
Glue ML Transforms1
- Glue ML Transform Encryption at Rest Check
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