
Explanation:
To meet regulatory requirements for running Amazon SageMaker jobs in an isolated environment without internet access, the optimal solution is network isolation. Here's why:
Complete Network Isolation: Amazon SageMaker's network isolation feature allows you to run training and inference jobs within a private Virtual Private Cloud (VPC). When enabled, this configuration ensures that SageMaker instances have no internet access and can only communicate with resources within the specified VPC.
Regulatory Compliance: Many regulatory frameworks (such as HIPAA, PCI-DSS, GDPR, and financial industry regulations) require strict network segmentation and isolation for sensitive data processing. Network isolation directly addresses these requirements by preventing any external network connectivity.
Technical Implementation: When you configure SageMaker with network isolation:
Security Enhancement: This approach provides defense-in-depth by eliminating potential attack vectors from the internet, reducing the attack surface, and ensuring data remains within the controlled VPC environment.
Option A (SageMaker Experiments): SageMaker Experiments is a feature for organizing, tracking, and comparing machine learning experiments. While useful for managing ML workflows, it does not provide network isolation or control internet access. It's a management tool rather than a security or compliance solution.
Option C (Encrypt data at rest): While encryption at rest is an important security best practice and may be required by some regulations, it does not address the specific requirement for network isolation and no internet access. Data encryption protects stored data but doesn't control network connectivity during job execution.
Option D (IAM roles): IAM roles control permissions and access to AWS resources, which is essential for security. However, IAM roles alone cannot enforce network isolation or prevent internet access. They manage authentication and authorization but not network-level restrictions.
When implementing network isolation for SageMaker:
This approach aligns with AWS best practices for secure, compliant ML workloads in regulated environments.
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How can a company configure Amazon SageMaker to conduct model training and inference in compliance with regulatory requirements that mandate an isolated environment with no internet access?
A
Run SageMaker training and inference by using SageMaker Experiments.
B
Run SageMaker training and Inference by using network Isolation.
C
Encrypt the data at rest by using encryption for SageMaker geospatial capabilities.
D
Associate appropriate AWS Identity and Access Management (IAM) roles with the SageMaker jobs.