Architecting secure AI sandboxes in AWS GovCloud (US)

This article presents a secure generative AI sandbox architecture for AWS GovCloud (US) environments, addressing federal compliance and data privacy requirements.

• Uses SageMaker AI Studio domains and shared spaces for workspace isolation and team collaboration
• AWS Lake Formation provides fine-grained data governance with database, table, column, row, and cell-level access control
• Authentication via Lambda-generated presigned URLs validating SAML/JWT against organizational identity providers
• VPC endpoints and PrivateLink keep all traffic within AWS GovCloud network, avoiding public internet
• Amazon Bedrock provides managed foundation model access with enterprise security and data isolation
• AWS Step Functions and SageMaker Pipelines orchestrate repeatable workflows for experimentation and inference
• CloudTrail and AWS Config enable compliance monitoring, audit trails, and configuration tracking
• Architecture supports FedRAMP, DoD CC SRG, and ITAR compliance requirements

This design enables federal agencies to safely experiment with generative AI while maintaining strict data governance, security isolation, and regulatory compliance in GovCloud environments.