Amazon SageMaker Unified Studio now supports VPC for notebook kernels

Amazon Web Services has added Virtual Private Cloud (VPC) support to notebook kernels in Amazon SageMaker Unified Studio, enabling enterprises to run interactive data science and machine learning workloads within isolated network environments. The new capability allows notebook kernels to execute within VPC configurations defined at the domain level, ensuring that compute traffic remains within designated network boundaries to meet security and compliance requirements. With VPC-enabled notebook kernels, data engineers and data scientists can now access private databases, internal APIs, and other non-publicly accessible data sources directly from their notebook environments. The kernels automatically inherit VPC settings, subnets, and security groups configured at the domain level, allowing administrators to centrally manage network policies. The feature supports SQL, Python, and natural language queries through the platform's built-in data agent, though VPC configuration applies specifically to the notebook's interactive compute environment rather than other compute engines. The VPC support for notebook kernels is now available across all AWS regions where SageMaker Unified Studio operates. This enhancement addresses a key enterprise requirement for network isolation in cloud-based data science workflows, particularly for organizations handling sensitive data or operating under strict regulatory frameworks.