We are thrilled to announce that customers in Canada can now leverage advanced foundation models, including Anthropic’s Claude Sonnet 4.5 and Claude Haiku 4.5, via Amazon Bedrock using cross-Region inference (CRIS). This capability enables Canadian organizations to utilize profiles from the Canada (Central) Region to accelerate their AI initiatives.\n\nFor organizations looking to enhance their machine learning workflows, Amazon SageMaker HyperPod now accommodates creating and managing interactive development environments like JupyterLab and open source Visual Studio Code. This new feature, known as Amazon SageMaker Spaces, allows developers to run notebooks efficiently, optimizing the use of GPU resources by combining both interactive workloads and training jobs within the same infrastructure.\n\nGetting started with these enhancements involves installing the Spaces add-on within your SageMaker cluster, where administrators can choose between a Quick install for default settings or a Custom install for specialized needs. Data scientists can create Spaces through the HyperPod Command Line Interface or Kubernetes tools and connect to them via a web UI or directly from local IDEs using SSH-over-SSM for secure access.\n\nTo enable users to manage and create Spaces, administrators must set up the required EKS access entries, ensuring seamless collaboration while maintaining security. Best practices include managing user identities, implementing role-based access controls, and utilizing custom templates for consistent configurations.\n\nWith these advancements, Canadian organizations can significantly reduce setup time and enhance their models’ development processes while ensuring secure, managed environments for their AI and ML applications. Don’t miss the opportunity to optimize your AI initiatives with Amazon Bedrock and SageMaker’s powerful new features!