HyperPod enhances ML infrastructure with security and storage | Amazon Web Services

HyperPod enhances ML infrastructure with security and storage | Amazon Web Services

Amazon SageMaker HyperPod is a purpose-built infrastructure for optimizing foundation model training and inference at scale. SageMaker HyperPod removes the undifferentiated heavy lifting involved in building and optimizing machine learning (ML) infrastructure for training foundation models (FMs).

As AI moves towards deployment adopting to a multitude of domains and use cases, the need for security and multiple storage options is becoming more pertinent. Large enterprises want to make sure that the GPU clusters follow the organization wide policies and security rules. Two new features in SageMaker HyperPod EKS enhance this control and flexibility for production deployment of large-scale machine learning workloads. These features include support for continuous scaling, custom Amazon Machine Images, and customer managed key (CMK) integration.

https://aws.amazon.com/blogs/machine-learning/hyperpod-enhances-ml-infrastructure-with-security-and-storage/