You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
This Guidance demonstrates how to deploy a machine learning inference architecture on Amazon Elastic Kubernetes Service (Amazon EKS). It addresses the basic implementation requirements as well as ways you can pack thousands of unique PyTorch deep learning (DL) models into a scalable architecture and evaluate performance at scale
Build a ready-to-use EKS+K10 demo environment on AWS in ~20 minutes with just one command (EKS+Cassandra+K10). 3 mins to protect containers if you already have an EKS cluster up running.
This guidance shows how to deploy a federated Kubernetes environment in Amazon Web Services (AWS) cloud using Amazon Elastic Kubernetes Service (Amazon EKS) and the open source CNCF Karmada project - multi-cluster Kubernetes management system with advanced scheduling capabilities that enable running containerized applications across clusters