Category: Amazon Elastic Kubernetes Service

In this post, we explore how AWS and NVIDIA Run:ai are extending GPU fractionalization and orchestration capabilities beyond traditional cloud regions to edge environments, including AWS Local Zones, Outposts, and EKS Hybrid Nodes. The collaboration addresses the growing demand for distributed AI/ML workloads that require efficient GPU resource management across geographically separated locations while maintaining consistent performance, compliance, and cost optimization .

In this post, we explore advanced traffic routing patterns with the Kubernetes Gateway API through a practical Calendar web application example, demonstrating how it streamlines and standardizes application connectivity and service mesh integration in Kubernetes. The post covers three key use cases: exposing applications to external clients through hostname-based routing, implementing canary deployments between microservices using gRPC traffic splitting, and controlling egress traffic to external services with security policies.

In this post, we explore how KubeArmor, an open source container-aware security enforcement system, enhances the security posture of containerized workloads running on EKS Auto Mode clusters. Although EKS Auto Mode significantly streamlines cluster management by automating control plane and node operations, securing the workloads running within the cluster remains a critical user responsibility.

In this post, we explore how to use AWS Identity and Access Management (IAM) Roles Anywhere, supported by HashiCorp Vault PKI, to facilitate joining EKS Hybrid Nodes to an Amazon EKS Cluster. This solution enables businesses to flexibly make use of compute resources outside of AWS by extending an Amazon Elastic Kubernetes Service (Amazon EKS) data plane beyond the AWS Cloud boundary, addressing use cases focused on data sovereignty, low latency communication, and regulatory compliance.

In this post, we explore the latest Amazon Elastic Kubernetes Service (Amazon EKS) Auto Mode features that enhance security, network control, and performance for enterprise Kubernetes deployments. These new capabilities address critical operational challenges including capacity management, network segmentation, enterprise PKI integration, and comprehensive encryption while maintaining the automated cluster management that makes EKS Auto Mode transformative for development teams.

In this post, we introduce the Slinky Project and explore how it enables organizations to run Slurm workload management within Amazon EKS, combining the deterministic scheduling capabilities of Slurm with Kubernetes’ dynamic resource allocation for efficient hybrid workload management. This unified approach allows teams to maximize resource utilization across both batch processing jobs and cloud-native applications without maintaining separate infrastructure silos.

In this post, we explore how to manage EKS Pod Identity associations at scale using Argo CD and AWS Controllers for Kubernetes (ACK), addressing the critical challenge of the eventually consistent EKS Pod Identity API. The guide demonstrates automation techniques to ensure proper IAM role associations before application deployment, maintaining GitOps workflows while preventing permission-related failures.

In this post, we explore patterns and practices for building and operating distributed Amazon Elastic Kubernetes Service (Amazon EKS)-based applications effectively. We examine three deployment models – SaaS Provider Hosted, Remote Application Plane, and Hybrid Nodes – each offering distinct advantages for specific use cases as companies scale their software as a service (SaaS) offerings.

In this post, we demonstrate how to configure Amazon Route 53 to enable unique failover behavior for each application within multi-tenant Amazon EKS environments across AWS Regions. This solution allows organizations to maintain the cost benefits of shared infrastructure while meeting diverse availability requirements by implementing application-specific health checks that provide granular control over failover scenarios.

In this post, we demonstrate how to use a Raspberry Pi 5 as an Amazon EKS hybrid node to process edge workloads while maintaining cloud connectivity. We show how to set up an EKS cluster that connects cloud and edge infrastructure, secure connectivity using WireGuard VPN, enable container networking with Cilium, and implement a real-world IoT application using an ultrasonic sensor that demonstrates edge-cloud integration.