Category: Amazon Elastic Kubernetes Service

Learn how to manage your Amazon Elastic Kubernetes Service (Amazon EKS) clusters through simple conversations instead of complex kubectl commands or deep Kubernetes expertise. This post shows you how to use the new fully managed EKS Model Context Protocol (MCP) Server in Preview to deploy applications, troubleshoot issues, and upgrade clusters using natural language with no deep Kubernetes expertise required. We’ll walk through real scenarios showing how conversational AI turns multi-step manual tasks into simple natural language requests.

In this post, we provide a comprehensive guide to the 48 Amazon EKS and Kubernetes sessions at AWS re:Invent 2025, covering everything from simplified cluster management with Amazon EKS Auto Mode to advanced AI/ML workload orchestration, platform engineering, and production-grade security strategies. Whether you’re new to Kubernetes or architecting multi-region platforms, you’ll find sessions tailored to your needs across workshops, chalk talks, builders sessions, and hands-on experiences at the Containers kiosk in the AWS Village.

In this post, we demonstrate how to monitor network performance for Amazon EKS workloads using new advanced network observability features powered by Network Flow Monitor. We explore how to capture Kubernetes-enriched network metrics, export them to AWS Managed Open-Source services like Amazon Managed Service for Prometheus and Amazon Managed Grafana, and visualize critical performance indicators including throughput, packet drops, latency, and connection states across your containerized services.

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.