Category: Technical How-to

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.

Amazon ECS today launched a fully managed, remote Model Context Protocol (MCP) server in preview, enabling AI agents to provide deep contextual knowledge of ECS workflows, APIs, and best practices for more accurate guidance throughout your application lifecycle. In this post, we walk through how to streamline your container troubleshooting using the Amazon ECS MCP server, which offers intelligent AI-assisted inspection and diagnostics through natural language queries in CLI tools like Kiro, IDEs like Cline and Cursor, and directly within the Amazon ECS console through Amazon Q.

Container image security is critical for modern applications with the increasing adoption of containerized workloads. Organizations need reliable ways to verify the authenticity and integrity of their container images. Amazon Elastic Container Registry (Amazon ECR) now offers managed signing as a streamlined approach to automatically sign container images when they are pushed to the Amazon […]

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 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 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 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.