Category: Learning Levels

In this post, we explore how to maximize Auto Mode’s value through comprehensive cost visibility, proactive governance, and continuous optimization strategies. We cover essential cost management dimensions: establishing spending visibility, forecasting resource needs, implementing governance controls, and measuring efficiency improvements. For both new and experienced Amazon EKS Auto Mode users, this guide offers actionable insights to balance performance, reliability, and cost-efficiency in Kubernetes deployments.

In this post, you’ll learn to back up and restore Amazon EKS cluster resources and persistent volume data using Velero. You’ll deploy a sample stateful application, back it up, and restore it to a different namespace within the same cluster. Along the way, you’ll configure least-privilege AWS Identity and Access Management (AWS IAM) roles using Amazon EKS Pod Identity and scope Velero’s Kubernetes permissions with a custom ClusterRole. A ClusterRole is a Kubernetes resource that defines cluster-wide permissions.

In this post, we walk through how linear and canary strategies work in Amazon ECS, how to configure each, and how to set up automatic rollbacks with CloudWatch alarms.

In this post, we walk you through a complete cross-Region DR implementation for Amazon EKS using AWS Backup. We deploy a stateful retail store application in a source Region, back it up, copy the backup to a DR Region, and restore the full application, including its persistent data, to a pre-provisioned cluster in the secondary Region. By the end of this walkthrough, you will have a fully functional DR environment with your application running in the secondary Region with all stateful data intact.

In this post, you’ll learn how to: (1) enable Container Network Observability in your Amazon EKS cluster, (2) identify and reduce inter-AZ traffic using traffic distribution control, (3) identify and reduce NAT gateway costs by implementing Amazon Virtual Private Cloud (VPC) endpoints, and (4) automate monitoring and reporting with an AI agent. This technical guide assumes familiarity with Kubernetes concepts and AWS networking basics.

In this post, we show you how to implement SPIFFE/SPIRE on Amazon EKS to establish secure service-to-service communication using a nested architecture. You’ll learn how to deploy SPIRE across multiple Amazon EKS clusters, configure workload attestation, and implement fine-grained authorization policies that scale with your infrastructure.

This post covers how EKS Auto Mode handles VPC CNI optimization, pod density scaling, network security implementation, and hybrid connectivity.

In this post, we demonstrate how AWS DevOps Agent works—from alert generation to identifying the affected EKS cluster, building knowledge graphs, and troubleshooting application or infrastructure issues, ultimately reducing MTTI and MTTR for your Kubernetes operations.

This post demonstrates a real-world example of integrating EKS Hybrid Nodes with NVIDIA DGX Spark, a compact and energy-efficient GPU platform optimized for edge AI deployment. In this post we walk you through deploying a large language model (LLM) for low-latency generative AI inference on-premises, setting up node monitoring and GPU observability with centralized management through Amazon EKS.

In this post, we will walk you through building an automated deployment pipeline using GitHub Actions. You will create a workflow that triggers on code changes, builds Docker images, pushes them to Amazon ECR, and deploys to Amazon ECS Express Mode using IAM roles for secure authentication. By the end, you will have a continuous integration and continuous delivery (CI/CD) workflow that automatically deploys your application when you push code.