In this edition we feature several exciting announcements related to Amazon EKS including but not limited to Amazon EKS support for Kubernetes version 1.33, launch of most anticipated Model Context Protocol (MCP) Servers and centralized EKS Dashboard
New AWS services and features
Amazon EKS and Amazon EKS Distro now supports Kubernetes version 1.33
- Amazon EKS now supports Kubernetes version 1.33 in all the AWS Regions where EKS is available, including the AWS GovCloud (US) Regions.
- Kubernetes version 1.33 includes stable support for sidecar containers, topology-aware routing and traffic distribution, and consideration of taints and tolerations when calculating pod topology spread constraints, ensuring that pods are distributed across different topologies according to their specified tolerance.
- This release also adds support for user namespaces within Linux pods, dynamic resource allocation for network interfaces, and in-place resource resizing for vertical scaling of pods.
Announcing new Model Context Protocol (MCP) Servers for AWS Serverless and Containers
- Model Context Protocol(MCP) servers are a standard interface to enhance AI-assisted application development by equipping AI code assistants with real-time, contextual understanding of AWS service in interaction.
- With this launch, there are now new MCP servers to interact with Amazon EKS in addition to Amazon Elastic Container Service (ECS), AWS Lambda and Finch.
- With MCP servers integrated into AI code assistants such as Amazon Q Developer, while building applications on Amazon EKS developers can now use natural language to describe their requirements while AI code assistants handle service configurations, infrastructure setup, and cross-service integrations.To learn more, navigate to documentation here
- As you expand your Kubernetes footprint to address operational and strategic objectives, such as improving availability, ensuring business continuity, isolating workloads, and scaling infrastructure, centralized visibility across your Kubernetes infrastructure would be an essential requirement.
- With this launch, Amazon Elastic Kubernetes Service (Amazon EKS) now offers EKS Dashboard, a centralized dashboard that can provide visibility across multiple AWS regions and accounts.
Amazon EKS introduces configuration insights for Amazon EKS Hybrid Nodes
- Amazon EKS cluster insights provide detection of issues and recommendations to resolve them to help you manage your cluster.Amazon EKS provides two types of insights: Configuration insights and Upgrade insights.
- With this launch of Configuration Insights, Amazon Elastic Kubernetes Service (Amazon EKS) now offers help in identifying misconfigurations in your EKS Hybrid Nodes setup that could impair functionality of your cluster or workloads.
Amazon Inspector enhances container security by mapping ECR images to running containers
- Amazon Inspector now automatically maps your Amazon Elastic Container Registry (Amazon ECR) images to specific pods running on Amazon Elastic Kubernetes Service (Amazon EKS), helping identify where the images are actively in use.
- With this launch, you can use Amazon Inspector console or APIs to identify your actively used container images, when you last used an image, and which clusters are running the image, thereby focusing resources on patching most critical vulnerable images and improving mean-time to remediation.
AWS blogs
[Blog] Accelerating application development with the Amazon EKS MCP server
- Large Language Models (LLMs) have revolutionized the way developers write code.As an open standard, MCP creates a standardized interface that empowers LLMs to tap into current, contextual information, making them even more powerful and precise in supporting specific application development use cases. This synergy between LLMs and MCP represents a significant advancement in AI-assisted development.
- This blog article is intended to serve as walkthrough on newly launched EKS MCP Server and tools it provides for AI assisted EKS interactions.
- Generative artificial intelligence (AI) applications are commonly built using a technique called Retrieval Augmented Generation (RAG) that provides foundation models (FMs) access to additional data they didn’t have during training.
- This blog article serves as a guide for a solution that leverages using Amazon Elastic Kubernetes Service (EKS) with Amazon Bedrock to build scalable and containerized RAG solutions for your generative AI applications
[Blog] How to automate incident response for Amazon EKS on Amazon EC2
- Triaging and quickly responding to security events is important to minimize impact within an AWS environment. When using Amazon EKS with EC2 nodes, automated forensics during an incident is very essential.
- This blog article serves as walkthrough guide for Automated Forensics Orchestrator solution for Amazon EKS.
[Blog] Introducing AI on EKS: powering scalable AI workloads with Amazon EKS
- AI on EKS is a new open source initiative from Amazon Web Services (AWS) designed to help customers deploy, scale, and optimize artificial intelligence/machine learning (AI/ML) workloads on Amazon Elastic Kubernetes Service (Amazon EKS).
- This blog article serves as a project introduction guide while covering a blueprint walkthrough.
[Blog] Streamline multi-environment deployments with Amazon EKS Blueprints and CDK pipelines
- Users are looking for ways to automate the deployment and maintenance of their Amazon Elastic Kubernetes Service (Amazon EKS) clusters across different versions, environments, accounts, and AWS Regions.
- This blog article serves as deep dive walkthrough on setting up automated pipelines for deploying and updating Amazon EKS infrastructure using the CDK pipelines module, which is part of Amazon EKS Blueprints for CDK.
- EKS clusters are often shared by multiple teams within an organization, allowing them to efficiently use available resources.
- This blog article serves as guide on leveraging vCluster for separating workloads on a shared EKS cluster.
[Blog] Optimizing data lakes with Amazon S3 Tables and Apache Spark on Amazon EKS
- Apache Iceberg has emerged as a popular solution, helping companies organize and analyze their expanding data collections efficiently. Although Apache Iceberg on Amazon S3 has become a widely adopted format for building data lakehouses, managing Iceberg tables at scale comes with operational challenges. To address these complexities, Amazon S3 Tables delivers a fully managed table storage service with built-in Apache Iceberg support.
- For organizations running Apache Spark on Amazon Elastic Kubernetes Service (Amazon EKS) with Iceberg tables in general purpose S3 buckets, S3 Tables streamlines management and improves performance.
- This blog articles serves as walks through guide on how to integrate S3 Tables with Apache Spark on Amazon EKS.
Community news and articles
Agentic AI Operations Hub with Remote MCP Server on Amazon EKS and Amazon Bedrock
- The article serves as introduction for Agentic AI Operations Hub - a revolutionary platform that combines the power of Model Context Protocol (MCP), Amazon Bedrock, and intelligent agents on Amazon EKS to transform how we manage database operations.
Cost-Effective LLM Serving with Optimal TP/DP on EKS using Inf2.48xl and g5.12xl
- This article explores how LLM inference costs can be optimized using EKS with Inf2.48xl and g5.12xl.
Q-Bits:Streamlining EKS Cluster Autoscaling with Amazon Q Developer
- This article explores how Q Developer can generate YAML configurations, explain complex scaling concepts, and provide tailored solutions for optimizing your EKS resources.
Videos and webinars
Open source projects
- KAI Scheduler
- KAI Scheduler is a robust, efficient, and scalable Kubernetes scheduler that optimizes GPU resource allocation for AI and machine learning workloads.