EKS Auto Mode Skills

Setting up EKS Auto Mode using Terraform

Automate Kubernetes the easy way. Deploy once, explore GPU, Spot, Graviton, cost optimization, ODCR, disruption budgets, observability, and more. Minimal add-on management. Auto Mode handles core compute, storage, and networking add-ons for you.

Table of Contents

• Overview
• Prerequisites
• Claude Code Skills (Plugin)
• Quick Start
• Examples
• Cleanup
• Configuration
• Components
• Learn More
• Contributing
• License and Disclaimer

Overview

Amazon EKS Auto Mode simplifies Kubernetes cluster management by automating compute, storage, and networking decisions. Under the hood it runs Karpenter, the AWS Load Balancer Controller, and the EBS CSI driver as managed components. You get the benefits without installing or upgrading any of them.

This repository is an educational companion. Each example demonstrates a specific EKS Auto Mode pattern (Graviton, GPU, Spot, ODCR targeting, disruption budgets, etc.) with a self-contained README explaining the "why" alongside the "how." Deploy the base cluster once, then apply individual examples to explore.

Key capabilities covered:

• Graviton (ARM64) and x86 workloads side by side
• GPU and Inferentia2 (Neuron) ML inference
• Spot and On-Demand mixed pools with overprovision headroom
• On-Demand Capacity Reservation targeting
• Static capacity pools and disruption budgets
• HPA and KEDA-driven autoscaling
• KMS encryption for ephemeral node storage
• CloudWatch Container Insights observability
• 5-layer resource tagging for cost allocation

Prerequisites

Required Tools:

• AWS CLI
• kubectl
• Terraform

Note: This project currently provides Linux-specific commands in the examples. Windows compatibility will be added in future updates.

Claude Code Skills (Plugin)

This repo ships as a Claude Code plugin with two AI-assisted skills for EKS Auto Mode:

Skill	Audience	What it covers
eks-automode-onboard	Newcomers	Concepts, deployment, example selection, troubleshooting
eks-automode-maintain	Repo maintainers	Rendering chain, 5-layer tagging, docs sync, PR checklist

Install

/plugin marketplace add https://github.com/aws-samples/sample-aws-eks-auto-mode.git

/plugin install eks-automode@sample-aws-eks-auto-mode

Alternative: manual install

git clone https://github.com/aws-samples/sample-aws-eks-auto-mode.git
cp -r sample-aws-eks-auto-mode/skills/eks-automode-onboard ~/.claude/skills/
cp -r sample-aws-eks-auto-mode/skills/eks-automode-maintain ~/.claude/skills/

Quick Start

1. Clone Repository:

git clone https://github.com/aws-samples/sample-aws-eks-auto-mode.git
cd sample-aws-eks-auto-mode

2. Deploy Cluster:

cd terraform
terraform init
terraform apply -auto-approve

# Configure kubectl
$(terraform output -raw configure_kubectl)

3. Apply an example (e.g., Graviton):

kubectl apply -f examples/graviton/

Examples

Each example has its own README with detailed explanations of the underlying mechanics.

Compute Patterns

Example	Description
Graviton	ARM64 workloads on cost-effective Graviton instances. Deploys a 2048 game.
Spot	Fault-tolerant workloads on EC2 Spot with diverse instance families. Deploys a 2048 game.
GPU	GPU-accelerated ML inference (Qwen 3 on NVIDIA GPUs).
Neuron	ML inference on AWS Inferentia2 (DeepSeek-R1-Qwen3-8B served by vLLM).

Cost Optimization

Example	Description
Cost Optimization	OD/Spot mixed pools with weighted priorities and pause-pod overprovision headroom.

Advanced Scheduling