eks-genai
byaws-samples· 161 skills
Use whenever someone is building, training, fine-tuning, or serving a generative AI / LLM workload on Amazon EKS — phrased as "GPU vs Trainium/Inferentia", "vLLM on EKS", "Ray Serve / KubeRay", "distributed training on EKS", "FSx for Lustre for ML", "Karpenter for GPU", "EFA / NCCL multi-node", "DCGM / Neuron Monitor", "LiteLLM / AI gateway", "RAG on EKS", "agentic AI on EKS", or "self-host Llama / Mistral / Qwen". Walks the opinionated 6-layer stack (compute → cluster/scheduler → frameworks → storage → observability → AI gateway), the GPU-vs-Neuron decision, the JARK + vLLM + LiteLLM canonical reference, KV-cache tiering, cost levers (Neuron, Spot, Capacity Blocks), and a non-negotiable security baseline. Trigger even if "GenAI" is never said — any GPU/Neuron, inference-serving, or distributed-training decision on EKS qualifies. Skip for SageMaker-only or Bedrock-only (no self-hosting) asks, and for generic cluster design/build with no AI/ML workload (use eks-design / eks-build).
How to install eks-genai?
aws-samples/sample-apex-skills/eks-genai
$npx -y skills add aws-samples/sample-apex-skills --skill eks-genaiInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/aws-samples/sample-apex-skills" --skill "aws-samples/sample-apex-skills/eks-genai"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/aws-samples/sample-apex-skills" that are relevant to the current task. Run `npx skills add "https://github.com/aws-samples/sample-apex-skills"` and select the relevant skills, then follow their instructions.
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