gpu-resource-management
OfficialOptimize GPU resource management on EKS with Karpenter and KEDA.
Authoraws-samples
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill helps optimize GPU resource management on EKS by utilizing Karpenter and KEDA for efficient NodePool scaling and GPU partitioning.
Core Features & Use Cases
- GPU Orchestration: Design and manage GPU NodePools with Karpenter.
- Auto-scaling: Implement KEDA for scaling-to-zero and HPA for pod-level scaling.
- GPU Partitioning: Use DRA for Multi-Instance GPU (MIG) partitioning.
- Use Case: Ideal for environments with mixed instance types and need to manage spot and on-demand instances effectively.
Quick Start
Design a GPU NodePool using Karpenter and implement scaling strategies with KEDA.
Dependency Matrix
Required Modules
karpenter.shkeda.shmcp__eksmcp__aws-pricingmcp__aws-documentationmcp__prometheus
Components
scriptsreferences
💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: gpu-resource-management Download link: https://github.com/aws-samples/sample-oh-my-aidlcops/archive/main.zip#gpu-resource-management Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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