#karpenter

Guide to building Agentic AI platform using Amazon EKS and open-source ecosystem

Optimal node strategies for GPU workloads across EKS Auto Mode, Karpenter, MNG, and Hybrid Nodes

GPU resource management and cost optimization using Karpenter, KEDA, and DRA on EKS

EKS GPU node strategy, Karpenter·KEDA·DRA resource management, NVIDIA GPU stack, AWS Neuron stack — the accelerated computing layer covering GPUs and AWS custom accelerators

llm-d architecture concepts, KV Cache-aware routing, Disaggregated Serving, EKS Auto Mode integration strategy

2-Tier GPU autoscaling (KEDA·Karpenter), DRA compatibility, and operational lessons learned from large MoE model (GLM-5·Kimi K2.5) deployments for LLM serving

An architecture that automates open-weight model onboarding through a seven-stage pipeline, from HuggingFace leaderboard scanning and benchmark reproduction to instance performance profiling, deployment guide generation for multiple targets, and global Spot capacity acquisition, with human involvement at approval gates

How Pod IPs on EKS consume subnet addresses, VPC NAU, and branch ENI limits, and how to keep Karpenter's instance-size fallback from turning into IP exhaustion through NodePool and VPC CNI settings.

In-depth debugging guide for the Karpenter autoscaler

Guide to diagnosing and resolving EKS node issues

FinOps guidance for Amazon EKS cost allocation and optimization with SCAD, CUR 2.0, Karpenter v1.13, tagging, per-container rightsizing, and ROI verification.

Karpenter autoscaling, Pod resource optimization, and EKS cost management strategies

Node provisioning, scaling signals, readiness, and cost validation with Karpenter v1.13 and EKS Auto Mode

Designs a highly available GenAI inference layer for EKS Hybrid Nodes GPU nodes with resource isolation (taints), a hybrid-only NVIDIA Device Plugin deployment, and a Karpenter-based cloud GPU fallback NodePool.