🧠💥 My HomeLab GPU Cluster – 12× RTX 5090, AI / K8s / Self-Hosted Everything

After months of planning, wiring, airflow tuning, and too many late nights this is my home lab GPU cluster finally up and running. This setup is built mainly for: • AI / LLM inference & training • Image & video generation pipelines • Kubernetes + GPU scheduling • Self-hosted APIs & experiments 🔧 Hardware Overview • Total GPUs: 12 × RTX 5090 • Layout: 6 machines × 2 GPUs each • Gpu Machine Memory: 128 GB per Machne • Total VRAM: 1.5 TB+ • CPU: 88 cores / 176 threads per server • System RAM: 256 GB per machine 🖥️ Infrastructure • Dedicated rack with managed switches • Clean airflow-focused cases (no open mining frames) • GPU nodes exposed via Kubernetes • Separate workstation + monitoring setup • Everything self-hosted (no cloud dependency) 🌡️ Cooling & Power • Tuned fan curves + optimized case airflow • Stable thermals even under sustained load • Power isolation per node (learned this the hard way 😅) 🚀 What I’m Running • Kubernetes with GPU-aware scheduling • Multiple AI workloads (LLMs, diffusion, video) • Custom API layer for routing GPU jobs • NAS-backed storage + backups This is 100% a learning + building lab, not a mining rig.