Capacity without conflict: A guide to multi-tenant GPU cluster design for AI-native teams

This post details the design principles, common failure modes, and implementation of multi-tenant GPU cluster architecture, focusing on pooled capacity, tenant isolation, and self-serve access. It outlines the two-layer infrastructure pattern (shared foundation, per-tenant top layer), quota-based allocation for capacity management, flexible configuration options for tenants, and robust GPU health check/node repair mechanisms. The goal is to provide data center unit economics with cloud-like flexibility and self-service velocity for AI-native teams.