Python-Based IaC Tackles Non-Homogeneous GPU Configs in Ray Clusters

Managing Ray clusters with diverse GPU models like A100 and V100 leads to resource fragmentation and performance issues. A Python-centric Infrastructure as Code approach using modular policies and containerization can optimize task scheduling and reduce configuration drift. This method addresses cloud provider inconsistencies and version compatibility risks in AI/ML workflows.