Run Model-as-a-Service for multiple LLMs on OpenShift

This blog post provides a comprehensive guide on implementing a Model-as-a-Service (MaaS) architecture for managing multiple large language models (LLMs) within an OpenShift environment. It outlines the benefits of a unified endpoint for AI inference, explains the routing mechanism for model requests, and offers step-by-step instructions on deploying the necessary infrastructure using various open-source tools. The guide emphasizes operational efficiency, reduced GPU wastage, and simplified application logic by centralizing model access through a single API endpoint.