Model Serving an Opensource model via vLLM on Kubernetes(AKS)- Full Demo

In this hands-on project, you'll learn how to deploy and serve a Large Language Model (LLM) on Azure Kubernetes Service (AKS) using vLLM, Terraform, Kubernetes, and the NVIDIA GPU Operator. This is a practical, production-oriented project that demonstrates how AI Infrastructure Engineers, MLOps Engineers, LLMOps Engineers, and GenAI Engineers deploy open-source LLMs on GPU infrastructure. Instead of simply calling an API like GPT or Claude, you'll learn how to self-host an open-source model and expose an OpenAI-compatible inference endpoint for real-world AI applications. 📌 In this video you'll learn: ✅ Deploy Azure AKS using Terraform ✅ Configure GPU Node Pool ✅ Install NVIDIA GPU Operator ✅ Deploy vLLM on Kubernetes ✅ Serve Qwen2.5-7B-AWQ ✅ Understand GPU Scheduling ✅ Configure GPU Memory ✅ Understand KV Cache ✅ Deploy OpenAI Compatible API ✅ Verify GPU Utilization ✅ Production LLM Serving Best Practices ✅ Cost Optimization ✅ Interview Questions 🛠️ Tech Stack • Azure AKS • Kubernetes • Terraform • vLLM • NVIDIA GPU Operator • Helm • Qwen2.5-7B-Instruct-AWQ • OpenAI Compatible API • NVIDIA GPU • Azure CLI