Our talk commences with an insightful exploration into the fundamental concepts of Graph, Graph Databases, and NebulaGraph. We will demystify the innovative integration of Graph + Large Language Models (LLM) and demonstrate how this potent combination enhances both existing LLM stacks and Knowledge Graph processes. Moving forward, the spotlight will be on Docker and Docker Extensions, and how containerization and the docker extension facilitate a seamless development and learning environment for NebulaGraph, NebulaGraph AI, and NebulaGraph LLM. We will delve into the practicalities of utilizing these technologies, revealing how they can simplify intricate processes into one-click solutions. This talk will show how leveraging Docker can optimize your infrastructure, accelerate dev/production deployment, and increase the efficiency of your AI development process. It is a must-attend for those intrigued by the potential of streamlining distributed graph-based machine learning and AI infrastructure.