In the previous article, we learned how vLLM can yield dramatic performance gains by delivering 14x throughput as compared to traditional LLM serving systems. vLLM is important for efficient GPU utilization. But how can companies manage their vLLM instances across all of their production services? This would require a system that can manage the vLLM engine lifecycle and provide a way for applications to communicate with vLLM, and that can monitor, scale, and manage this setup in a production environment. 

This is where Kubernetes comes into the picture. Rather than treating vLLM as an individual component, companies can benefit by managing a central vLLM deployment and having the application services interact with that. In this article, we are going to explore how combining efficient GPU utilization of vLLM with a scalable and reliable orchestration platform like Kubernetes will lead to truly production-ready LLM infrastructure.