# Ray Serve

URL: https://donedeploy.com/technologies/ray-serve/

[!AI · November 2, 2026CI/CD for Models and PromptsEvaluation gates, model registries, canary releases and rollback: applying CI/CD discipline to prompts and models in LLM applications.](https://donedeploy.com/cicd-for-llms/)[!AI · October 23, 2026Fine-Tuning or Prompting? A Decision Guide for Small TeamsWhen prompting, RAG or fine-tuning is the right way to adapt a language model, and what each one costs a small engineering team.](https://donedeploy.com/fine-tuning-or-prompting/)

Questions

## Ray Serve: frequently asked

How is Ray Serve different from vLLM?

vLLM is an engine for serving language models efficiently. Ray Serve is a general framework for composing and scaling models and code, and can use vLLM inside it.

Do we need Kubernetes to use Ray Serve?

No, Ray can run on plain VMs. For production we usually recommend Kubernetes with KubeRay for upgrades, recovery and resource management.

Running Ray Serve, or deciding whether to? Tell us what you have; the first consultation is free.

[Let's talk »](https://donedeploy.com/lets-talk/)