xinyun/vllm
1
0
Fork 0
mirror of https://git.datalinker.icu/vllm-project/vllm.git synced 2025-12-09 07:14:58 +08:00
Code Issues Packages Projects Releases Wiki Activity

[Docs] Add Kuberay to deployment integrations (#20592)

Browse Source 
Signed-off-by: Ricardo Decal <rdecal@anyscale.com>
This commit is contained in:
Ricardo Decal 2025-07-14 23:13:55 -04:00 committed by GitHub
parent d4170fad39
commit 054c8657e3
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
2 changed files with 21 additions and 0 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

20
docs/deployment/integrations/kuberay.md Normal file
View File

@ -0,0 +1,20 @@
# KubeRay
[KubeRay](https://github.com/ray-project/kuberay) provides a Kubernetes-native way to run vLLM workloads on Ray clusters.
A Ray cluster can be declared in YAML, and the operator then handles pod scheduling, networking configuration, restarts, and blue-green deployments — all while preserving the familiar Kubernetes experience.
## Why KubeRay instead of manual scripts?
| Feature | Manual scripts | KubeRay |
|---------|-----------------------------------------------------------|---------|
| Cluster bootstrap | Manually SSH into every node and run a script | One command to create or update the whole cluster: `kubectl apply -f cluster.yaml` |
| Autoscaling | Manual | Automatically patches CRDs for adjusting cluster size |
| Upgrades | Tear down & re-create manually | Blue/green deployment updates supported |
| Declarative config | Bash flags & environment variables | Git-ops-friendly YAML CRDs (RayCluster/RayService) |
Using KubeRay reduces the operational burden and simplifies integration of Ray + vLLM with existing Kubernetes workflows (CI/CD, secrets, storage classes, etc.).
## Learn more
* ["Serve a Large Language Model using Ray Serve LLM on Kubernetes"](https://docs.ray.io/en/master/cluster/kubernetes/examples/rayserve-llm-example.html) - An end-to-end example of how to serve a model using vLLM, KubeRay, and Ray Serve.
* [KubeRay documentation](https://docs.ray.io/en/latest/cluster/kubernetes/index.html)

1
docs/deployment/k8s.md
View File

@ -13,6 +13,7 @@ Alternatively, you can deploy vLLM to Kubernetes using any of the following:
- [Helm](frameworks/helm.md)
- [InftyAI/llmaz](integrations/llmaz.md)
- [KServe](integrations/kserve.md)
- [KubeRay](integrations/kuberay.md)
- [kubernetes-sigs/lws](frameworks/lws.md)
- [meta-llama/llama-stack](integrations/llamastack.md)
- [substratusai/kubeai](integrations/kubeai.md)