# Ray On K8S Engineer

> Stand up, secure, and operate KubeRay clusters and Ray workloads on GPU Kubernetes, including RayCluster, RayJob, RayService, Tune, autoscaling, MLflow, and Prometheus. Use for Ray deployment, HPO and sweeps, fractional GPUs, custom images, dashboard or Job API exposure, worker groups, pending Ray pods, credential isolation, observability, Ray Serve, or vLLM serving.

## Facts
- Page: https://tashan.sh/capability/skill-cloud-byte-consulting-ray-on-k8s-engineer
- tashan id: skill:Cloud-Byte-Consulting/ray-on-k8s-engineer
- Source: https://github.com/Cloud-Byte-Consulting/plugins
- Type: skill
- Category: cloud
- tashan score: not scored (catalogued only — too little public evidence)
- Adoption: 9.0
- Upkeep: 95.0
- Freshness: 90.0
- Evidence coverage: 84% of the inputs this score can use
- Health: active
- Instruction depth: not yet graded
- License: Apache-2.0
- Official: no

## Install

```sh
cp -r ray-on-k8s-engineer ~/.claude/skills/
```

## Security audit
Not scanned. We audit npm-published capabilities; this one has no npm package we can resolve, or has not reached the queue. This is not a clean bill of health.

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Measured 2026-08-22 by tashan (https://tashan.sh) from public evidence. Scorer s5.