# Possible to deploy ray operator on K8s cluster without AVX hardware?

**URL:** <https://discuss.ray.io/t/possible-to-deploy-ray-operator-on-k8s-cluster-without-avx-hardware/6851>\
**Category:** Kubernetes\
**Created:** [July 16, 2022, 7:35pm UTC](https://discuss.ray.io/t/possible-to-deploy-ray-operator-on-k8s-cluster-without-avx-hardware/6851 "2022-07-16T19:35:05Z")\
**Posts on this page:** 2\
**Page:** 1

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**Author:** ![iqster](https://sea2.discourse-cdn.com/flex020/user_avatar/discuss.ray.io/iqster/32/2897_2.png) [@iqster](https://discuss.ray.io/u/iqster)\
**Post date:** [July 16, 2022, 7:35pm UTC](https://discuss.ray.io/t/possible-to-deploy-ray-operator-on-k8s-cluster-without-avx-hardware/6851/1 "2022-07-16T19:35:05Z")

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**How severe does this issue affect your experience of using Ray?**

- High: It blocks me to complete my task.

Hello … I have a K8s homelab that I was trying to deploy ray onto (using the helm chart). The ray operator pod terminates right away with error 132. I checked the docker logs and they seem to be empty. My hardware is an old AMD server class processor without AVX instructions, and I think that is the cause. Is there a version of the docker image where AVX became mandatory (without it being listed as a requirement)? If so, I can try out an older version of the image. I’d love to experiment with Ray Serve on my hardware for some upcoming projects, so am looking forward to a response.

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**Author:** ![ckw017](https://sea2.discourse-cdn.com/flex020/user_avatar/discuss.ray.io/ckw017/32/1683_2.png) [@ckw017](https://discuss.ray.io/u/ckw017)\
**Post date:** [August 16, 2022, 5:46pm UTC](https://discuss.ray.io/t/possible-to-deploy-ray-operator-on-k8s-cluster-without-avx-hardware/6851/2 "2022-08-16T17:46:04Z")

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What Ray version are you using? AFAIK this isn’t a direct dependency of Ray, but might have been pulled in by one of our dependencies.

Operator pod terminating immediately is a bit concerning. If possible, you can try running docker directly on your hardware, and then trying to `docker run` to get a shell into the docker image, and then run the pod’s command directly (should be able to find this info with `kubectl get pod/<ray operator pod> -o yaml`). This might provide some more useful output and let you poke around.