Running Ray on Kubernetes with KubeRay

In this episode of the Kubernetes Bytes podcast, Bhavin sits down with Kai-Hsun Chen, Software Engineer at Anyscale and maintainer of the KubeRay project. The discussion focuses on how the open source Ray project can help organizations use a single tool for data prep, model training, fine tuning and model serving workflows, both for their predictive AI and generative AI models. The discussion also dives into the KubeRay project and how it provides three different Kubernetes CRDs for Data Scientists to deploy Ray clusters on demand.

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Cloud Native News:

• https://azure.github.io/AKS/2024/08/23/fine-tuning-language-models-with-kaito
• https://orca.security/resources/blog/kubernetes-testing-environment/
• https://www.redhat.com/en/about/press-releases/red-hat-openstack-services-openshift-now-generally-available

Show links:

• Kai's LinkedIn: https://www.linkedin.com/in/kaihsun1996/
• KubeRay doc: https://docs.ray.io/en/latest/cluster/kubernetes/index.html
• Ray Summit registration: https://raysummit.anyscale.com/flow/anyscale/raysummit2024/reg/createaccount (code: KaiHsunC15)
• KubeRay repository: https://github.com/ray-project/kuberay
• Ray repository: https://github.com/ray-project/ray
• Ray Slack workspace: https://docs.google.com/forms/d/e/1FAIpQLSfAcoiLCHOguOm8e7Jnn-JJdZaCxPGjgVCvFijHB5PLaQLeig/viewform

Timestamps:

• 00:02:40 Cloud Native News
• 00:07:20 Interview with Kai
• 00:49:15 Key takeaways