Ray & KubeRay, with Richard Liaw and Kai-Hsun Chen
Description
In this episode, guest host and AI correspondent Mofi Rahman interviews Richard Liaw and Kai-Hsun Chen from Anyscale about Ray and KubeRay. Ray is an open-source unified compute framework that makes it easy to scale AI and Python workloads, while KubeRay integrates Ray’s capabilities into Kubernetes clusters.
Do you have something cool to share? Some questions? Let us know:
- web: kubernetespodcast.com
- mail: kubernetespodcast@google.com
- twitter: @kubernetespod
News of the week
-
Kubernetes Podcast from Google episode 234 - LitmusChaos, with Karthik Satchitanand
-
Google Cloud Blog - Run your AI inference applications on Cloud Run with NVIDIA GPUs
-
Google Kubernetes Engine Release Notes - August 20, 2024 (1.31 available in Rapid Channel)
-
Kubernetes Podcast from Google - Kubernetes v1.31: "Elli", with Angelos Kolaitis
-
Red Hat Press Release - Red Hat OpenStack Services on OpenShift is Now Generally Available
-
Red Hat Enables OpenStack to Run Natively on OpenShift Platform
-
Broadcom Revamps Tanzu to Simplify Cloud-Native App Development and Deployment
-
Tanzu Platform 10 Offers Cloud Foundry Users Deep Visibility and Productivity Enhancements
Links from the interview
-
Ray: A Distributed System for AI by Robert Nishihara and Philipp Moritz - Jan 9, 2018
-
Examples of schedulers for Batch/AI workloads in Kubernetes
-
Examples of observability tools for Batch/AI workloads in Kubernetes
-
Examples of loadbalancers
-
Dask Python - Parallel Python
-
Karpenter - “Just-in-time nodes for any Kubernetes cluster”
-
Types of hardware accelerators
<li dir="ltr" ar