
Ray & KubeRay, with Richard Liaw and Kai-Hsun Chen
About this episode
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.
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News of the week
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Kubernetes Podcast from Google episode 234 - LitmusChaos, with Karthik Satchitanand
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Google Cloud Blog - Run your AI inference applications on Cloud Run with NVIDIA GPUs
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Google Kubernetes Engine Release Notes - August 20, 2024 (1.31 available in Rapid Channel)
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Kubernetes Podcast from Google - Kubernetes v1.31: "Elli", with Angelos Kolaitis
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Red Hat Press Release - Red Hat OpenStack Services on OpenShift is Now Generally Available
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Red Hat Enables OpenStack to Run Natively on OpenShift Platform
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Broadcom Revamps Tanzu to Simplify Cloud-Native App Development and Deployment
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Tanzu Platform 10 Offers Cloud Foundry Users Deep Visibility and Productivity Enhancements
Links from the interview
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Ray: A Distributed System for AI by Robert Nishihara and Philipp Moritz - Jan 9, 2018
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Examples of schedulers for Batch/AI workloads in Kubernetes
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Examples of observability tools for Batch/AI workloads in Kubernetes
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Examples of loadbalancers
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Dask Python - Parallel Python
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Karpenter - "Just-in-time nodes for any Kubernetes cluster"
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Types of hardware accelerators
Links from the post-interview chat
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