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Kubernetes just formed a workload conformance group. Here’s why it matters for AI teams.

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Kubernetes just formed a workload conformance group. Here’s why it matters for AI teams.

Welcome to the final edition of Road to KubeCon, where we track the Kubernetes and cloud-native ecosystem each week on The New Stack as we head into KubeCon + CloudNativeCon NA, November 9-12 in Salt Lake City, Utah.

This week we explore how Kubernetes is getting new guidance for running AI workloads, including a new book from TNS, a dedicated Kubernetes working group, and advice on running LLMs across multiple GPUs.

Also in this day-before-Halloween-timed column, we’ve got OTel operators speaking a new language, security horrors from the latest AGNTCon + MCPCon, and untangling the dark webs of Kubernetes pod troubleshooting gone awry.

HPE will have a big presence at KubeCon NA this year. The gold sponsor will be at Booths 151 and 145, where they’ll present live sessions throughout the day on topics spanning vSphere, HPE Kubernetes Service (HKS), distributed inference, setting up cloud storage for Kubernetes, and more.

Hewlett Packard Enterprise (HPE) is a presenting sponsor of Road to KubeCon. HPE Software helps IT organizations modernize infrastructure, streamline operations, and accelerate AI initiatives across hybrid, multi-vendor environments.

This year, the focus is on gaining visibility and control across Kubernetes environments across VMs, infrastructure, and clouds. If you’d like to schedule a meeting with an HPE representative, contact jennifer.osuna@hpe.com.

In partnership with HPE, The New Stack has published a helpful book containing ten checks for teams running AI workloads on Kubernetes. The book, Kubernetes in 2027: Building Platforms for AI, Autonomy, and Scale , is available for download now.


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