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Kubernetes on cgroup v1 is dead. Here’s what comes next.

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Kubernetes on cgroup v1 is dead. Here’s what comes next.

Welcome back to another edition of Road to KubeCon, where we’re tracking the latest movements in the cloud-native ecosystem as we prepare for KubeCon + CloudNativeCon North America 2026, happening November 9-12 in Salt Lake City, Utah.

In this edition, we consider what happens when compute workloads need to run AI on the edge. Underlying Kubernetes mechanics change, as do observability practices and security decisions. We take a look at the emerging tactics and how a couple of key projects are responding to these changes.

Check out the story below on opening up Kubernetes capacity, HPE’s advances in purpose-built compute for AI, a reminder to evolve a deprecated Linux kernel interface, and what to expect at this year’s Kubernetes on Edge Day and Cilium co-located events.

Using edge compute for AI inference makes sense for many reasons — you reduce unnecessary server calls, cut data egress fees, and keep data away from the cloud for compliance. As a result, many enterprises are turning to edge AI for these reasons 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.

However, as HPE’s Aaron Lamond notes in a recent HPE blog post, organizations often try to fit a square peg in a round hole when using unoptimized servers. “As intelligence becomes more distributed, purpose-built compute becomes increasingly critical to operational success,” he writes.

For Lamond, “purpose-built compute” should consider how hardware, software, security, and operations fit together.


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