A year in, Google wants its Axion processors to feel like a scheduling decision
At KubeCon Europe, Google Cloud’s Jago Macleod and Abdel Sghiouar argued that adopting Arm for Kubernetes workloads has shifted from a complex migration to a practical, low-friction choice. After a year of production use, Google’s custom Arm-based Axion processors—powering C4A and N4A instances—are positioned as broadly viable for most containerized applications, offering strong gains in performance, cost efficiency, and energy usage compared to x86.
Rather than requiring a full overhaul, moving to Arm typically involves recompiling containers for a multi-architecture target and gradually rolling out via Kubernetes practices like canary deployments. While edge cases exist, they are relatively uncommon.
A key enabler is GKE’s compute classes, which allow workloads to express preferences across VM types, turning infrastructure decisions into automated scheduling choices rather than manual provisioning.
Ultimately, the conversation points to a larger constraint: energy. As AI workloads grow, efficiency—measured in “tokens per watt”—is emerging as the defining metric, with cost savings translating directly into greater compute capacity.
Learn more from The New Stack about the latest developments around Google’s work with Axion:
Arm: See a Demo About Migrating a x86-Based App to ARM64
Do All Your AI Workloads Actually Require Expensive GPUs?
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K8s vs serverless for distributed systems
Listener Joe Davidson recently tweeted: “I’d really be interested in an episode debating Kubernetes vs serverless functions for distributed systems. As someone working a lot with serverless to create large scale systems, for me the complexity in Kubernetes doesn’t seem worth it, especially when onboarding new people. But I’d like to see it from the other perspectives. I could be missing something.”
So we invited Joe on the show alongside Abdel Sghiouar and Srdjan Petrovic to discuss!
Join the discussion
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Featuring:
Joe Davidson – GitHub, X
Abdel Sghiouar – GitHub, LinkedIn, X
Srdjan Petrovic – X
Natalie Pistunovich – GitHub, X
Show Notes:
Cncf landscape
Article: Shifting left is for suckers. Shift down instead
Service Weaver
Firebase
Range: Why Generalists Triumph in a Specialized world
CloudRun
Knative
Fargate
Dapr
Azure Container Apps
Kelsey Hightower’s Tweet on k8s becoming an operating system for the cloud
Something missing or broken? PRs welcome!