The next stages of AI conformance in the cloud-native, open-source world
From The New Stack Podcast by The New Stack
April 9, 2026 · 25 min · Episode 1604
About this episode
This episode discusses the challenges of running AI models on Kubernetes and the importance of standardization for AI workloads.
Running AI models on Kubernetes has historically been inconsistent, with workloads behaving differently across cloud providers due to variations in GPUs, networking, and autoscaling. As organizations move AI from experimentation to production, standardization has become critical. In this episode of The New Stack Makers, Jonathan Bryce, Executive Director of The Cloud Native Computing Foundation shared that the Foundation’s Kubernetes AI conformance program aims to solve this by ensuring portability, predictability, and production readiness for AI workloads across environments.
People in this episode
Host: The New Stack
Guest: Jonathan Bryce
Topics covered
- AI conformance
- cloud-native
- open-source
- Kubernetes
- standardization
- production readiness
Keywords
- AI models
- Kubernetes
- cloud providers
- production
- workloads
- autoscaling
- predictability
Mentioned in this episode
Organizations: The Cloud Native Computing Foundation, Kubernetes
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