Uploaded July 2026 | Updated September 2026, 2 weeks ago
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Rab Ne Bana Di Jodi - Why Platforms & AI Need Each Other - Ram Iyengar, Cloud Foundry Foundation
A match made in heaven, or one hell of a couple? Platform teams spent 2 years perfecting golden paths for cloud-native infrastructure. 5 engineers managing 100 services.
Last week, a new AI agent generated the same config in 30 seconds. This week they're managing 5 LLM models across 200 services. The future seems one-sided. This couple needs counselling.
This is escalating abstraction: Platforms reduce k8s chaos. AI automates those paths at breakneck speed. But AI-generated configs violate platform policies. Platforms enforce governance via admission controllers. Governance needs observability. Observability reveals the gap: no model lifecycle management, no agent audit trails, no cost control APIs.
This talk traces real interdependencies: deprecating models, managing sprawl, isolating agents, controlling budgets. You'll learn what exists - CNCF AI Conformance, tools, working groups & the critical gaps.
Right now, there's no greater agony than rationalising AI without platforms.
Don't miss out! Join us at our next KubeCon + CloudNativeCon events in Yokohama, Japan (29-30 July, 2026), and Shanghai, China (8-9 September, 2026) Salt Lake City, United States (Nov 9–12, 2026). Connect with our current graduated, incubating, and sandbox projects as the community gathers to further the education and advancement of cloud native computing. Learn more at kubecon.io
Rab Ne Bana Di Jodi - Why Platforms & AI Need Each Other - Ram Iyengar, Cloud Foundry Foundation
A match made in heaven, or one hell of a couple? Platform teams spent 2 years perfecting golden paths for cloud-native infrastructure. 5 engineers managing 100 services.
Last week, a new AI agent generated the same config in 30 seconds. This week they're managing 5 LLM models across 200 services. The future seems one-sided. This couple needs counselling.
This is escalating abstraction: Platforms reduce k8s chaos. AI automates those paths at breakneck speed. But AI-generated configs violate platform policies. Platforms enforce governance via admission controllers. Governance needs observability. Observability reveals the gap: no model lifecycle management, no agent audit trails, no cost control APIs.
This talk traces real interdependencies: deprecating models, managing sprawl, isolating agents, controlling budgets. You'll learn what exists - CNCF AI Conformance, tools, working groups & the critical gaps.
Right now, there's no greater agony than rationalising AI without platforms.
