Synthèse
For more than a decade, the cloud native community has built the infrastructure that runs the modern internet. Kubernetes and the CNCF ecosystem gave organizations a common way to orchestrate complex, distributed applications across heterogeneous environments at global scale. AI workloads are landing on that same foundation because they need the same things: dynamic scheduling, observability, networking, and coordination that holds together when individual components fail. What is still missing
For more than a decade, the cloud native community has built the infrastructure that runs the modern internet. Kubernetes and the CNCF ecosystem gave organizations a common way to orchestrate complex, distributed applications across heterogeneous environments at global scale. AI workloads are landing on that same foundation because they need the same things: dynamic scheduling, observability, networking, and coordination that holds together when individual components fail. What is still missing is first-class support for GPUs in that foundation. The cloud native ecosystem knows how to schedule, network, observe, and secure distributed workloads.
Bringing that same flexibility to GPUs is the opportunity in front of the community.