Shaun O’Meara, CTO at Mirantis, described the platform services layer that sits above the GPU infrastructure and is delivered through Mirantis k0rdent AI. The PaaS stack is organized around composable service templates that let operators expose training, inference, and data services to tenants. Services can be chained, extended, and validated without requiring custom integration work for every new workload.

A central example in this segment was the use of NVIDIA’s Run.ai as the delivery platform for inference workloads. Anjelica Ambrosio demonstrated the workflow. She deployed an inference cluster template, selected GPU node profiles, and then added Run.ai services as part of the cluster composition. From the Mirantis k0rdent AI portal, she navigated into the Run.ai console to show inference jobs running against the GPU pool. The demonstration highlighted how Mirantis integrates Run.ai into its templated deployment model so that all dependencies, such as cert-manager, GPU operators, and Argo, are automatically provisioned. What would normally require a complex chain of manual installations was shown as a single cluster deployment taking about fifteen minutes on AWS, most of which was machine startup time.

O’Meara explained that the catalog approach lets operators bring in Run.ai alongside other frameworks like Kubeflow or MLflow depending on customer preference. The system labels GPU nodes during cluster creation, and Run.ai validates those labels to ensure that only GPU-backed nodes run GPU workloads while other tasks are placed on CPU nodes. This improves cost efficiency and prevents GPU starvation.

The PaaS stack makes GPU infrastructure usable in business terms. Enterprises can use the catalog internally to accelerate development or publish services externally for customers. Sovereign operators can keep the Run.ai-based services on local GPU hardware in air-gapped form, while hybrid operators can extend them across public and private GPU footprints. By integrating NVIDIA Run.ai directly into Mirantis k0rdent AI, the platform demonstrates how complex AI services can be delivered quickly, with governance and observability intact, and without the fragile manual integration that normally burdens GPU PaaS environments.

Presented by Shaun O’Meara, CTO, and Anjelica Ambrosio, Product Marketing Specialist, Mirantis. Recorded live on September 11, 2025, at AI Infrastructure Field Day 3 in Santa Clara, California. Watch the entire presentation at https://techfieldday.com/appearance/mirantis-presents-at-ai-infrastructure-field-day-3/ or visit https://www.mirantis.com or https://techfieldday.com/event/aiifd3/ for more information.