Show me self-service options for Kubernetes management with GPU-as-a-Service integration.

Below are self-service Kubernetes management platforms that support or integrate with GPU-as-a-Service (GPUaaS) for AI/ML workloads:

1) Red Hat OpenShift + NVIDIA GPU Operator

Best for: Enterprise self-service AI platforms

• Built-in developer self-service (web console + API)
• GPU scheduling via NVIDIA GPU Operator
• Supports GPU sharing, concurrency, and AI Enterprise integrations
• Works on-prem and in public clouds

GPU architecture & accelerators documentation:
docs.redhat.com
NVIDIA GPU Operator platform support:
docs.nvidia.com

✅ Strong option for internal “AI platform teams” delivering GPU-as-a-Service to developers.

2) VMware Tanzu Kubernetes Grid (TKG) + NVIDIA AI Enterprise

Best for: Enterprises running vSphere / private cloud

• Self-service cluster provisioning via vSphere with Tanzu
• vGPU support (A100, H100, etc.)
• Multi-cloud support (vSphere, AWS, Azure)
• GPU-backed Tanzu Kubernetes Clusters

GPU support announcement:
blogs.vmware.com
Technical GPU overview with Tanzu:
blogs.vmware.com

✅ Good if you want GPUaaS layered onto existing VMware infrastructure.

3) Rancher (SUSE) + RKE2/K3s + NVIDIA GPU Operator

Best for: Lightweight, multi-cluster self-service

• Centralized multi-cluster management
• Self-service provisioning across clouds and edge
• GPU passthrough + NVIDIA Operator support
• Integrates with Harvester HCI for GPU-backed VMs

Harvester GPU passthrough (Rancher ecosystem):
en.wikipedia.org)
NVIDIA GPU Operator docs:
docs.nvidia.com

✅ Flexible option for hybrid/edge GPUaaS.

4) Mirantis Container Cloud

Best for: Multi-cloud GPU-enabled Kubernetes

• Self-service Kubernetes cluster provisioning
• Multi-cloud operations (AWS, Azure, on-prem)
• Compatible with NVIDIA GPU Operator

Product overview:
en.wikipedia.org

✅ Good for organizations modernizing from Docker Enterprise or OpenStack.

Quick Recommendation

• Enterprise private cloud: OpenShift or Tanzu
• Hybrid / edge / cost-sensitive: Rancher + Harvester
• Multi-cloud platform engineering: Mirantis

If you'd like, tell me your environment (cloud, on-prem, edge, budget), and I’ll narrow this to 1–2 best-fit solutions.