Kubernetes-based GPU orchestration platform fully deployed on-premises, including the control plane and clusters, enabling dynamic AI workload scheduling and resource optimization within your infrastructure.
NVIDIA Run:ai
NVIDIA Run:ai accelerates AI and machine learning operations by addressing key infrastructure challenges through dynamic resource allocation, comprehensive AI life-cycle support, and strategic resource management.
By pooling resources across environments and utilizing advanced orchestration, NVIDIA Run:ai significantly enhances GPU efficiency and workload capacity. With support for public clouds, private clouds, hybrid environments, or on-premises data centers, NVIDIA Run:ai provides unparalleled flexibility and adaptability.
Self-hosted
This collection provides NVIDIA Run:ai fully deployed within your own infrastructure.
The self-hosted deployment includes both the control plane and cluster components required to enable dynamic AI workload scheduling and GPU resource optimization on-premises or within private cloud environments.
The self-hosted option is designed for organizations that cannot use a SaaS solution due to regulatory, security, or data governance requirements.
NVIDIA Run:ai self-hosted variants
- Connected – The organization can freely download from the internet.
- Air-gapped – The organization has no connection to the internet. The air-gapped installation package is provided as a Resource in NVIDIA NGC.
Using NVIDIA Run:ai
NVIDIA Run:ai is an enterprise‑grade AI workload and GPU orchestration platform for customers running training, inference, or development workloads on Kubernetes clusters, typically at enterprise scale (16 GPUs or more).
NVIDIA Run:ai provides advanced scheduling, workload optimization, RBAC, governance, and auditing capabilities, enabling IT and data science teams to maximize GPU utilization and operational efficiency.
It is designed for mature enterprise environments with Kubernetes expertise and is not recommended for small, single‑node, or POC‑scale deployments, as setup and integration require infrastructure planning.
Getting Started
Start with the NVIDIA Run:ai overview to understand the platform architecture, system components, and deployment models.
Then proceed to the Installation section for your selected deployment model, which provides step-by-step instructions for connected and air-gapped environments.
Documentation
Find all the product guides, quickstarts, tutorials, configuration references, and API documentation in the NVIDIA Run:ai Documentation Portal.
Enterprise Support
Get access to knowledge-base articles and support cases or submit a ticket.
License: https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-software-license-agreement
