> This page is for Self-Hosted, version v3.0 (default).
> For other versions, use one of these documentation indexes:
> - v3.0 (default): https://docs.nvidia.com/run-ai/self-hosted/v3.0/llms.txt
> - v2.26: https://docs.nvidia.com/run-ai/self-hosted/v2.26/llms.txt
> - v2.25: https://docs.nvidia.com/run-ai/self-hosted/v2.25/llms.txt
> - v2.24: https://docs.nvidia.com/run-ai/self-hosted/v2.24/llms.txt

> For clean Markdown of any page, append .md to the page URL.
> For a complete documentation index, see https://docs.nvidia.com/run-ai/llms.txt.
> For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://docs.nvidia.com/run-ai/_mcp/server.

# Configuration

Day 1 Configuration covers the infrastructure configuration that makes NVIDIA Run:ai production-ready for your environment, once installation is complete. Which configurations apply depends on your environment and workload needs - not every section here is required for every deployment.

## Cluster and Control Plane Settings

* **[Node Roles](/run-ai/self-hosted/documentation/installation-and-configuration/config/node-roles)** - Designates dedicated nodes for NVIDIA Run:ai system services, GPU workloads, and CPU-only workloads, so system services do not compete with GPU workloads for CPU cycles on expensive GPU machines.
* **[Advanced Control Plane Configuration](/run-ai/self-hosted/documentation/installation-and-configuration/config/advanced-control-plane-configuration)** - Advanced Helm chart values for customizing the control plane deployment beyond its defaults.
* **[Advanced Cluster Configuration](/run-ai/self-hosted/documentation/installation-and-configuration/config/advanced-cluster-configuration)** - Advanced Helm chart and `runaiconfig` values for customizing cluster behavior - scheduling policies, resource management, and system service tuning.
* **[Cluster Authentication](/run-ai/self-hosted/documentation/installation-and-configuration/config/cluster-authentication)** - Configures the Kubernetes API server to authenticate users via the NVIDIA Run:ai identity provider (OIDC), so users can securely submit workloads directly with `kubectl`.

## Networking

* **[Kubernetes Gateway API](/run-ai/self-hosted/documentation/installation-and-configuration/config/networking/kubernetes-gateway-api)** - An alternative to Ingress for routing external traffic, offering a more flexible and extensible routing model.
* **[Service Mesh](/run-ai/self-hosted/documentation/installation-and-configuration/config/networking/service-mesh)** - Configuration required to run NVIDIA Run:ai alongside a service mesh with sidecar injection.
* **[External Access to Containers](/run-ai/self-hosted/documentation/installation-and-configuration/config/networking/external-access-to-containers)** - Lets researchers connect to running containers remotely - for example, to run a Jupyter Notebook or connect an IDE for remote development.

## Security

* **[User Identity in Containers](/run-ai/self-hosted/documentation/installation-and-configuration/config/security/user-identity-in-containers)** - Propagates the correct user identity into containers instead of running as root by default, which matters for both functionality (like network file system access) and security.
* **[Security Best Practices](/run-ai/self-hosted/documentation/installation-and-configuration/config/security/security-best-practices)** - Actionable, platform-native and Kubernetes-mapped best practices for securely configuring and operating NVIDIA Run:ai.
* **[Secure Your Cluster](/run-ai/self-hosted/documentation/installation-and-configuration/config/security/secure-your-cluster)** - The specific permissions NVIDIA Run:ai requires, for administrators and security officers evaluating the platform.

## Storage

* **[Storage](/run-ai/self-hosted/documentation/installation-and-configuration/config/storage)** - Sets up shared storage accessible to every worker node, so distributed training and shared datasets can be read and written consistently across nodes.

## Third-Party Integrations

* **[Supported Integrations](/run-ai/self-hosted/documentation/installation-and-configuration/config/third-party-integrations/supported-integrations)** - Kubernetes components and external tools with built-in NVIDIA Run:ai support.
* **[Community Support Integrations](/run-ai/self-hosted/documentation/installation-and-configuration/config/third-party-integrations/community-support-integrations)** - Integrations commonly used alongside NVIDIA Run:ai but not supported out of the box.
* **[Karpenter](/run-ai/self-hosted/documentation/installation-and-configuration/config/third-party-integrations/karpenter)** - Guidance for running the Kubernetes cluster autoscaler Karpenter (optimizes for cost) alongside the NVIDIA Run:ai Scheduler (optimizes for fairness and utilization), since the two can conflict.