Control Plane Installation | NVIDIA Run:ai Documentation

This page describes how to install the NVIDIA Run:ai control plane on your Kubernetes cluster using Helm. The control plane provides the central management layer for NVIDIA Run:ai multi-tenant, handling tenant management, resource and access management, as well as workload submission and monitoring across tenant clusters.

This procedure includes:

Configuring key settings such as domain name, ingress, and administrator credentials
Deploying the control plane into the runai-backend namespace

By completing this process, the NVIDIA Run:ai control plane will be running in your cluster and accessible via the configured domain, ready to onboard tenants.

Before You Start

Before installing the NVIDIA Run:ai control plane, complete Preparations.

Permissions

As part of the installation, you will be required to install the NVIDIA Run:ai control plane Helm chart. The Helm chart requires Kubernetes administrator permissions. You can review the exact objects that are created by the chart using the --dry-run flag.

Installation

Note

To customize the installation based on your environment, see Advanced Control Plane Configurations.
PostgreSQL and Keycloakx are installed with default usernames and passwords. To change the default credentials, see Advanced Control Plane Configurations.

Create a values.yaml file using the appropriate example below based on your metrics backend:

YAML with Grafana Labs

YAML with Mimir

global:
  domain: <RUNAI_DOMAIN> # example: "runai.hostorg.com"
  multiTenancy: 
    enabled: true
  management:
    user: <ADMIN-USER>
    password: <ADMIN-PASSWORD>
metricsService:
  config:
   datasourceUrl: <METRIC_STORE_READ_URL> # example: https://prometheus-prod-13-prod-us-east-0.grafana.net/api/prom
tenantsManager:
  config:
    defaultMetricStore:
      read:
        auth:
          basic:
            password: <METRIC_STORE_READ_PASSWORD>
            username: "1434499"
        url: <METRIC_STORE_READ_URL> # example: https://prometheus-prod-13-prod-us-east-0.grafana.net/api/prom
      useXscopeHeader: true
      write:
        auth:
          basic:
            password: <METRIC_STORE_WRITE_PASSWORD>
            username: "1434499"
        url: <METRIC_STORE_WRITE_URL> # example: https://prometheus-prod-56-prod-us-east-2.grafana.net/api/prom
thanos:
  enabled: false
authorization:
  config:
    isCSPEnv: true

Run the following commands to install the NVIDIA Run:ai control plane using your configured values.yaml file. Use the commands for the release type you are installing.

Open Source

Support-Entitled

Open Source

helm repo add runai https://helm.ngc.nvidia.com/nvidia/runai-oss --force-update
helm repo update
helm upgrade -i runai-backend -n runai-backend runai/control-plane \
    -f /path/to/your/values.yaml

Note

To install a specific version, add --version <VERSION> to the install command. You can find all available versions by using the helm search repo runai/control-plane --versions command.
Use the --dry-run flag to gain an understanding of what is being installed before the actual installation.

Next Steps

Set up API Access to authenticate your API requests, then onboard your first tenant. See Create a Tenant and Cluster. Before installing a tenant’s cluster, make sure you have completed the required setup in Prerequisites and Features on that tenant’s own Kubernetes cluster.