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This page describes how to install the NVIDIA Run:ai control plane on a dedicated Kubernetes cluster, and one or more NVIDIA Run:ai clusters on separate Kubernetes clusters, over an internet-connected environment. To install the control plane and cluster together on one Kubernetes cluster instead, see Same-Cluster Installation.

The runai-installer CLI runs once per Kubernetes cluster with a dedicated configuration file:

  1. Install the control plane (mode: runai_control_plane_only) on the control plane cluster.
  2. Install the cluster component (mode: runai_cluster_only) on each NVIDIA Run:ai cluster, and register it with the control plane.

Before You Start

Complete Preparations before continuing, including the system requirements for your Kubernetes cluster, any required registry credentials, and downloading the runai-installer binary. The installer deploys and configures NVIDIA Run:ai itself; it does not provision this underlying infrastructure for you.

Install the Control Plane

Configuration Templates

The steps below build the minimum configuration for a multi-cluster installation on Kubernetes or OpenShift - one file for the control plane, one for each NVIDIA Run:ai cluster. Depending on your Kubernetes distribution, workload routing, networking setup, and the prerequisites and workload features you need, you may require additional configuration.

  • Once you understand the minimum configuration, see Configuration Templates - if your use case matches one, use it as your starting point instead of building the configuration from scratch.
  • See Prerequisites and Features to understand the components required, depending on the workload types you plan to enable.
  • See Configuration Reference for the full set of supported fields and descriptions, to build a configuration from scratch.

Create a cp-config.yaml file for the control plane cluster. Use the domains, TLS certificates, and networking values you prepared in Networking Setup when completing the configuration below.

Expand the section for your platform:

For a control plane installation on Kubernetes, configure:

  1. Define the installation:

    • install.mode - Set to runai_control_plane_only to install the control plane only.
    • install.connectivity - Set to connected, for an installation with outbound internet access.
    install:
    mode: runai_control_plane_only
    connectivity: connected
  2. Configure the registry:

    • registry.type - Set to ngc.
    • registry.tokenPath - For NVIDIA Run:ai Support-Entitled Release installations, provide the path to your NGC Personal Key. Open Source installations do not require registry credentials. See Registry Credentials.
    registry:
    type: ngc
    tokenPath: /path/to/ngc-token # Support-Entitled Release only
  3. Define the control plane:

    • controlPlane.domain - The FQDN for the NVIDIA Run:ai UI and API. See Domains and TLS Certificates.
    • controlPlane.tls - The certificate and private key for the control plane FQDN, as certPath and keyPath. See Domains and TLS Certificates.
    • controlPlane.version - The control plane version to install. Omit it to install the latest supported version.
    • controlPlane.customHelmValues - Merges Helm values into the control plane chart, for settings not otherwise exposed by the installer. See Advanced Control Plane Configurations for the full set of keys.
      • supportEntitled - For NVIDIA Run:ai Support-Entitled Release, must be set to true.
      • telemetryService.enabled - For NVIDIA Run:ai Support-Entitled Release, must be set to true to enable telemetry.
      • telemetryService.telemetryAuth - Optional, Support-Entitled Release only. Associates NVIDIA Run:ai’s telemetry with your NCA ID - by default, telemetry is not associated with your organization. See Registry Credentials for how to generate the NGC Service API Key. Provide it one of two ways:
        • token: <SERVICE_API_KEY> - Sets the Service API Key directly; the chart creates and manages the Kubernetes secret for you. Stored in plaintext in the configuration file, so protect it accordingly, or use existingSecret instead.
        • existingSecret: <SECRET_NAME> / secretKey: <KEY_NAME> - References a secret you create yourself beforehand - the installer does not create or manage it.
      • Third-party services - Add the image pull secret, the external PostgreSQL connection, and the hardened images and settings of the control plane third-party services. See Gov-Ready Third-Party Services for the values. Gov-ready
      • global.fipsMode - Enables FIPS mode, so that the NVIDIA Run:ai services use only FIPS-validated cryptography. Set to only. Gov-ready
    controlPlane:
    enabled: true
    domain: <DOMAIN>
    tls:
    certPath: /path/to/cp-cert.pem
    keyPath: /path/to/cp-key.pem
    version: "" # Omit to install the latest supported version
    customHelmValues:
    supportEntitled: true # Support-Entitled Release only
    telemetryService: # Support-Entitled Release only
    enabled: true
    telemetryAuth: # Optional
    token: <SERVICE_API_KEY>
    # Gov-ready: add the image pull secret, external PostgreSQL, and hardened control plane values, see Gov-Ready Third-Party Services
    global:
    fipsMode: only # Gov-ready
  4. Configure external access to the control plane:

    • externalConnection - Configures how traffic reaches the NVIDIA Run:ai control plane UI/API from outside the cluster, through a Kubernetes Ingress Controller or Gateway API implementation already running on your cluster. See Networking Setup.
    externalConnection:
    type: ingress
    ingress:
    className: <YOUR_INGRESS_CLASS>

The following example combines these settings to install the NVIDIA Run:ai control plane:

install:
mode: runai_control_plane_only
connectivity: connected
registry:
type: ngc
tokenPath: /path/to/ngc-token # Support-Entitled Release only
controlPlane:
enabled: true
domain: <DOMAIN>
tls:
certPath: /path/to/cp-cert.pem
keyPath: /path/to/cp-key.pem
version: ""
customHelmValues:
supportEntitled: true # Support-Entitled Release only
# Gov-ready: add the image pull secret, external PostgreSQL, and hardened control plane values, see Gov-Ready Third-Party Services
global:
fipsMode: only # Gov-ready
externalConnection:
type: ingress
ingress:
className: <YOUR_INGRESS_CLASS>

For a control plane installation on OpenShift, configure:

  1. Define the installation:

    • install.mode - Set to runai_control_plane_only to install the control plane only.
    • install.connectivity - Set to connected, for an installation with outbound internet access.
    • install.kubernetesDistribution - Set to openshift.
    install:
    mode: runai_control_plane_only
    connectivity: connected
    kubernetesDistribution: openshift
  2. Configure the registry:

    • registry.type - Set to ngc.
    • registry.tokenPath - For NVIDIA Run:ai Support-Entitled Release installations, provide the path to your NGC Personal Key. Open Source installations do not require registry credentials. See Registry Credentials.
    registry:
    type: ngc
    tokenPath: /path/to/ngc-token # Support-Entitled Release only
  3. Define the control plane:

    • controlPlane.domain - The FQDN for the NVIDIA Run:ai UI and API. See Domains and TLS Certificates.
    • controlPlane.version - The control plane version to install. Omit it to install the latest supported version.
    • controlPlane.customHelmValues - Merges Helm values into the control plane chart, for settings not otherwise exposed by the installer. See Advanced Control Plane Configurations for the full set of keys.
      • supportEntitled - For NVIDIA Run:ai Support-Entitled Release, must be set to true.
      • telemetryService.enabled - For NVIDIA Run:ai Support-Entitled Release, must be set to true to enable telemetry.
      • telemetryService.telemetryAuth - Optional, Support-Entitled Release only. Associates NVIDIA Run:ai’s telemetry with your NCA ID - by default, telemetry is not associated with your organization. See Registry Credentials for how to generate the NGC Service API Key. Provide it one of two ways:
        • token: <SERVICE_API_KEY> - Sets the Service API Key directly; the chart creates and manages the Kubernetes secret for you. Stored in plaintext in the configuration file, so protect it accordingly, or use existingSecret instead.
        • existingSecret: <SECRET_NAME> / secretKey: <KEY_NAME> - References a secret you create yourself beforehand - the installer does not create or manage it.
      • Third-party services - Add the image pull secret, the external PostgreSQL connection, and the hardened images and settings of the control plane third-party services. See Gov-Ready Third-Party Services for the values. Gov-ready
      • global.fipsMode - Enables FIPS mode, so that the NVIDIA Run:ai services use only FIPS-validated cryptography. Set to only. Gov-ready
    controlPlane:
    enabled: true
    domain: <DOMAIN>
    version: "" # Omit to install the latest supported version
    customHelmValues:
    supportEntitled: true # Support-Entitled Release only
    telemetryService: # Support-Entitled Release only
    enabled: true
    telemetryAuth: # Optional
    token: <SERVICE_API_KEY>
    # Gov-ready: add the image pull secret, external PostgreSQL, and hardened control plane values, see Gov-Ready Third-Party Services
    global:
    fipsMode: only # Gov-ready

The following example combines these settings to install the NVIDIA Run:ai control plane on OpenShift:

install:
mode: runai_control_plane_only
connectivity: connected
kubernetesDistribution: openshift
registry:
type: ngc
tokenPath: /path/to/ngc-token # Support-Entitled Release only
controlPlane:
enabled: true
domain: <DOMAIN>
version: ""
customHelmValues:
supportEntitled: true # Support-Entitled Release only
# Gov-ready: add the image pull secret, external PostgreSQL, and hardened control plane values, see Gov-Ready Third-Party Services
global:
fipsMode: only # Gov-ready

Run the Installer

  • Validate first - Before applying any changes, check your configuration against the control plane cluster:

    ./runai-installer install \
    --config cp-config.yaml \
    --kubeconfig /path/to/cp-kubeconfig \
    --preflight-only
  • Preview the plan - Go further and preview the full installation plan without applying it:

    ./runai-installer install \
    --config cp-config.yaml \
    --kubeconfig /path/to/cp-kubeconfig \
    --dry-run
  • Run the installer - Once you are ready, run it against the control plane cluster:

    ./runai-installer install \
    --config cp-config.yaml \
    --kubeconfig /path/to/cp-kubeconfig \
    --logs-dir ./logs

When the installation completes, verify that the control plane is reachable at its FQDN (for example, https://runai.mycorp.local) before continuing.

Retrieve Control Plane Credentials

Retrieve the generated control plane administrator username and password - use these when installing NVIDIA Run:ai clusters below:

kubectl get configmap runai-backend-tenants-manager -n runai-backend -o jsonpath='{.data.ADMIN_USERNAME}'
kubectl get secret runai-backend-gen-tenants-manager -n runai-backend -o jsonpath='{.data.ADMIN_PASSWORD}' | base64 -d

Install Each NVIDIA Run:ai Cluster

Create a cluster-config.yaml file for each NVIDIA Run:ai cluster. The control plane must already be installed and reachable at its FQDN. Use the domains, TLS certificates, and networking values you prepared in Networking Setup when completing the configuration below.

Expand the section for your platform:

For a cluster installation on Kubernetes, configure:

  1. Define the installation:

    • install.mode - Set to runai_cluster_only to install the cluster component only.
    • install.connectivity - Set to connected, for an installation with outbound internet access.
    install:
    mode: runai_cluster_only
    connectivity: connected
  2. Configure the registry:

    • registry.type - Set to ngc.
    • registry.tokenPath - For NVIDIA Run:ai Support-Entitled Release installations, provide the path to your NGC Personal Key. Open Source installations do not require registry credentials. See Registry Credentials.
    registry:
    type: ngc
    tokenPath: /path/to/ngc-token # Support-Entitled Release only
  3. Define the cluster:

    • cluster.name - The name of the NVIDIA Run:ai cluster as it appears in the control plane.
    • cluster.domain - The FQDN for this cluster. See Domains and TLS Certificates. Required when the cluster component is installed on a different Kubernetes cluster than the control plane. The installer also uses this domain to reach the control plane when registering the cluster.
    • cluster.controlPlaneUrl - The control plane’s FQDN, reachable over HTTPS from this cluster.
    • cluster.controlPlaneCredentials - Identifies this cluster to the control plane. Use the control plane administrator username and password generated during control plane installation - the installer uses these to register the cluster and fetch its bootstrap token automatically, in the same run. See Retrieve Control Plane Credentials.
    • cluster.workloadRouting - host (the default) or path. This determines which certificate you need for cluster.tls below.
    • cluster.tls - A certificate and private key for the cluster domain, as certPath and keyPath. See Domains and TLS Certificates for which certificate you need.
    • cluster.version - The cluster version to install. Omit it to install the latest supported version.
    • cluster.customHelmValues - Merges Helm values into the cluster chart, for settings not otherwise exposed by the installer. See Advanced Cluster Configurations for the full set of keys.
      • Third-party services - Add the image pull secret and the hardened images of the cluster third-party services. See Gov-Ready Third-Party Services for the values. Gov-ready
      • global.fipsMode - Enables FIPS mode, so that the NVIDIA Run:ai services use only FIPS-validated cryptography. Set to only. Gov-ready
    cluster:
    enabled: true
    name: <CLUSTER_NAME>
    domain: <CLUSTER_DOMAIN>
    workloadRouting: host # Default; determines the certificate cluster.tls needs
    controlPlaneUrl: https://<DOMAIN>
    controlPlaneCredentials:
    username: <ADMIN_EMAIL>
    passwordPath: /path/to/cp-password
    tls:
    certPath: /path/to/cluster-a-cert.pem
    keyPath: /path/to/cluster-a-key.pem
    version: "" # Omit to install the latest supported version
    customHelmValues:
    # Gov-ready: add the image pull secret and hardened cluster values, see Gov-Ready Third-Party Services
    global:
    fipsMode: only # Gov-ready
  4. Enable the prerequisites:

    • prerequisites.gpuOperator - Required for every installation. See Prerequisites and Features for more details.
      • mode - Set to install.
      • version - Omit to install the latest version, or see Support Matrix for the supported range if you want to set it explicitly. GPU fractions (memory fractions, dynamic memory fractions, or compute modes) require 26.7.1 or later, installed automatically when omitted.
      • customHelmValues - Merges Helm values into the GPU Operator’s own Helm chart. Set driver.version to r615 or later if you plan to use GPU fractions, since GPU Operator 26.7.1 does not default to this driver version. Set cdi.nriPluginEnabled to false, since GPU memory fractions do not function while the NRI plugin is enabled. See GPU Memory Fractions.
      • GPU Operator values - Add the Helm values required for a Gov-ready GPU Operator to customHelmValues. See Install the Gov-Ready GPU Operator for the values. Gov-ready
    • prerequisites.prometheus - Required for every installation. See Prerequisites and Features for more details.
      • mode - Set to install.
      • version - Omit to install the latest version, or see Support Matrix for the supported range.
      • customHelmValues - Merges Helm values into Prometheus’s own Helm chart.
    prerequisites:
    gpuOperator:
    mode: install
    version: ""
    customHelmValues: {} # Gov-ready: add the GPU Operator Helm values
    prometheus:
    mode: install
    version: ""
    customHelmValues: {}

    Features

    The minimum configuration does not include features such as Knative, Kubeflow, MPI Operator, LWS, NIM Operator, Dynamo, or Grove. These are skipped by default.

    If your workloads require any of these features, add the corresponding features configuration. See Prerequisites and Features.

    Some features require additional networking configuration. For example, externally exposed standard inference with Knative requires an additional inference wildcard FQDN and TLS certificate. See Networking Setup.

  5. Configure external access to the cluster:

    • externalConnection - Configures how traffic reaches the NVIDIA Run:ai cluster endpoint from outside the cluster, through a Kubernetes Ingress Controller or Gateway API implementation already running on your cluster. This is separate from cluster.workloadRouting, which controls how the workloads you submit are exposed. See Networking Setup.
    externalConnection:
    type: ingress
    ingress:
    className: <YOUR_INGRESS_CLASS>

The following example combines these settings to install the NVIDIA Run:ai cluster component on a separate Kubernetes cluster, and has the installer register it with the control plane using the control plane administrator username and password:

install:
mode: runai_cluster_only
connectivity: connected
registry:
type: ngc
tokenPath: /path/to/ngc-token # Support-Entitled Release only
cluster:
enabled: true
name: <CLUSTER_NAME>
domain: <CLUSTER_DOMAIN>
workloadRouting: host
controlPlaneUrl: https://<DOMAIN>
controlPlaneCredentials:
username: <ADMIN_EMAIL>
passwordPath: /path/to/cp-password
tls:
certPath: /path/to/cluster-a-cert.pem
keyPath: /path/to/cluster-a-key.pem
version: ""
customHelmValues:
# Gov-ready: add the image pull secret and hardened cluster values, see Gov-Ready Third-Party Services
global:
fipsMode: only # Gov-ready
prerequisites:
gpuOperator:
mode: install
version: ""
customHelmValues: {} # Gov-ready: add the GPU Operator Helm values
prometheus:
mode: install
version: ""
customHelmValues: {}
externalConnection:
type: ingress
ingress:
className: <YOUR_INGRESS_CLASS>

For a cluster installation on OpenShift, configure:

  1. Define the installation:

    • install.mode - Set to runai_cluster_only to install the cluster component only.
    • install.connectivity - Set to connected, for an installation with outbound internet access.
    • install.kubernetesDistribution - Set to openshift.
    install:
    mode: runai_cluster_only
    connectivity: connected
    kubernetesDistribution: openshift
  2. Configure the registry:

    • registry.type - Set to ngc.
    • registry.tokenPath - For NVIDIA Run:ai Support-Entitled Release installations, provide the path to your NGC Personal Key. Open Source installations do not require registry credentials. See Registry Credentials.
    registry:
    type: ngc
    tokenPath: /path/to/ngc-token # Support-Entitled Release only
  3. Define the cluster:

    • cluster.name - The name of the NVIDIA Run:ai cluster as it appears in the control plane.
    • cluster.domain - The FQDN for this cluster. See Domains and TLS Certificates. Required when the cluster component is installed on a different OpenShift cluster than the control plane. The installer also uses this domain to reach the control plane when registering the cluster.
    • cluster.controlPlaneUrl - The control plane’s FQDN, reachable over HTTPS from this cluster.
    • cluster.controlPlaneCredentials - Identifies this cluster to the control plane. Use the control plane administrator username and password generated during control plane installation - the installer uses these to register the cluster and fetch its bootstrap token automatically, in the same run. See Retrieve Control Plane Credentials.
    • cluster.version - The cluster version to install. Omit it to install the latest supported version.
    • cluster.customHelmValues - Merges Helm values into the cluster chart, for settings not otherwise exposed by the installer. See Advanced Cluster Configurations for the full set of keys.
      • Third-party services - Add the image pull secret and the hardened images of the cluster third-party services. See Gov-Ready Third-Party Services for the values. Gov-ready
      • global.fipsMode - Enables FIPS mode, so that the NVIDIA Run:ai services use only FIPS-validated cryptography. Set to only. Gov-ready
    cluster:
    enabled: true
    name: <CLUSTER_NAME>
    domain: <CLUSTER_DOMAIN>
    controlPlaneUrl: https://<DOMAIN>
    controlPlaneCredentials:
    username: <ADMIN_EMAIL>
    passwordPath: /path/to/cp-password
    version: "" # Omit to install the latest supported version
    customHelmValues:
    # Gov-ready: add the image pull secret and hardened cluster values, see Gov-Ready Third-Party Services
    global:
    fipsMode: only # Gov-ready
  4. Enable the prerequisites:

    • prerequisites.gpuOperator - Required for every installation. See Prerequisites and Features for more details.
      • mode - Set to install. The installer installs the GPU Operator through OperatorHub (OLM).
      • version - Omit to install the latest version, or see Support Matrix for the supported range if you want to set it explicitly. GPU fractions (memory fractions, dynamic memory fractions, or compute modes) require 26.7.1 or later, installed automatically when omitted.
      • openshift.customResource - Merges values into the GPU Operator’s ClusterPolicy. customHelmValues is not supported on OpenShift. Set driver.version to r615 or later if you plan to use GPU fractions, since GPU Operator 26.7.1 does not default to this driver version. See GPU Memory Fractions and Per-Component OpenShift Fields.
      • GPU Operator values - Add the values required for a Gov-ready GPU Operator to openshift.customResource. See Install the Gov-Ready GPU Operator for the values. Gov-ready
    • prerequisites.prometheus - See Prerequisites and Features for more details.
      • mode - Set to skip, to use the cluster’s built-in monitoring stack. install is rejected on OpenShift.
    prerequisites:
    gpuOperator:
    mode: install
    version: ""
    openshift:
    customResource: # Gov-ready: add the GPU Operator values
    driver:
    version: <DRIVER_VERSION>
    prometheus:
    mode: skip

    Features

    The minimum configuration does not include features such as Knative, Kubeflow, MPI Operator, LWS, NIM Operator, Dynamo, or Grove. These are skipped by default.

    If your workloads require any of these features, add the corresponding features configuration. See Prerequisites and Features.

    Some features need OpenShift-specific configuration. For example, Knative, required for standard inference, installs through the OpenShift Serverless operator and requires cluster.inference.wildcardDomain, but no wildcard TLS certificate. Features that install through OperatorHub, such as Knative and LWS, are customized through openshift.customResource rather than customHelmValues. See Per-Component OpenShift Fields.

The following example combines these settings to install the NVIDIA Run:ai cluster component on a separate OpenShift cluster, and has the installer register it with the control plane using the control plane administrator username and password:

install:
mode: runai_cluster_only
connectivity: connected
kubernetesDistribution: openshift
registry:
type: ngc
tokenPath: /path/to/ngc-token # Support-Entitled Release only
cluster:
enabled: true
name: <CLUSTER_NAME>
domain: <CLUSTER_DOMAIN>
controlPlaneUrl: https://<DOMAIN>
controlPlaneCredentials:
username: <ADMIN_EMAIL>
passwordPath: /path/to/cp-password
version: ""
customHelmValues:
# Gov-ready: add the image pull secret and hardened cluster values, see Gov-Ready Third-Party Services
global:
fipsMode: only # Gov-ready
prerequisites:
gpuOperator:
mode: install
version: ""
openshift:
customResource: # Gov-ready: add the GPU Operator values
driver:
version: <DRIVER_VERSION>
prometheus:
mode: skip

Run the Installer

  • Validate first - Before applying any changes, check your configuration against the target cluster:

    ./runai-installer install \
    --config cluster-config.yaml \
    --kubeconfig /path/to/cluster-a-kubeconfig \
    --preflight-only
  • Preview the plan - Go further and preview the full installation plan without applying it:

    ./runai-installer install \
    --config cluster-config.yaml \
    --kubeconfig /path/to/cluster-a-kubeconfig \
    --dry-run
  • Run the installer - Once you are ready, run it against the target cluster:

    ./runai-installer install \
    --config cluster-config.yaml \
    --kubeconfig /path/to/cluster-a-kubeconfig \
    --logs-dir ./logs

Repeat this step for each additional NVIDIA Run:ai cluster with its own configuration file - each cluster requires a unique cluster.name and its own cluster.domain.

Verify the Installation

After each installer run completes successfully, verify that the NVIDIA Run:ai pods are running:

# On the control plane cluster
kubectl get pods -n runai-backend
# On each NVIDIA Run:ai cluster
kubectl get pods -n runai

All pods should reach Running or Completed status.

Connect to NVIDIA Run:ai User Interface

Note

After installation, it may take a few minutes for the UI to become accessible (up to 15 minutes). Accessing it too early may result in a “server cannot be reached” error.

  1. Open your browser and go to the control plane domain (for example, https://runai.mycorp.local).
  2. Log in using the control plane administrator username and password retrieved earlier. It is recommended to change the password after the first login.
  3. Verify that each installed cluster appears under its configured cluster.name with a Connected status. If a cluster does not show as Connected, see Troubleshooting scenarios.

Command Reference and Troubleshooting

See Command Reference and Troubleshooting for installer flags and common troubleshooting scenarios.