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Preparing for a Run:ai Kubernetes installation

The following section provides IT with the information needed to prepare for a Run:ai installation.


Follow the prerequisites as explained in Self-Hosted installation over Kubernetes.

Software artifacts

You should receive a file: runai-gcr-secret.yaml from Run:ai Customer Support. The file provides access to the Run:ai Container registry.

SSH into a node with kubectl access to the cluster and Docker installed. Run the following to enable image download from the Run:ai Container Registry on Google cloud:

kubectl create namespace runai-backend
kubectl apply -f runai-reg-creds.yaml

You should receive a single file runai-air-gapped-<VERSION>.tar.gz from Run:ai customer support

SSH into a node with kubectl access to the cluster and Docker installed.

Run:ai assumes the existence of a Docker registry for images. Most likely installed within the organization. The installation requires the network address and port for the registry (referenced below as <REGISTRY_URL>).

To extract Run:ai files, replace <VERSION> in the command below and run:

tar xvf runai-air-gapped-<VERSION>.tar.gz
cd deploy

kubectl create namespace runai-backend

Upload images

Upload images to a local Docker Registry. Set the Docker Registry address in the form of NAME:PORT (do not add https):

export REGISTRY_URL=<Docker Registry address>

Run the following script (you must dockerd installed and at least 20GB of free disk space to run):

sudo -E ./

If Docker is configured to run as non-root then sudo is not required.

The script should create a file named custom-env.yaml which will be used by the control-plane installation.

Private Docker Registry (optional)

To access the organization's docker registry it is required to set the registry's credentials (imagePullSecret)

Create the secret named runai-reg-creds based on your existing credentials. For more information, see Pull an Image from a Private Registry.

Configure your environment

Domain Certificate

The Run:ai control plane requires a domain name (FQDN). You must supply a domain name as well as a trusted certificate for that domain.

  • When installing the first Run:ai cluster on the same Kubernetes cluster as the control plane, the Run:ai cluster URL will be the same as the control-plane URL.
  • When installing the Run:ai cluster on a separate Kubernetes cluster, follow the Run:ai domain name requirements.
  • If your network is air-gapped, you will need to provide the Run:ai control-plane and cluster with information about the local certificate authority.

You must provide the domain's private key and crt as a Kubernetes secret in the runai-backend namespace. Run:

kubectl create secret tls runai-backend-tls -n runai-backend \
    --cert /path/to/fullchain.pem --key /path/to/private.pem

Local Certificate Authority (air-gapped only)

In air-gapped environments, you must prepare the public key of your local certificate authority as described here. It will need to be installed in Kubernetes for the installation to succeed.

Mark Run:ai system workers (optional)

You can optionally set the Run:ai control plane to run on specific nodes. Kubernetes will attempt to schedule Run:ai pods to these nodes. If lacking resources, the Run:ai nodes will move to another, non-labeled node.

To set system worker nodes run:

kubectl label node <NODE-NAME>


Do not select the Kubernetes master as a runai-system node. This may cause Kubernetes to stop working (specifically if Kubernetes API Server is configured on 443 instead of the default 6443).

Additional permissions

As part of the installation, you will be required to install the Run:ai Control Plane and Cluster Helm Charts. The Helm Charts require Kubernetes administrator permissions. You can review the exact permissions provided by using the --dry-run on both helm charts.

Validate Prerequisites

Once you believe that the Run:ai prerequisites and preperations are met, we highly recommend installing and running the Run:ai pre-install diagnostics script. The tool:

  • Tests the below requirements as well as additional failure points related to Kubernetes, NVIDIA, storage, and networking.
  • Looks at additional components installed and analyze their relevance to a successful Run:ai installation.

To use the script download the latest version of the script and run:

chmod +x preinstall-diagnostics-<platform>
./preinstall-diagnostics-<platform> --domain <dns-entry>

If the script fails, or if the script succeeds but the Kubernetes system contains components other than Run:ai, locate the file runai-preinstall-diagnostics.txt in the current directory and send it to Run:ai technical support.

For more information on the script including additional command-line flags, see here.

Next steps

Continue with installing the Run:ai Control Plane.