Skip to content



See Prerequisites section above.

Prepare Installation Artifacts

Run:ai Software Files

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-gcr-secret.yaml

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

tar xvf runai-<version>.tar.gz
cd deploy

kubectl create namespace runai-backend

Run:ai Administration CLI

Install the Run:ai Administrator Command-line Interface by following the steps here.

Use the Run:ai Administrator Command-line Interface located in the deploy folder. To allow running the binary, run:

chmod +x runai-adm

Install Helm

If helm v3 does not yet exist on the machine, install it now:

See on how to install Helm. Run:ai works with Helm version 3 only (not helm 2).

The Helm installation image is under the deploy directory. Run:

tar xvf helm-<version>-linux-amd64.tar.gz
sudo mv linux-amd64/helm /usr/local/bin/

Mark Run:ai System Workers

In previous versions, you set nodes that were dedicated to Run:ai software:

  • Setting the nodes was mandatory.
  • Run:ai was confined to these nodes. If the selected nodes failed or lacked resources, Run:ai would stop working.

In version 2.9,

  • There is no need to set nodes for Run:ai.
  • You can optionally set the Run:ai control plane to run on specific nodes.
  • Run:ai is no longer confined to these notes. Instead, 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>

If you want to preserve the previous functionality, please contact Run:ai customer support.


The new functionality is limited to the Run:ai control plane and has not yet been implemented in the Run:ai cluster.

The Run:ai control plane should be installed on a set of dedicated Run:ai system worker nodes rather than GPU worker nodes. To set system worker nodes run:

kubectl label node <NODE-NAME>

To avoid single-point-of-failure issues, we recommend assigning more than one node in production environments.


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.

Next Steps

Continue with installing the Run:ai Control Plane.

Last update: 2023-03-26
Created: 2023-03-26