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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
Upload images to 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 have at least 20GB of free disk space to run):

kubectl create namespace runai-backend

sudo -E ./

(If docker is configured to run as non-root then sudo is not required).

Run:AI Administration CLI

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

Install the Run:AI Administrator Command-line Interface by following the steps here. Use the image under deploy/runai-admin-cli-<version>-linux-amd64.tar.gz

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).

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

Mark Run:AI System Workers

The Run:AI Backend 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>

Additional Permissions

As part of the installation you will be required to install the Backend 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 backend.

Last update: January 16, 2022