Install the Run:AI Command-line Interface¶
The Run:AI Command-line Interface (CLI) is one of the ways for a Researcher to send deep learning workloads, acquire GPU-based containers, list jobs, etc.
The instructions below will guide you through the process of installing the CLI.
- Run:AI CLI runs on Mac and Linux.
When installing the command-line interface, its worth considering future upgrades:
- Install the CLI on a dedicated Jumpbox machine. Researches will connect to the Jumpbox from which they can submit Run:AI commands
- Install the CLI on a shared directory that is mounted on Researchers' machines.
Kubectl (Kubernetes command-line interface) installed and configured to access your cluster. Please refer to https://kubernetes.io/docs/tasks/tools/install-kubectl/.
- Helm. See https://helm.sh/docs/intro/install/ on how to install Helm. Run:AI works with Helm version 3 only (not helm 2).
- A Kubernetes configuration file obtained from the Kubernetes cluster installation.
When enabled, Researcher authentication requires additional setup when installing the CLI. To configure authentication see Setup Project-based Researcher Access Control. Use the modified Kubernetes configuration file described in the article.
- On the Researcher's root folder, create a directory .kube. Copy the Kubernetes configuration file into the directory. Each Researcher should have a separate copy of the configuration file. The Researcher should have write access to the configuration file as it stores user defaults.
- If you choose to locate the file at a different location than
~/.kube/config, you must create a shell variable to point to the configuration file as follows:
- Test the connection by running:
kubectl get nodes
Run:AI CLI Installation¶
- Download the latest release from the Run:AI releases page
- Unarchive the downloaded file
- Install by running:
- To verify the installation run:
runai list jobs
Troubleshooting the CLI Installation¶
Updating the Run:AI CLI¶
To update the CLI to the latest version run:
sudo runai update