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(Optional) Customize Cluster Installation

The Run:ai cluster creation wizard requires the download of a Helm values file runai-<cluster-name>.yaml. The file may be edited to customize the cluster installation.

Configuration Flags

Key Default Description
runai-operator.config.project-controller.createNamespaces true Set to falseif unwilling to provide Run:ai the ability to create namespaces. When set to false, will requires an additional manual step when creating new Run:ai Projects
runai-operator.config.project-controller.clusterWideSecret true Set to false when using PodSecurityPolicy or OpenShift
runai-operator.config.mps-server.enabled false Set to true to allow the use of NVIDIA MPS. MPS is useful with Inference workloads
runai-operator.config.global.runtime docker Defines the container runtime of the cluster (supports docker and containerd). Set to containerd when using Tanzu
runai-operator.config.global.nvidiaDcgmExporter.namespace gpu-operator The namespace where dcgm-exporter (or gpu-operator) was installed
runai-operator.config.global.nvidiaDcgmExporter.installedFromGpuOperator true Indicated whether the dcgm-exporter was installed via gpu-operator or not

Understanding Custom Access Roles

To review the access roles created by the Run:ai Cluster installation, see Understanding Access Roles.

Manual Creation of Namespaces

Run:ai Projects are implemented as Kubernetes namespaces. By default, the administrator creates a new Project via the Administration user interface which then triggers the creation of a Kubernetes namespace named runai-<PROJECT-NAME>. There are a couple of use cases that customers will want to disable this feature:

  • Some organizations prefer to use their internal naming convention for Kubernetes namespaces, rather than Run:ai's default runai-<PROJECT-NAME> convention.
  • Some organizations will not allow Run:ai to automatically create Kubernetes namespaces.

Follow these steps to achieve this:

  1. Disable the namespace creation functionality. See the runai-operator.config.project-controller.createNamespaces flag above.
  2. Create a Project using the Run:ai User Interface.
  3. Create the namespace if needed by running: kubectl create ns <NAMESPACE>. The suggested Run:ai default is runai-<PROJECT-NAME>.
  4. Label the namespace to connect it to the Run:ai Project by running kubectl label ns <NAMESPACE> runai/queue=<PROJECT_NAME>, where <PROJECT_NAME> is the name of the project you have created in the Run:ai user interface above and <NAMESPACE> is the name you chose for your namespace.
Last update: 2023-08-07
Created: 2021-03-31