Understand the Kubernetes Cluster Access provided to Run:ai¶

Run:ai has the ability to work under restrictive Kubernetes environments. Namely:

• Kubernetes PodSecurityPolicy
• OpenShift

You can enable these restricted environment by setting the pspEnabled or openshift configuration flags in the Helm values file before installing the Run:ai cluster.

Other configuration flags are controlling specific behavioral aspects of Run:ai. Specifically, those which require additional permissions. Such as automatic namespace/project creation, secret propagation, and more.

The purpose of this document is to provide security officers with the ability to review what cluster-wide access Run:ai requires, and verify that it is in line with organizational policy, before installing the Run:ai cluster.

Review Cluster Access Roles¶

Run:

helm repo add runai https://run-ai-charts.storage.googleapis.com
helm repo update
helm install runai-cluster runai/runai-cluster -n runai -f runai-<cluster-name>.yaml \
        --dry-run > cluster-all.yaml

The file cluster-all.yaml can be then be reviewed. You can use the internal filenames (provided in comments within the file) to gain more understanding according to the table below:

Folder	File	Purpose
clusterroles	base.yaml	Mandatory Kubernetes Cluster Roles and Cluster Role Bindings
clusterroles	project-controller-ns-creation.yaml	Automatic Project Creation and Maintenance. Provides Run:ai with the ability to create Kubernetes namespaces when the Run:ai administrator creates new Projects. Can be turned on/off via flag
clusterroles	project-controller-rb-creation.yaml	Automatically assign Users to Projects. Can be turned on/off via flag
clusterroles	project-controller-cluster-wide-secrets.yaml	Allow the propagation of Secrets. See Secrets in Jobs. Can be turned on/off via flag
clusterroles	project-controller-limit-range.yaml	Disables the usage of the Kubernetes Limit Range feature. Can be turned on/off via flag
ocp	scc.yaml	OpenShift-specific Security Contexts
priorityclasses	4 files	Folder contains a list of Priority Classes used by Run:ai
psp	baseline-psp.yaml	A subset of the Kubernetes baseline PodSecurityPolicy (here)
psp	nvidia-psp.yaml	Required for NVIDIA components
psp	runai-container-toolkit-psp.yaml	Required for Run:ai GPU Fractions technology. Can be turned on/off via flag.
psp	runai-user-psp.yaml	Required for User Workloads. Extends the Kubernetes baseline PodSecurityPolicy for Run:ai GPU Fractions technology. Can be turned on/off via flag.
psp	privileged.yaml	priviliged Kubernetes PodSecurityPolicy. Used only for installing Node Feature Discovery and NVIDIA GPU Feature Discovery third parties. Can be turned on/off via flag