Installing Kubeflow
This guide describes how to use the Kubeflow Operator to deploy Kubeflow. As mentioned in the Operator introduction, the Operator also allows you to monitor and manage the Kubeflow installation beyond the initial installation.
Prerequisites
- Kubeflow Operator needs to be deployed on your cluster for rest of steps to work. Please follow the
Install the Kubeflow Operatorguide to install the Kubeflow Operator
Deployment Instructions
The Kubeflow Operator uses the KfDef as its custom resource. You can compose a KfDef configuration or pick a default KfDef from the Kubeflow manifests repo. Keep in mind choosing the release that will work with the Kubeflow Operator.
Prepare KfDef configuration
The metadata.name field must be set for the KfDef manifests whether it is downloaded from the Kubeflow manifests repo or is originally written. Following example shows how to prepare the KfDef manifests
# download a default KfDef configuration from remote repo
export KFDEF_URL=https://raw.githubusercontent.com/kubeflow/manifests/v1.1-branch/kfdef/kfctl_ibm.yaml
export KFDEF=$(echo "${KFDEF_URL}" | rev | cut -d/ -f1 | rev)
curl -L ${KFDEF_URL} > ${KFDEF}
# add metadata.name field
# Note: yq can be installed from https://github.com/mikefarah/yq
export KUBEFLOW_DEPLOYMENT_NAME=kubeflow
yq w ${KFDEF} 'metadata.name' ${KUBEFLOW_DEPLOYMENT_NAME} > ${KFDEF}.tmp && mv ${KFDEF}.tmp ${KFDEF}
Deploy the Kubeflow with the Kubeflow Operator
Kubeflow Operator is watching on any KfDef resource in the Kubernetes cluster. Depends on how the operator is installed, there are a couple of ways to start the Kubeflow deployment. You can always manually run with following commands
# create the namespace for Kubeflow deployment
KUBEFLOW_NAMESPACE=kubeflow
kubectl create ns ${KUBEFLOW_NAMESPACE}
# create the KfDef custom resource
kubectl create -f ${KFDEF} -n ${KUBEFLOW_NAMESPACE}
Note: in the example above, ${KFDEF} points to a local KfDef configuration file, however, it can also points to a remote URL containing a valid KfDef configuration.
Watch the deployment progress
The Kubeflow deployment is carried on by the operator, you can watch the progress with this command
kubectl logs deployment/kubeflow-operator -n ${OPERATOR_NAMESPACE} -f
Verify the Kubeflow deployment by monitoring the pods in the ${KUBEFLOW_NAMESPACE}
kubectl get pod -n ${KUBEFLOW_NAMESPACE}
NAME READY STATUS RESTARTS AGE
admission-webhook-bootstrap-stateful-set-0 1/1 Running 3 2m26s
admission-webhook-deployment-5bc5f97cfd-chjnm 1/1 Running 2 46s
application-controller-stateful-set-0 1/1 Running 0 2m30s
argo-ui-669bcd8bfc-5dk5c 1/1 Running 0 45s
cache-deployer-deployment-b75f5c5f6-42n6l 2/2 Running 1 45s
cache-server-85bccd99bd-tfrnr 2/2 Running 0 44s
centraldashboard-8849f64cf-l45zc 1/1 Running 0 44s
jupyter-web-app-deployment-6c568f4cbc-pd68m 1/1 Running 0 43s
kubeflow-pipelines-profile-controller-846cc56f44-cmbbf 1/1 Running 0 43s
metacontroller-0 1/1 Running 0 96s
metadata-writer-59d755696c-fh6px 2/2 Running 0 43s
minio-d45d44d4f-rmxft 1/1 Running 0 42s
ml-pipeline-6bc56cd86d-kn7zt 1/2 Running 0 42s
ml-pipeline-persistenceagent-6f99b56974-x2f52 2/2 Running 0 41s
ml-pipeline-scheduledworkflow-d596b8bd-qdz6m 2/2 Running 0 41s
ml-pipeline-ui-8695cc6b46-hr8p5 2/2 Running 0 40s
ml-pipeline-viewer-crd-5998ff7f56-5rn4s 2/2 Running 2 40s
ml-pipeline-visualizationserver-cbbb5b5b-w7rbd 2/2 Running 0 39s
mysql-76597cf5b5-jpsrx 1/2 Running 0 39s
notebook-controller-deployment-756587d86-fffg8 1/1 Running 0 38s
profiles-deployment-865b78d47f-pbgl4 2/2 Running 0 38s
workflow-controller-54dccb7dc4-hkg9s 1/1 Running 0 37s
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