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KFServing on OpenShift

OpenShift Container Platform is built on top of Kubernetes, and offers a consistent hybrid cloud foundation for building and scaling containerized applications. To install standalone KFServing on OpenShift, the easiest way is to use the quick_install.sh script provided in this repository. This assumes you do not already have Istio and Knative running on your cluster.

Note: These instructions were tested on OpenShift 4.5.15, with KFServing 0.4.1, Istio 1.6.2, and Knative 0.15.0 which are in the quick install script. Additionally, we have tested it with Kubeflow 1.2 recommended versions for Istio and Knative, i.e. Istio 1.3.1 and Knative 0.14.3.

Clone repository

git clone https://github.com/kubeflow/kfserving

Add Security Context Constraint (SCC)

Run the following to enable containers to run with UID 0 for Istio’s service accounts, as recommended on Istio's installation instructions for OpenShift

oc adm policy add-scc-to-group anyuid system:serviceaccounts:istio-system

Run install script

From the root of the kfserving directory, execute the following:

./hack/quick_install.sh

This script will install Istio, Knative, Cert Manager, and then finally KFServing.

Verify KFServing installation

Check that the KFserving controller is running:

oc get po -n kfserving-system

NAME                             READY   STATUS    RESTARTS   AGE
kfserving-controller-manager-0   2/2     Running   0          2m28s

Expose OpenShift route

After installation is verified, expose an OpenShift route for the ingress gateway.

oc -n istio-system expose svc/istio-ingressgateway --port=http2

Test KFServing installation

Now, create an inference service. From the root of the kfserving directory, run:

oc create ns kfserving-test
oc apply -f docs/samples/sklearn/sklearn.yaml -n kfserving-test

Give it a minute, then check the InferenceService status:

oc get inferenceservices sklearn-iris -n kfserving-test

NAME           URL                                              READY   DEFAULT TRAFFIC   CANARY TRAFFIC   AGE
sklearn-iris   http://sklearn-iris.kfserving-test.example.com   True    100                                3m37s

Once the InferenceService is ready, try curling it for a prediction:

export INGRESS_HOST=$(oc get route istio-ingressgateway -n istio-system -ojsonpath='{.spec.host}')
export INGRESS_PORT=$(oc -n istio-system get service istio-ingressgateway -o jsonpath='{.spec.ports[?(@.name=="http2")].nodePort}')
export SERVICE_HOSTNAME=$(oc get inferenceservice sklearn-iris -n kfserving-test -o jsonpath='{.status.url}' | cut -d "/" -f 3)
curl -v -H "Host: ${SERVICE_HOSTNAME}" http://${INGRESS_HOST}:${INGRESS_PORT}/v1/models/sklearn-iris:predict -d @./docs/samples/sklearn/iris-input.json

You should see a prediction output like:

{"predictions": [1, 1]}