Add "machine-learning-ui deploy with k8s"

machine-learning-ui/README.md

@@ -33,3 +33,21 @@ Extra Build ARGs
 - ``swupd_args`` Specifies [SWUPD](https://github.com/clearlinux/swupd-client/blob/master/docs/swupd.1.rst#options) flags
 
 Default build args in Docker are on: https://docs.docker.com/engine/reference/builder/#arg
+
+### Deploy with Kubernetes
+
+This image can also be deployed on a Kubernetes cluster, such as [minikube](https://kubernetes.io/docs/setup/learning-environment/minikube/).The following example YAML files are provided in the repository as reference for Kubernetes deployment:
+
+- [`machine-learning-ui-deployment.yaml`](https://github.com/clearlinux/dockerfiles/blob/master/machine-learning-ui/machine-learning-ui-deployment.yaml): example to provide jupyter notebook service.
+
+  
+
+Steps to deploy notebook on a Kubernetes cluster:
+
+1. Deploy `machine-learning-ui-deployment.yaml`
+
+   ```
+   kubectl create -f machine-learning-ui-deployment.yaml
+   ```
+
+2. Navigate to [http://\<nodeIP\>:30001](http://\<nodeIP\>:30001) in your browser, where 30001 is the port number defined in your service.

machine-learning-ui/machine-learning-ui-deployment.yaml

@@ -0,0 +1,39 @@
+apiVersion: v1
+kind: Service
+metadata:
+  name: ml-notebook
+  labels:
+    app: ml-notebook
+spec:
+  type: NodePort
+  ports:
+    - port: 8888     
+      targetPort: 8888
+      nodePort: 30001
+      name: jupyter
+  selector:
+    app: ml-notebook
+
+---
+apiVersion: apps/v1beta2
+kind: Deployment
+metadata:
+  name: ml-notebook
+  labels:
+    app: ml-notebook
+spec:
+  selector:
+    matchLabels:
+      app: ml-notebook
+  template:
+    metadata:
+      labels:
+        app: ml-notebook
+    spec:
+      containers:
+        - name: jupyter
+          image: "docker.io/clearlinux/machine-learning-ui"
+          imagePullPolicy: IfNotPresent
+          ports:
+            - containerPort: 8888
+              name: jupyter