Added k8s mnist example using minikube

kubernetes/examples/mnist/MNIST.md

@@ -0,0 +1,117 @@
+# Digit recognition model with MNIST dataset using a Kubernetes cluster
+
+In this example, we show how to use a pre-trained custom MNIST model to performing real time Digit recognition with TorchServe.
+We will be serving the model using a Kubernetes cluster deployed using [minikube](https://minikube.sigs.k8s.io/docs/start/).
+
+The inference service would return the digit inferred by the model in the input image.
+
+We used the following pytorch example to train the basic MNIST model for digit recognition :
+https://github.com/pytorch/examples/tree/master/mnist
+
+## Serve an MNIST model on TorchServe docker container
+
+Run the commands given in following steps from the parent directory of the root of the repository. For example, if you cloned the repository into /home/my_path/serve, run the steps from /home/my_path/serve
+
+ ### Create a torch model archive using the torch-model-archiver utility to archive the above files.
+
+  ```
+  torch-model-archiver --model-name mnist --version 1.0 --model-file examples/image_classifier/mnist/mnist.py --serialized-file examples/image_classifier/mnist/mnist_cnn.pt --handler  examples/image_classifier/mnist/mnist_handler.py
+  ```
+
+  ### Move .mar file into model_store directory
+
+  ```
+  mkdir model_store
+  mv mnist.mar model_store/
+  ```
+
+  ### Start kubernetes cluster
+
+  We start the cluster mounting the location of `serve` to `/host`
+
+  The following command works if torchserve is under $HOME/serve
+  ```
+  minikube start --mount-string="$HOME/serve:/host" --mount
+  ```
+
+  ### Deploy the cluster
+
+  In this example, we are launching a cluster with a single pod.
+  We are exposing ports 8080 and 8081
+  We are also mapping the the `model_store` directory created on host to
+  `/home/model-server/model-store` on the container
+
+  ```
+  kubectl apply -f kubernetes/examples/mnist/deployment.yaml
+  ```
+
+  Make sure the pod is running
+
+  ```
+  kubectl get pods
+  ```
+  shows the output
+  ```
+  NAME                      READY   STATUS    RESTARTS   AGE
+  ts-def-5c95fdfd57-m446t   1/1     Running   0          58m
+
+  ```
+
+  ### Create a Service
+  We create a service to send inference request to the pod.
+  We are using `NodePort` so that the cluster can be accessed by the outside world.
+
+  ```
+  kubectl apply -f kubernetes/examples/mnist/service.yaml
+  ```
+
+  Verify the service is running
+
+  ```
+  kubectl get svc
+  ```
+  shows the output
+  ```
+
+    NAME         TYPE        CLUSTER-IP      EXTERNAL-IP   PORT(S)                         AGE
+    ts-def       NodePort    10.109.14.120   <none>        8080:30160/TCP,8081:30302/TCP   59m
+
+  ```
+
+  ### Make cluster accessible by localhost
+
+  We use kubectl port-forward to make the cluster accessible from the local machine. This will run in the background. Make sure to kill the process when the test is done.
+
+  ```
+  kubectl port-forward svc/ts-def 8080:8080 8081:8081 &
+  ```
+
+  ### Register the model on TorchServe using the above model archive file
+
+  ```
+  curl -X POST "localhost:8081/models?model_name=mnist&url=mnist.mar&initial_workers=4"
+  ```
+
+  If this succeeeds, you will see a message like below
+
+  ```
+  {
+  "status": "Model \"mnist\" Version: 1.0 registered with 4 initial workers"
+  }
+  ```
+
+  ### Run digit recognition inference
+
+  ```
+  curl http://127.0.0.1:8080/predictions/mnist -T examples/image_classifier/mnist/test_data/0.png
+  ```
+
+   The output in this case will be a `0`
+
+
+  ### Delete the cluster
+
+  ```
+  minikube stop
+  minikube delete
+  ```

kubernetes/examples/mnist/deployment.yaml

@@ -0,0 +1,29 @@
+apiVersion: apps/v1
+kind: Deployment
+metadata:
+  name: ts-def
+  labels:
+    app: ts-def
+spec:
+  replicas: 1
+  selector:
+    matchLabels:
+      app: ts-def
+  template:
+    metadata:
+      labels:
+        app: ts-def
+    spec:
+      volumes:
+        - name: model-store
+          hostPath:
+            path: /host/model_store
+      containers:
+        - name: torchserve
+          image: pytorch/torchserve:latest-cpu
+          ports:
+            - containerPort: 8080
+            - containerPort: 8081
+          volumeMounts:
+          - name: model-store
+            mountPath: /home/model-server/model-store

kubernetes/examples/mnist/service.yaml

@@ -0,0 +1,19 @@
+apiVersion: v1
+kind: Service
+metadata:
+  name: ts-def
+  labels:
+    run: ts-def
+spec:
+  type: NodePort
+  selector:
+    app: ts-def
+  ports:
+  - protocol: TCP
+    port: 8080
+    targetPort: 8080
+    name: inference
+  - protocol: TCP
+    port: 8081
+    targetPort: 8081
+    name: management

ts_scripts/spellcheck_conf/wordlist.txt

@@ -1047,6 +1047,7 @@ QueueTime
 WorkerLoadTime
 WorkerName
 WorkerThreadTime
+minikube
 MicroSoft
 lmi
 torchrun