fix k8s manifest

README.md

@@ -6,7 +6,7 @@ Example how to build and run a Machine Learning (ML) models using [Scikit-Learn]
 ![predict](https://miro.medium.com/v2/resize:fit:1150/format:webp/1*R6MR34xT4Ve6fI744EVN0A.png)
 
 
-## Usage
+## Deployment
 
 - ML image:
 ```
@@ -15,22 +15,31 @@ $ docker run -it --rm -e CSV_FILE=/data/prices.csv -v $(PWD)/data/prices.csv:/da
 
 - Web
 ```
-$ docker run -it --rm -e MODEL_FILE=/app/model.pkl -v $(PWD)/ml-model/model.pkl:/app/model.pkl -p 8080:8080  ghcr.io/atrakic/ml-house-pricing-web:latest
+$ docker run -it --rm -e MODEL_FILE=/app/model.pkl -v $(PWD)/ml-model/model.pkl:/app/model.pkl -p 8080:8080 ghcr.io/atrakic/ml-house-pricing-web:latest
 
 ```
 
-## Docker-compose
+### Docker-compose
 
 ```
 $ docker-compose up --build --no-deps --remove-orphans -d
+
+# Test
+$ curl -d '{"rooms":2, "distance":20}' -H "Content-Type: application/json" \
+    -X POST http://localhost:5000/api
 ```
 
-## Kubernetes
+### Kubernetes
 
 ```
 $ kubectl apply -f ./k8s-manifests/web.yml
-```
 
+# Test
+$ kubectl describe -f k8s-manifests/web.yml
+$ kubectl run -it --rm --image=curlimages/curl --restart=Never curl-test -- \
+    -d '{"rooms":2, "distance":20}' -H "Content-Type: application/json" \
+    -X POST http://$(k get svc ml-house-pricing-web --output=jsonpath='{.spec.clusterIPs[0]}'):80/api
+```
 
 ## LICENSE
 See [LICENSE](LICENSE) for details.

frontend/Dockerfile

@@ -16,7 +16,7 @@ COPY ./src .
 RUN adduser -u 5678 --disabled-password --gecos "" appuser && chown -R appuser /app
 USER appuser
 
-ARG PORT=5000
+ARG PORT=8080
 ENV PORT $PORT
 EXPOSE $PORT
 

k8s-manifests/web.yml

@@ -2,13 +2,13 @@
 apiVersion: v1
 kind: Service
 metadata:
-  name: web
+  name: ml-house-pricing-web
   labels:
     app: web
 spec:
   ports:
-    - port: 8080
-      targetPort: 80
+    - port: 80
+      targetPort: 8080
       name: web
   selector:
     app: web
@@ -32,24 +32,32 @@ spec:
       containers:
         - name: web
           image: ghcr.io/atrakic/ml-house-pricing-web:latest
-          imagePullPolicy: IfNotPresent   # Always
+          imagePullPolicy: Always # IfNotPresent
           ports:
-            - containerPort: 80
+            - containerPort: 8080
               name: web
           env:
+            - name: PORT
+              value: "8080"
             - name: MODEL_FILE
               value: "/opt/model.pkl"
+          volumeMounts:
+            - name: data
+              mountPath: /opt
       initContainers:
-        - name: init-model
+        # First we need to create model and serialise data on file
+        - name: init
           image: ghcr.io/atrakic/ml-house-pricing-model:latest
-          restartPolicy: Always
+          imagePullPolicy: Always # IfNotPresent
           # command: ['sh', '-c', 'tail -F /opt/logs.txt']
           volumeMounts:
             - name: data
               mountPath: /opt
           env:
+            - name: MODEL_FILE
+              value: /opt/model.pkl
             - name: CSV_FILE
-              value: "https://raw.githubusercontent.com/atrakic/ml-model-house-pricing/data/prices.csv"
+              value: "https://raw.githubusercontent.com/atrakic/ml-model-house-pricing/main/data/prices.csv"
       volumes:
         - name: data
           emptyDir: {}

ml-model/app.py

@@ -27,3 +27,4 @@
 print(f"Model predict : {lm.predict([[15, 61]])}")  # format of input
 
 pickle.dump(lm, open(model_file, "wb"))  # serialize and save the model to the file
+print("Created model file : ", model_file)

tests/test.sh

@@ -0,0 +1,9 @@
+#!/bin/bash
+set -e
+
+curl -d '{"rooms":2, "distance":20}' -H "Content-Type: application/json" \
+  -X POST http://localhost:5000/api
+
+kubectl run -it --rm --image=curlimages/curl --restart=Never curl-test -- \
+  -d '{"rooms":2, "distance":20}' -H "Content-Type: application/json" \
+  -X POST http://$(k get svc ml-house-pricing-web --output=jsonpath='{.spec.clusterIPs[0]}'):80/api