Now It is time to change from docker-compose to deploy into Kubernetes.

As this is not new to me to deploy microservice into K8S, also I already have a running Kubernetes cluster in hand, so here I will just create docker images for the 3 services: API gateway, user and order, then push them into the docker hub repository, then create Kubernetes manifest for deployment and service.

  # Folder structure
  /07-with-k8s
  .
  ├── api_gateway.py
  ├── depolyment.yaml
  ├── Dockerfile_apigateway
  ├── Dockerfile_order
  ├── Dockerfile_user
  ├── order_service.py
  └── user_service.py

  # Build, tag and push the docker images
  docker login

  docker build -t zackz001/python-user:latest -f Dockerfile_user .
  docker build -t zackz001/python-order:latest -f Dockerfile_order .
  docker build -t zackz001/python-apigateway:latest -f Dockerfile_apigateway .
  docker push zackz001/python-apigateway:latest
  docker push zackz001/python-user:latest
  docker push zackz001/python-order:latest

  docker image ls

  REPOSITORY                                      TAG       IMAGE ID       CREATED        SIZE
  zackz001/python-apigateway                      latest    bc3db11f4be8   1 hours ago    138MB
  zackz001/python-user                            latest    c93973bece33   1 hours ago    136MB
  zackz001/python-order                           latest    e35d5de9254b   1 hours ago    136MB
  prom/prometheus                                 latest    1bd2b9635267   8 days ago     271MB
  grafana/grafana                                 latest    c42c21cd0ebc   3 weeks ago    453MB
  consul                                          1.15.4    686495461132   4 months ago   155MB
  docker.elastic.co/elasticsearch/elasticsearch   7.13.2    11a830014f7c   3 years ago    1.02GB
  docker.elastic.co/logstash/logstash             7.13.2    8dc1af4dd662   3 years ago    965MB
  docker.elastic.co/kibana/kibana                 7.13.2    6c4869a27be1   3 years ago    1.35GB

  # k8s deployment Manifests

  apiVersion: apps/v1
  kind: Deployment
  metadata:
   name: user-service
  spec:
   replicas: 1
   selector:
    matchLabels:
     app: user-service
   template:
    metadata:
     labels:
      app: user-service
    spec:
     containers:
      - name: user-service
        image: zackz001/python-user:latest
        ports:
         - containerPort: 5001

  ---
  apiVersion: v1
  kind: Service
  metadata:
   name: user-service
  spec:
   selector:
    app: user-service
   ports:
    - protocol: TCP
      port: 5001
      targetPort: 5001

  ---
  apiVersion: apps/v1
  kind: Deployment
  metadata:
   name: order-service
  spec:
   replicas: 1
   selector:
    matchLabels:
     app: order-service
   template:
    metadata:
     labels:
      app: order-service
    spec:
     containers:
      - name: order-service
        image: zackz001/python-order:latest
        ports:
         - containerPort: 5002

  ---
  apiVersion: v1
  kind: Service
  metadata:
   name: order-service
  spec:
   selector:
    app: order-service
   ports:
    - protocol: TCP
      port: 5002
      targetPort: 5002

  ---
  apiVersion: apps/v1
  kind: Deployment
  metadata:
   name: api-gateway
  spec:
   replicas: 1
   selector:
    matchLabels:
     app: api-gateway
   template:
    metadata:
     labels:
      app: api-gateway
    spec:
     containers:
      - name: api-gateway
        image: zackz001/python-apigateway:latest
        ports:
         - containerPort: 5000

  ---
  apiVersion: v1
  kind: Service
  metadata:
   name: api-gateway
  spec:
   type: NodePort
   selector:
    app: api-gateway
   ports:
    - protocol: TCP
      port: 5000
      targetPort: 5000
  

Now Run kubectl apply -f to bring all deployments and services up and running. Should see all services in the Rancher console.

  kubectl create ns python

  kubectl apply -f depolyment.yaml -n python

  kubectl get all -n python

  NAME                                 READY   STATUS    RESTARTS      AGE
  pod/api-gateway-d664cf8c4-7l7q8      1/1     Running   2 (50m ago)   1h
  pod/order-service-856577f666-gk5gt   1/1     Running   2 (50m ago)   1h
  pod/user-service-5d8766d9cb-4rqnz    1/1     Running   2 (50m ago)   1h

  NAME                    TYPE        CLUSTER-IP      EXTERNAL-IP   PORT(S)          AGE
  service/api-gateway     NodePort    10.43.38.27      5000:32060/TCP   1h
  service/order-service   ClusterIP   10.43.27.255     5002/TCP         1h
  service/user-service    ClusterIP   10.43.160.232    5001/TCP         1h

  NAME                            READY   UP-TO-DATE   AVAILABLE   AGE
  deployment.apps/api-gateway     1/1     1            1           1h
  deployment.apps/order-service   1/1     1            1           1h
  deployment.apps/user-service    1/1     1            1           1h

  NAME                                       DESIRED   CURRENT   READY   AGE
  replicaset.apps/api-gateway-d664cf8c4      1         1         1       1h
  replicaset.apps/order-service-856577f666   1         1         1       1h
  replicaset.apps/user-service-5d8766d9cb    1         1         1       1h
  

Verify API gateway, user and order services

Access API gateway via http://NodeIP:NodePort/users and http://NodeIP:NodePort/orders

Conclusion

Now we complete all Python Flask sessions.

I have done this End-to-End Python Microservice application solution development, which enhanced my DevOps practices of Python programming, microservices architecture design and deployment with docker-compose, API Gateway implementation, service registery with Consul, logging and monitoring, and finally Kubernetes deployment.

• simple Python Flask app
• Microservice applications with user and order
• Create API gateway Flask app
• Service registery with Consul
• Logging with ELK
• Monitoring with Prometheus and Grafana
• K8S deployment