Test your Python deployment

Table of contents

Prerequisites

Overview

In this section, you'll learn how to use Docker Desktop to deploy your application to a fully-featured Kubernetes environment on your development machine. This allows you to test and debug your workloads on Kubernetes locally before deploying.

Create a Kubernetes YAML file

In your python-docker-dev-example directory, create a file named docker-postgres-kubernetes.yaml. Open the file in an IDE or text editor and add the following contents.

apiVersion: apps/v1 kind: Deployment metadata:  name: postgres  namespace: default spec:  replicas: 1  selector:  matchLabels:  app: postgres  template:  metadata:  labels:  app: postgres  spec:  containers:  - name: postgres  image: postgres  ports:  - containerPort: 5432  env:  - name: POSTGRES_DB  value: example  - name: POSTGRES_USER  value: postgres  - name: POSTGRES_PASSWORD  valueFrom:  secretKeyRef:  name: postgres-secret  key: POSTGRES_PASSWORD  volumeMounts:  - name: postgres-data  mountPath: /var/lib/postgresql/data  volumes:  - name: postgres-data  persistentVolumeClaim:  claimName: postgres-pvc --- apiVersion: v1 kind: Service metadata:  name: postgres  namespace: default spec:  ports:  - port: 5432  selector:  app: postgres --- apiVersion: v1 kind: PersistentVolumeClaim metadata:  name: postgres-pvc  namespace: default spec:  accessModes:  - ReadWriteOnce  resources:  requests:  storage: 1Gi --- apiVersion: v1 kind: Secret metadata:  name: postgres-secret  namespace: default type: Opaque data:  POSTGRES_PASSWORD: cG9zdGdyZXNfcGFzc3dvcmQ= # Base64 encoded password (e.g., 'postgres_password')

In your python-docker-dev-example directory, create a file named docker-python-kubernetes.yaml. Replace DOCKER_USERNAME/REPO_NAME with your Docker username and the repository name that you created in Configure CI/CD for your Python application.

apiVersion: apps/v1 kind: Deployment metadata:  name: docker-python-demo  namespace: default spec:  replicas: 1  selector:  matchLabels:  service: fastapi  template:  metadata:  labels:  service: fastapi  spec:  containers:  - name: fastapi-service  image: DOCKER_USERNAME/REPO_NAME  imagePullPolicy: Always  env:  - name: POSTGRES_PASSWORD  valueFrom:  secretKeyRef:  name: postgres-secret  key: POSTGRES_PASSWORD  - name: POSTGRES_USER  value: postgres  - name: POSTGRES_DB  value: example  - name: POSTGRES_SERVER  value: postgres  - name: POSTGRES_PORT  value: "5432"  ports:  - containerPort: 8001 --- apiVersion: v1 kind: Service metadata:  name: service-entrypoint  namespace: default spec:  type: NodePort  selector:  service: fastapi  ports:  - port: 8001  targetPort: 8001  nodePort: 30001

In these Kubernetes YAML file, there are various objects, separated by the ---:

  • A Deployment, describing a scalable group of identical pods. In this case, you'll get just one replica, or copy of your pod. That pod, which is described under template, has just one container in it. The container is created from the image built by GitHub Actions in Configure CI/CD for your Python application.
  • A Service, which will define how the ports are mapped in the containers.
  • A PersistentVolumeClaim, to define a storage that will be persistent through restarts for the database.
  • A Secret, Keeping the database password as an example using secret kubernetes resource.
  • A NodePort service, which will route traffic from port 30001 on your host to port 8001 inside the pods it routes to, allowing you to reach your app from the network.

To learn more about Kubernetes objects, see the Kubernetes documentation.

Note
  • The NodePort service is good for development/testing purposes. For production you should implement an ingress-controller.

Deploy and check your application

  1. In a terminal, navigate to python-docker-dev-example and deploy your database to Kubernetes.

    $ kubectl apply -f docker-postgres-kubernetes.yaml

    You should see output that looks like the following, indicating your Kubernetes objects were created successfully.

    deployment.apps/postgres created service/postgres created persistentvolumeclaim/postgres-pvc created secret/postgres-secret created

    Now, deploy your python application.

    kubectl apply -f docker-python-kubernetes.yaml

    You should see output that looks like the following, indicating your Kubernetes objects were created successfully.

    deployment.apps/docker-python-demo created service/service-entrypoint created

  2. Make sure everything worked by listing your deployments.

    $ kubectl get deployments

    Your deployment should be listed as follows:

    NAME READY UP-TO-DATE AVAILABLE AGE docker-python-demo 1/1 1 1 48s postgres 1/1 1 1 2m39s

    This indicates all one of the pods you asked for in your YAML are up and running. Do the same check for your services.

    $ kubectl get services

    You should get output like the following.

    NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE kubernetes ClusterIP 10.43.0.1 <none> 443/TCP 13h postgres ClusterIP 10.43.209.25 <none> 5432/TCP 3m10s service-entrypoint NodePort 10.43.67.120 <none> 8001:30001/TCP 79s

    In addition to the default kubernetes service, you can see your service-entrypoint service, accepting traffic on port 30001/TCP and the internal ClusterIP postgres with the port 5432 open to accept connections from you python app.

  3. In a terminal, curl the service. Note that a database was not deployed in this example.

    $ curl http://localhost:30001/ Hello, Docker!!!

  4. Run the following commands to tear down your application.

    $ kubectl delete -f docker-python-kubernetes.yaml $ kubectl delete -f docker-postgres-kubernetes.yaml

Summary

In this section, you learned how to use Docker Desktop to deploy your application to a fully-featured Kubernetes environment on your development machine.

Related information: