Test your Python deployment
Prerequisites
- Complete all the previous sections of this guide, starting with Use containers for python development.
- Turn on Kubernetes in Docker Desktop.
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
.
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: technox64/python-docker-dev-example-test:latest
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 a 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
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
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 yourservice-entrypoint
service, accepting traffic on port 30001/TCP and the internalClusterIP
postgres
with the port5432
open to accept connections from you python app.In a terminal, curl the service. Note that a database was not deployed in this example.
$ curl http://localhost:30001/ Hello, Docker!!!
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: