---
title: Test your Python deployment
linkTitle: Test your deployment
weight: 50
keywords: deploy, kubernetes, python
description: Learn how to develop locally using Kubernetes
aliases:
- /language/python/deploy/
- /guides/language/python/deploy/
---
## Prerequisites
- Complete all the previous sections of this guide, starting with [Use containers for Python development](develop.md).
- [Turn on Kubernetes](/manuals/desktop/features/kubernetes.md#install-and-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.
```yaml
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](./configure-github-actions.md).
```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: 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](configure-github-actions.md).
- 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](https://kubernetes.io/docs/home/).
> [!NOTE]
>
> - The `NodePort` service is good for development/testing purposes. For production you should implement an [ingress-controller](https://kubernetes.io/docs/concepts/services-networking/ingress-controllers/).
## Deploy and check your application
1. In a terminal, navigate to `python-docker-dev-example` and deploy your database to
Kubernetes.
```console
$ kubectl apply -f docker-postgres-kubernetes.yaml
```
You should see output that looks like the following, indicating your Kubernetes objects were created successfully.
```console
deployment.apps/postgres created
service/postgres created
persistentvolumeclaim/postgres-pvc created
secret/postgres-secret created
```
Now, deploy your python application.
```console
kubectl apply -f docker-python-kubernetes.yaml
```
You should see output that looks like the following, indicating your Kubernetes objects were created successfully.
```console
deployment.apps/docker-python-demo created
service/service-entrypoint created
```
2. Make sure everything worked by listing your deployments.
```console
$ kubectl get deployments
```
Your deployment should be listed as follows:
```console
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.
```console
$ kubectl get services
```
You should get output like the following.
```console
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.
```console
$ curl http://localhost:30001/
Hello, Docker!!!
```
4. Run the following commands to tear down your application.
```console
$ 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:
- [Kubernetes documentation](https://kubernetes.io/docs/home/)
- [Deploy on Kubernetes with Docker Desktop](/manuals/desktop/features/kubernetes.md)
- [Swarm mode overview](/manuals/engine/swarm/_index.md)