Kubernetes (K8s) is an open-source container orchestration system that helps deploy, manage, and scale containerized applications. In this guide, we’ll learn how to deploy a Python application on Kubernetes.
What You Will Learn
Why use Kubernetes for Python applications
Writing a Dockerfile for a Python app
Creating Kubernetes YAML files
Deploying a Python app on a Kubernetes cluster
Scaling and managing applications with Kubernetes
1. Why Use Kubernetes for Python Applications?
Kubernetes automates deployment, scaling, and management of containerized applications.
Benefits
✔ Scalability – Easily scale applications up or down
✔ High Availability – Automatically restarts failed containers
✔ Load Balancing – Distributes traffic efficiently
✔ Self-Healing – Detects and replaces unhealthy containers
2. Setting Up Kubernetes for Python Applications
2.1 Prerequisites
✔ Install Docker and Kubernetes (kubectl, minikube or a cloud Kubernetes service)
Start Minikube (for local development):
minikube start
3. Writing a Python Application and Dockerizing It
3.1 Example Python App (app.py)
from flask import Flask
app = Flask(__name__)
@app.route('/')
def home():
return "Hello, Kubernetes!"
if __name__ == '__main__':
app.run(host='0.0.0.0', port=5000)
3.2 Create a requirements.txt File
flask
3.3 Writing the Dockerfile
# Use Python as base image
FROM python:3.9
# Set working directory
WORKDIR /app
# Copy application files
COPY . .
# Install dependencies
RUN pip install --no-cache-dir -r requirements.txt
# Expose the application port
EXPOSE 5000
# Run the application
CMD ["python", "app.py"]
3.4 Build and Push the Docker Image
- Build the Image
docker build -t my-python-app . - Tag and Push to Docker Hub
docker tag my-python-app username/my-python-app docker push username/my-python-app
4. Deploying to Kubernetes
We need three key components:
✔ Deployment – Defines how the app runs and updates
✔ Service – Exposes the application to the network
✔ Ingress (optional) – Manages external access
4.1 Creating Deployment YAML (deployment.yaml)
apiVersion: apps/v1
kind: Deployment
metadata:
name: python-app
spec:
replicas: 2
selector:
matchLabels:
app: python-app
template:
metadata:
labels:
app: python-app
spec:
containers:
- name: python-app
image: username/my-python-app
ports:
- containerPort: 5000
4.2 Creating a Service YAML (service.yaml)
apiVersion: v1
kind: Service
metadata:
name: python-app-service
spec:
selector:
app: python-app
ports:
- protocol: TCP
port: 80
targetPort: 5000
type: LoadBalancer
5. Deploying to Kubernetes
5.1 Apply the Deployment and Service
kubectl apply -f deployment.yaml
kubectl apply -f service.yaml
5.2 Verify the Deployment and Service
kubectl get pods
kubectl get services
6. Scaling the Application
6.1 Scale Up to 5 Replicas
kubectl scale deployment python-app --replicas=5
6.2 Verify Scaling
kubectl get pods
7. Managing Kubernetes Applications
7.1 View Logs
kubectl logs <pod-name>
7.2 Describe a Pod
kubectl describe pod <pod-name>
7.3 Delete Deployment and Service
kubectl delete -f deployment.yaml
kubectl delete -f service.yaml