Container Orchestration for Python Services with Kubernetes

1. Introduction

This lesson covers how to use Kubernetes for orchestrating Python microservices. Kubernetes automates the deployment, scaling, and management of containerized applications, providing a robust platform for Python services.

2. Key Concepts

3. Kubernetes Setup

To get started with Kubernetes, you need to set up a Kubernetes cluster. This can be done using various tools such as Minikube, kubeadm, or cloud providers like GKE, EKS, or AKS.

3.1 Setting up Minikube

Minikube is a local Kubernetes environment that you can set up easily.

brew install minikube
minikube start

4. Deploying Python Service

Once your Kubernetes cluster is set up, you can deploy your Python service.

4.1 Create a Dockerfile

First, create a Dockerfile for your Python application.

FROM python:3.9-slim

WORKDIR /app
COPY . /app
RUN pip install -r requirements.txt

CMD ["python", "app.py"]

4.2 Build and Push Docker Image

Build your Docker image and push it to a container registry.

docker build -t yourusername/python-service:latest .
docker push yourusername/python-service:latest

4.3 Create a Kubernetes Deployment

Create a deployment YAML file to define your service.

apiVersion: apps/v1
kind: Deployment
metadata:
  name: python-service
spec:
  replicas: 2
  selector:
    matchLabels:
      app: python-service
  template:
    metadata:
      labels:
        app: python-service
    spec:
      containers:
      - name: python-service
        image: yourusername/python-service:latest
        ports:
        - containerPort: 5000

4.4 Apply the Deployment

kubectl apply -f deployment.yaml

5. Best Practices

• Use liveness and readiness probes to manage application health.
• Implement resource requests and limits to ensure efficient resource usage.
• Use ConfigMaps and Secrets to manage application configurations securely.

6. FAQ