Python Application Deployment on EKS

This project demonstrates deploying a simple Python application on Amazon Elastic Kubernetes Service (EKS). The application is built using Flask and is containerized using Docker. The Kubernetes deployment includes a service to expose the application.

Features

• A Flask-based Python app.
• Dockerized application with a lightweight python:3.9-slim image.
• Kubernetes deployment and service configurations.
• Runs on EKS.

Files

• app.py: The Flask application.
• Dockerfile: Instructions for building the Docker image.
• requirements.txt: Python dependencies.
• deployment.yaml: Kubernetes Deployment manifest.
• service.yaml: Kubernetes Service manifest.
• get_helm.sh: Helper script for setting up Helm (optional).

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Prerequisites

1. Amazon EKS Cluster: Set up an EKS cluster and configure kubectl to connect to it.
2. Docker: Install Docker to build the container image.
3. kubectl: Ensure you have the Kubernetes command-line tool installed.
4. Helm (optional): If needed for additional setup tools.

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AWS EKS Setup

1. Create an EKS Cluster

Use eksctl to create an EKS cluster with the necessary node groups.

# Create EKS cluster
eksctl create cluster \
  --name flask-rps-cluster \
  --version 1.26 \
  --region <your-region> \
  --nodegroup-name flask-rps-nodes \
  --node-type t3.medium \
  --nodes 2 \
  --nodes-min 1 \
  --nodes-max 3 \
  --managed

Explanation:

• --name: Specifies the name of the cluster.
• --version: Kubernetes version for the cluster.
• --region: AWS region where the cluster will be created.
• --nodegroup-name: Name of the managed node group.
• --node-type: Instance type for the nodes (e.g., t3.medium).
• --nodes: Number of desired nodes (initial size).
• --nodes-min / --nodes-max: Auto-scaling configuration for the node group.
• --managed: Uses managed node groups for easier management.

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2. Configure kubectl to Connect to the Cluster

After creating the cluster, update your kubeconfig file:

aws eks --region <your-region> update-kubeconfig --name flask-rps-cluster

Verify connection to the cluster:

kubectl get nodes

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3. Deploy the Flask App

Step 1: Apply the Deployment Manifest

Save the following deployment manifest to deployment.yaml:

apiVersion: apps/v1
kind: Deployment
metadata:
  name: flask-rps-deployment
  labels:
    app: flask-rps
spec:
  replicas: 2
  selector:
    matchLabels:
      app: flask-rps
  template:
    metadata:
      labels:
        app: flask-rps
    spec:
      containers:
      - name: flask-rps
        image: ibraheemcisse/flask-rps-app:latest
        ports:
        - containerPort: 5000

Apply it using:

kubectl apply -f deployment.yaml

Step 2: Apply the Service Manifest

Save the following service manifest to service.yaml:

apiVersion: v1
kind: Service
metadata:
  name: flask-rps-service
spec:
  type: LoadBalancer
  selector:
    app: flask-rps
  ports:
  - protocol: TCP
    port: 80
    targetPort: 5000

Apply it using:

kubectl apply -f service.yaml

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4. Access the Application

Once the LoadBalancer service is deployed, get its external IP:

kubectl get svc

Access your app at http://<external-ip>.

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Future Enhancements

• Add Horizontal Pod Autoscaler (HPA) for scaling.
• Implement an Ingress resource for better traffic management.
• Enhance security with NetworkPolicies and Secrets.