Cloud Native Resource Monitoring Python App on Kubernetes

This project demonstrates how to create a cloud-native resource monitoring application using Python, Flask, Docker, AWS EKS, and Kubernetes. The application monitors system metrics like CPU and memory usage and displays them in a user-friendly web interface.

Prerequisites

• AWS Account
• Programmatic access and AWS configured with CLI
• Python3 Installed
• Docker and Kubectl installed
• Code editor (Vscode)

Getting Started

Part 1: Running the Flask Application Locally

1. Clone the repository: git clone <repository_url>
2. Install dependencies: pip3 install -r requirements.txt
3. Run the application: python3 app.py

Part 2: Dockerizing the Flask Application

1. Create a Dockerfile
2. Build the Docker image: docker build -t <image_name> .
3. Run the Docker container: docker run -p 5000:5000 <image_name>

Part 3: Pushing the Docker Image to ECR

1. Create an ECR repository using Python
2. Push the Docker image to ECR: docker push <ecr_repo_uri>:<tag>

Part 4: Creating an EKS Cluster and Deploying the App Using Python

1. Create an EKS cluster and add a node group
2. Create a node group in the EKS cluster
3. Create a deployment and service (make sure to edit the name of the image on line 25 with your image URI)

Once you run python3 eks.py, the deployment and service will be created. You can check by running the following commands:

• kubectl get deployment -n default
• kubectl get service -n default
• kubectl get pods -n default

Once your pod is up and running, run the port-forward to expose the service: kubectl port-forward service/<service_name> 5000:5000

Acknowledgements

This project was inspired by a YouTube tutorial. I forked the original repository and added my own modifications to enhance the functionality of the application.