Kubernetes Cluster Instance Matching

This project is a Python-based server that helps identify the AWS EC2 instances or Azure VMs that best fit for a Kubernetes cluster based on their CPU and memory requirements and limits.

Prerequisites

• Python 3.9 or higher
• Docker (optional, for containerization)

Installation

1. Clone the repository:

git clone git@github.com:raghavendra-rafay/k8s-cost-clinder.git
cd k8s-cost-clinder

2. (Optional) Create and activate a virtual environment:

python3 -m venv venv
source venv/bin/activate

3. Install the required Python dependencies:

pip install -r requirements.txt

Usage

1. Start the server:

python app.py

2. Access the server:

Open your web browser and go to http://localhost:5000.

• If you see an HTML form, you can upload a kubeconfig file and click the "Identify Instance" button to get the instance information that best fits the Kubernetes cluster.
• If you see an error message or encounter any issues, please make sure the server is running correctly and check the terminal for any error logs.

Docker Containerization (optional)

1. Build the Docker image:

docker build -t flask-server .

2. Run the Docker container:

docker run -p 9000:5000 --name flask-server-container flask-server

3. Access the server:

Open your web browser and go to http://localhost:9000.