gfragi / cloudcasestudy

Cloud Services Analysis

Overview

This repository contains a suite of tools and notebooks for analyzing cloud service usage, performing clustering, and calculating resources. It utilizes data science and machine learning techniques to optimize resource allocation and predict usage patterns for cloud service users.

Getting Started

Prerequisites

Before you begin, ensure you have met the following requirements:

• Python 3.x
• Pip package manager

Installation

Clone the repository and install the necessary Python packages:

git clone https://github.com/gfragi/cloudCasestudy.git
cd cloudCasestudy
pip install -r requirements.txt

Usage

The project includes Jupyter notebooks that can be used to run different analyses:

• clustering-storage.ipynb for clustering based on storage usage
• clustering-strg-cpu-ram.ipynb for clustering based on storage, CPU, and RAM usage
• clustering_cpu_ram.ipynb for clustering based on CPU and RAM usage
• pricing.ipynb for analyzing the pricing of resources
• resources.ipynb for calculating and predicting resource usage

Contributing

We welcome contributions from the community. If you wish to contribute to the repository, please fork the repository and create a pull request with your changes.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Support

For support, email gfragi [at] hua.gr

Case study