PyCostOptiCap: Infrastructure Cloud Cost Optimization Model

Disclaimer: Only including coding files without data for security reasons

PyCostOptiCap is a powerful Python-based project that provides a user-friendly interface for an intelligent infrastructure cost optimization model. This project is designed to help organizations maximize cost savings by optimizing the total cost of infrastructure for Virtual Machines (VMs) and Bare Metal (BM) servers. By considering critical parameters such as the number of hosts, the number of CPUs, and the database size, PyCostOptiCap employs various multi-linear regression algorithms and customized cost functions (including Mean Absolute Error - MAE for VMs and Root Mean Square Error - RMSE for BMs) to provide cost-saving recommendations.

Table of Contents

• Installation
• Usage
• Features
• Contributing
• License

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/PyCostOptiCap.git

2. Navigate to the project directory:

   cd PyCostOptiCap

3. Install the required dependencies:

   pip install -r requirements.txt

4. Run the application:

   python app.py

Usage

1. Open your web browser and go to http://localhost:5000 to access the PyCostOptiCap interface.

2. Follow the on-screen instructions to input your data and retrieve cost-saving recommendations.

3. Explore the various features and options provided by PyCostOptiCap to fine-tune your infrastructure cost optimization.

Features

• User-friendly Python-based front-end for the infrastructure cost optimization model.
• Customizable input parameters, including the number of hosts, number of CPUs, and database size.
• Utilizes multi-linear regression algorithms and cost functions (MAE for VMs, RMSE for BMs) to provide accurate cost-saving recommendations.
• Monitors and maximizes cost savings by optimizing infrastructure capacity usage.
• Intuitive dashboard for comparing optimized infrastructure capacity utilization against actual trending data.
• Empowers users to efficiently allocate resources, reducing over-provisioning and unnecessary costs.
• Addresses challenges related to forecasting demand through intelligent cost optimization algorithms.
• Potential for significant cost reduction opportunities for users.

Contributing

We welcome contributions from the community. To contribute to PyCostOptiCap, please follow these steps:

1. Fork the repository.

2. Create a new branch for your feature or bug fix:

   git checkout -b feature/your-feature-name

3. Make your changes and commit them with clear and concise messages:

   git commit -m "Add your feature or fix"

4. Push your changes to your fork:

   git push origin feature/your-feature-name

5. Open a pull request to the main repository, describing your changes in detail.

License

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

---

Thank you for using PyCostOptiCap! We hope this project helps you optimize your infrastructure costs effectively. If you have any questions or encounter issues, please feel free to open an issue on GitHub or contact us at [[email protected]].