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πŸ–₯️ Infrastructure Monitoring Dashboard A Streamlit-Based System Health & Resource Monitoring Tool

πŸ“˜ Overview This project is an infrastructure monitoring dashboard developed for a university assignment as part of a broader exploration into system administration, security, and system visualisation. The application provides a real-time view of system health, resource usage, and diagnostic information using a clean, multipage Streamlit interface.

This final version extends an earlier beta prototype originally built using HTML, CSS, PHP, and JavaScript. It has now been re-implemented using Python and Streamlit to improve portability, streamline development, and enable simplified deployment on virtualised environments.

🎯 Project Objectives Design, build, and deploy a functional system monitoring dashboard Provide real-time system metrics (CPU, memory, disk, processes) Support testing within a controlled virtual environment (e.g., Kali Linux VM) Demonstrate the evolution from a traditional LAMP-style stack to a Python framework Show understanding of virtualisation, OS interaction, and local infrastructure tooling

🧩 Features System Information Panel Hostname Operating system Architecture Uptime Resource Monitoring CPU usage Memory consumption Disk utilisation Processes Overview Active processes High-resource tasks Multipage Streamlit Layout Organised pages for metrics, system information, and diagnostics Lightweight Deployment Runs locally on any Linux VM with Python

πŸ“¦ Installation Requirements Python 3.8+ Streamlit pandas psutil

Linux environment (tested on Kali Linux)

Install dependencies pip install streamlit pandas psutil

▢️ Running the Application Local run python -m streamlit run app.py

Access in a browser: http://localhost:8501

Remote access (within VM network) python -m streamlit run app.py --server.address 0.0.0.0 --server.port 8501

From another device: http://:8501

πŸ—οΈ Project Structure Streamlit/ β”œβ”€β”€ app.py β”œβ”€β”€ pages/ β”œβ”€β”€ Images/ └── README.md

Add log analysis and threat-detection modules

Containerise the application using Docker

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