/sys-monInsight

System Monitoring and Analysis Tool is a utility for real-time performance tracking. It logs CPU, memory, and disk usage, provides visual graphs, and offers performance recommendations. Perfect for optimizing system efficiency.

Primary LanguagePython

System Monitoring and Analysis Tool

Overview

This project is a Python-based system monitoring and analysis tool designed to track and log the CPU, memory, and disk usage of your computer. The tool provides real-time usage statistics, logs data to a CSV file, and offers recommendations based on system performance. It also includes data visualization capabilities for analyzing historical usage trends.

Features

  • Real-Time Monitoring: Captures CPU, memory, and disk usage statistics every second.
  • Data Logging: Logs usage data to a CSV file for historical analysis.
  • Data Analysis: Analyzes logged data and generates plots to visualize CPU, memory, and disk usage over time.
  • Recommendations: Provides suggestions for optimizing system performance based on current usage metrics.

Installation

  1. Clone the Repository

    git clone https://github.com/nomadsdev/sys-monInsight.git 
cd sys-monInsight

  2. Install Dependencies

    Ensure you have Python 3.x installed. Then install the required Python packages using pip:

    pip install psutil pandas matplotlib

Usage

  1. Run the Monitoring Script

    Execute the monitoring script to start logging system usage data:

    python main.py

    The script will log data to system_usage_log.csv and print real-time statistics and recommendations to the console.

  2. Analyze Data

    To visualize the logged data, run the following script:

    python main.py

    This script will read the system_usage_log.csv file and generate plots for CPU, memory, and disk usage over time.

Scripts

main.py

  • Function: Collects system usage data and logs it to a CSV file.
  • Functions:
    • get_cpu_usage(): Retrieves the current CPU usage percentage.
    • get_memory_usage(): Retrieves current memory usage statistics.
    • get_disk_usage(): Retrieves current disk usage statistics.
    • log_usage_to_csv(): Logs the collected data to system_usage_log.csv.
    • provide_recommendations(): Provides recommendations based on system usage.

analyze.py

  • Function: Analyzes and visualizes the logged system usage data.
  • Functions:
    • analyze_data(file_path): Loads data from a CSV file and generates usage plots.

File Structure

  • monitor.py: Script for monitoring and logging system usage.
  • analyze.py: Script for analyzing and visualizing logged data.
  • system_usage_log.csv: CSV file where usage data is logged.
  • README.md: This documentation file.

Recommendations

  • High CPU Usage: Consider upgrading your CPU or optimizing applications.
  • High Memory Usage: Consider adding more RAM or closing unnecessary applications.
  • High Disk Usage: Consider cleaning up or expanding disk space.

License

This project is licensed under the MIT License.