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OS Intelligence - Linux Deployment Guide

Prerequisites

  1. Ubuntu 20.04+ (Recommended) or any modern Linux distro.
  2. Docker installed and running (sudo systemctl status docker).
    • Add your user to docker group: sudo usermod -aG docker $USER.
  3. Python 3.9+ installed (python3 --version).
  4. Git installed.

1. Installation

Clone Request

git clone <your-repo-url>
cd OS

Install Dependencies

# It runs best in a virtual environment
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt

(Note: If requirements.txt is missing, manually install: pip install fastapi uvicorn docker requests psutil)

2. Running the Dashboard (Terminal 1)

This servers the UI and the API.

# In OS/ directory
source venv/bin/activate
python3 -m uvicorn src.dashboard_app:app --host 0.0.0.0 --port 8000
  • Open Browser to: http://localhost:8000 (or your server IP).

3. Running the Simulation Lab

  1. Navigate to Simulation Lab in the browser.
  2. Click "Start Simulation".
  3. You should see 3 simulated containers (web-server, db-service, etc.) appear.

4. Running the Real ML Project (Terminal 2)

This launches the real Docker container and the monitoring Agent.

# In OS/ directory
source venv/bin/activate

# Make script executable (first time only)
chmod +x run_ml_workload.sh

# Run it
./run_ml_workload.sh

Expected Output:

[1/3] Building Docker Image...
[2/3] Starting Container...
[3/3] Launching Agent...
SUCCESS! ML Project is running.
Agent PID: 12345

5. Verify in Dashboard

  1. Go to Statistics View.
  2. The graphs should automatically switch to show os-ml-project.
  3. Watch the 2-minute lifecycle:
    • 0-10s: Low usage.
    • 10-40s: Memory climb (Loading Data).
    • 40-100s: CPU Spike (Training).
    • 100s+: Cool down.

6. Cleanup

When finished:

# Terminate the workload and agent
./stop_ml_workload.sh

Then click "Stop" in the Simulation Lab UI.

Troubleshooting

  • Permission Denied: Ensure you used chmod +x *.sh.
  • Docker Errors: Ensure sudo docker ps works. The scripts use sudo by default for Docker commands to be safe, but if you configured non-root access, you can edit the scripts to remove sudo.
  • Port 8000 Busy: Change port in Step 2 (--port 8001) and update the URL.