Step 1: Set Up System Monitoring

1. Install Prometheus and Node Exportersudo apt install prometheus prometheus-node-exporter
2. Configure Prometheus to scrape metrics from your system.
3. Visualize with Grafana:
   • Install Grafana.
   • Connect it to Prometheus.
   • Create dashboards for CPU, memory, disk I/O, and service health.

Step 2: Train a Machine Learning Model

1. Collect historical logs and metrics (e.g., /var/log/syslog, Prometheus time series).
2. Use Python with pandas, scikit-learn, or TensorFlow to:
   • Label past failures.
   • Train a model to detect anomalies or predict failures.
   • Export the model as a .pkl or .onnx file.

Step 3: Automate Recovery

1. Write Bash or Python scripts to:
   • Restart services (systemctl restart nginx)
   • Roll back configs (cp /etc/nginx/nginx.conf.bak /etc/nginx/nginx.conf)
   • Reboot if needed
2. Use cron jobs or a Python daemon to:
   • Run the ML model periodically
   • Trigger recovery scripts based on predictions

Step 4: Test and Harden

• Simulate failures (e.g., kill a service, fill disk space).
• Monitor how the system reacts.
• Add logging and alerting (e.g., email or Telegram bot notifications).

You now have a self-healing Linux system that predicts and recovers from failures automatically—ideal for showcasing automation, AI, and DevOps skills.