I've got a Raspberry Pi 5 sitting on my desk that runs my entire home automation stack, monitors my servers, and even hunts for security vulnerabilities while I sleep. It cost me under $100 and draws less power than a lightbulb. Here's how I built it — and how you can too.
Why the Pi?
The Raspberry Pi is the perfect automation server: it's silent, runs 24/7 on pennies of electricity, and has a massive ecosystem of accessories. But the real magic happens when you stop treating it like a toy and start running autonomous workflows on it.
Here's what my Pi handles right now:
- Network monitoring — pings critical services every 60 seconds, alerts me via Telegram if anything goes down
- Automated security scans — runs nightly vulnerability checks against my homelab and cloud infrastructure
- Smart home orchestration — controls lights, cameras, and sensors through Home Assistant + custom Python scripts
- AI-powered log analysis — parses system logs and flags anomalies before they become problems
The Stack
All of this runs on a headless Pi with a simple but powerful stack:
Python + systemd for the core services. Every automation is a Python script wrapped in a systemd unit file. This gives you automatic restarts, logging, and dependency management for free.
SQLite for local state. No need for a heavy database — SQLite handles everything from sensor readings to scan results without breaking a sweat.
Cron + health checks for scheduling. Each cron job outputs a structured JSON log, and a watchdog script checks those logs for failures. If something breaks, I get a notification with the exact error and a suggested fix — no more silent cron failures discovered days later.
Docker for isolated workloads. Security tools, web scrapers, and anything that touches untrusted input runs in containers. One compromised container can't touch the rest of the system.
Automation That Actually Saves Time
1. The Self-Healing Pi
My Pi monitors itself. A health check script runs every 5 minutes, checking:
- CPU temperature (throttles if it exceeds 70°C)
- Disk usage (cleans old logs at 85%)
- Memory pressure (restarts leaky services)
- SD card wear (alerts me when it's time to replace)
import psutil
import subprocess
def check_temperature():
temp = psutil.sensors_temperatures()['cpu_thermal'][0].current
if temp > 70:
subprocess.run(['systemctl', 'restart', 'heavy-service'])
return {"status": "throttled", "temp": temp}
return {"status": "ok", "temp": temp}
This has saved me from at least three SD card failures and countless overheating incidents.
2. Automated Bug Bounty Recon
One of my favorite Pi projects: a fully autonomous bug bounty reconnaissance pipeline. It runs nightly and performs:
- Subdomain enumeration with multiple tools
- Port scanning on discovered hosts
- Technology fingerprinting
- Screenshot capture of web services
All results land in a structured directory, and the Pi sends me a morning summary with anything worth investigating. If you want to build something similar, I put together a complete Bug Bounty Automation Kit that includes all the scripts, Docker configurations, and cron schedules I use.
3. AI-Powered Log Analysis
This is where things get interesting. I pipe system logs through a lightweight LLM (running locally via Ollama on a separate machine, with the Pi sending API calls) that:
- Detects patterns I'd miss (like a service that fails every Tuesday at 3 AM)
- Flags security-relevant events (unexpected SSH logins, new listening ports)
- Generates a daily digest in plain English
The Pi doesn't run the model — it just orchestrates the workflow. The heavy lifting happens elsewhere, and the Pi stitches everything together.
Getting Started
You don't need to build everything at once. Start with one automation that solves a real problem:
- Pick a pain point — something you manually check or fix regularly
- Write a Python script that handles it
- Wrap it in systemd so it stays running
- Add monitoring so you know when it breaks
- Iterate — add notifications, logging, and intelligence over time
Going Further
Once you've got the basics, the possibilities are endless. I've used my Pi for:
- Automated code review on PRs
- Social media scheduling and analytics
- Cryptocurrency price monitoring and alerts
- Personal data pipelines (backups, photo organization, etc.)
If you're ready to take your Raspberry Pi automation to the next level, check out the AI Agent Toolkit — it's a complete guide to building autonomous agents that run on lightweight hardware, including ready-to-deploy templates for the Pi.
Your Pi is more powerful than you think. Give it a real job, and it'll surprise you.
