Deploy to Raspberry Pi in One Command: Building a Rust-based Deployment Tool

Kazilsky — Mon, 12 Jan 2026 07:59:29 +0000

Article

Ever SSH'd into 5 different Raspberry Pis just to git pull and restart a service? Yeah, me too. That's why I built Flare.

The Problem

I run a small homelab with multiple Raspberry Pis:

Pi in living room: Home automation
Pi in garage: Temperature monitoring
Pi in basement: Blog and personal sites

Every time I wanted to deploy an update:

ssh pi@192.168.1.50
cd ~/apps/temperature-monitor
git pull
npm install
sudo systemctl restart temp-monitor

ssh pi@192.168.1.51
# ... repeat ...

ssh pi@192.168.1.52
# ... and again ...

Ansible? Too heavy. Docker Swarm? Overkill for 3 Pis. I just wanted git push → deployed.

The Solution

I built Flare - a lightweight deployment tool in Rust that:

Auto-discovers devices on your network
Deploys from GitHub/Gitea with one command
Manages apps (start/stop/restart)
Sets up databases automatically

Here's what it looks like:

![Demo GIF]https://github.com/Velooroo/Flare/raw/main/assets/demo.gif

How It Works

1. Start daemon on your Pi

# On Raspberry Pi
flared
# Listening on :7530

That's it. No Docker, no Python, just a 10MB binary.

2. Discover devices from your laptop

# On your laptop
$ flare discover
[0] 192.168.1.50:7530 (new)
[1] 192.168.1.51:7530 (new)

$ flare sync 0
Name: pi-living-room

Flare uses UDP broadcast to find devices automatically. No static IPs needed!

3. Add config to your project

Create flare.toml in your repo:

[app]
name = "temp-monitor"
version = "1.0.0"

[run]
command = "python sensor.py"
port = 8080

[database]
type = "sqlite"
name = "readings.db"

4. Deploy!

flare deploy github-user/temp-monitor --device pi-living-room

Real-World Example

Here's my temperature monitoring setup:

# sensor.py
import time
import sqlite3
from flask import Flask, jsonify
from w1thermsensor import W1ThermSensor

app = Flask(__name__)
sensor = W1ThermSensor()

@app.route('/temperature')
def get_temp():
    temp = sensor.get_temperature()

    # Store in SQLite
    conn = sqlite3.connect('readings.db')
    c = conn.cursor()
    c.execute('INSERT INTO readings VALUES (?, ?)', 
              (time.time(), temp))
    conn.commit()

    return jsonify({'temperature': temp})

if __name__ == '__main__':
    app.run(host='0.0.0.0', port=8080)

With this flare.toml:

[app]
name = "temperature-monitor"
version = "1.0.0"

[build]
command = "pip install -r requirements.txt"

[run]
command = "python sensor.py"
port = 8080

[database]
type = "sqlite"
name = "readings.db"
preseed = "schema.sql"

[health]
url = "http://localhost:8080/temperature"
timeout = 10

Deploy to all Pis at once:

flare deploy my-github/temp-monitor --device all

Technical Details

For the curious, here's what happens under the hood:

Discovery: UDP broadcast on port 7001
Authentication: Argon2 hashed tokens (auto-generated)
Transport: TLS encrypted TCP (self-signed certs)
Protocol: Length-prefixed messages
Isolation: Optional systemd scopes

The stack:

Rust with tokio for async
rustls for TLS
clap for CLI
serde for serialization

Security

Flare generates unique tokens for each device during sync:

// CLI generates random token
let token = generate_random_token();

// Hashes with argon2
let hash = argon2::hash(token);

// Sends hash to daemon
daemon.register(hash);

// Future deploys use this token
deploy_with_token(token);

No passwords to manage, rotatable anytime.

Performance

On a Raspberry Pi Zero W:

Binary size: 10MB
RAM usage: ~20MB idle, ~40MB during deploy
Deploy time: 5-15 seconds depending on repo size
CPU: ~5% idle, ~30% during deploy

Compare to Ansible:

Ansible needs Python (100MB+)
Takes minutes to run playbooks
Requires maintaining inventory files

Current Limitations 📝

Being honest - this is v0.2:

Gateway reverse proxy incomplete (static sites work, APIs coming)
No Windows daemon support yet
Single database per app
Basic health checks

But it works great for my homelab!

Try It!

# Install
cargo install flare-cli flare-daemon
# Or download binaries from GitHub

# Quick test
flared &
flare discover
flare deploy your-github/your-app

GitHub: https://github.com/Velooroo/flare

What's Next?

[ ] Web dashboard
[ ] Multi-database support
[ ] Metrics collection
[ ] Plugin system

Conclusion

Flare solved my "I just want to deploy to Pi" problem. It might not be Kubernetes, but for homelabs and IoT projects, sometimes simple is better.

If you're running a homelab or IoT devices, give it a try! I'd love feedback on what features you'd want.

What's your deployment setup for edge devices? Do you use Ansible, scripts, or something else? Let me know in the comments!

Forem: Kazilsky