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

Source: Dev.to

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 I had to run commands like:

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 felt too heavy, Docker Swarm was overkill for three 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

How It Works

1. Start daemon on your Pi

# On Raspberry Pi
flared
# Listening on :7530

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 repository:

[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

Sensor code (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)

Corresponding 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

• 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

Stack: Rust with Tokio for async, rustls for TLS, clap for CLI, serde for serialization.

Security

Flare generates a unique token 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; tokens can be rotated anytime.

Performance

On a Raspberry Pi Zero W:

• Binary size: ~10 MB
• RAM usage: ~20 MB idle, ~40 MB during deploy
• Deploy time: 5–15 seconds (repo size dependent)
• CPU: ~5 % idle, ~30 % during deploy

Compared to Ansible:

• Ansible requires Python (100 MB+) and takes minutes to run playbooks, plus inventory maintenance.

Current Limitations 📝

• v0.2 status
• Gateway reverse proxy incomplete (static sites work, APIs coming)
• No Windows daemon support yet
• Single database per app
• Basic health checks only

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:

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 isn’t Kubernetes, but for homelabs and IoT projects, simplicity often wins.

If you’re running a homelab or edge devices, give it a try and share your feedback!