🧪 A lightweight eMMC wear monitoring dashboard for early GPD Pocket (eMMC models)
Designed for low write amplification, long-term observation, and experimental use.
This project is primarily tested on early GPD Pocket models with eMMC storage.
Newer GPD devices may use:
- NVMe SSD
- Different eMMC controllers
- Different block device paths
Before deployment, verify your device path:
lsblkIf your storage device is not mmcblk0, adjust accordingly (e.g. /sys/block/nvme0n1/stat).
Build a minimal-impact eMMC monitoring service:
- Ultra-low disk writes
- Simple architecture
- Long-term safe logging
- Web-based visualization (Chart.js)
- No heavy monitoring stack
Perfect for:
- Experimental Linux setups
- Small home servers
- Embedded devices
- Always-on lab machines
Every 5 minutes:
Read /sys/block/mmcblk0/stat
↓
Append 1 line to log file
↓
Web page reads log
↓
Chart.js renders graph
| Period | Log Size |
|---|---|
| Daily | 288 lines |
| Yearly | ~100 KB |
| 5 Years | ~500 KB |
Negligible impact on eMMC lifespan.
- Nginx
- Python3 (CGI via fcgiwrap)
- Chart.js
- Cron
No database required.
nano ~/mmc_logger.sh#!/bin/bash
LOGFILE="/var/log/mmc_stat.log"
TS=$(date +%s)
STAT=$(cat /sys/block/mmcblk0/stat)
WRITE_SECTORS=$(echo $STAT | awk '{print $7}')
echo "$TS $WRITE_SECTORS" >> $LOGFILEMake it executable:
chmod +x ~/mmc_logger.shcrontab -eAdd:
*/5 * * * * /home/youruser/mmc_logger.sh✔ 288 writes per day
✔ Extremely low wear
sudo apt update
sudo apt install nginx fcgiwrapsudo nano /var/www/html/mmc.html<!DOCTYPE html>
<html>
<head>
<title>GPD eMMC Monitor</title>
<script src="https://cdn.jsdelivr.net/npm/chart.js"></script>
</head>
<body>
<h2>eMMC Total Writes (GB)</h2>
<canvas id="mmcChart"></canvas>
<script>
fetch('/mmc_data')
.then(response => response.json())
.then(data => {
const labels = data.map(d => new Date(d.time * 1000).toLocaleString());
const values = data.map(d => d.gb);
new Chart(document.getElementById('mmcChart'), {
type: 'line',
data: {
labels: labels,
datasets: [{
label: 'Total Written GB',
data: values,
fill: false,
tension: 0.1
}]
}
});
});
</script>
</body>
</html>sudo nano /usr/local/bin/mmc_json.py#!/usr/bin/env python3
import json
data = []
with open("/var/log/mmc_stat.log") as f:
lines = f.readlines()
for line in lines:
ts, sectors = line.strip().split()
sectors = int(sectors)
gb = sectors * 512 / (1024**3)
data.append({"time": int(ts), "gb": round(gb,2)})
print("Content-Type: application/json\n")
print(json.dumps(data))Make executable:
sudo chmod +x /usr/local/bin/mmc_json.pyEdit:
sudo nano /etc/nginx/sites-enabled/defaultInside server {} add:
location /mmc_data {
include fastcgi_params;
fastcgi_pass unix:/run/fcgiwrap.socket;
fastcgi_param SCRIPT_FILENAME /usr/local/bin/mmc_json.py;
}Restart:
sudo systemctl restart nginxOpen:
http://YOUR_IP/mmc.html
You will see:
- Total written GB
- Growth trend
- Write velocity changes
- Abnormal spikes detection
From:
/sys/block/mmcblk0/stat
Field 7:
Write sectors
Formula:
Bytes written = sectors × 512
Displayed value:
Total written GB
Assume eMMC rated TBW:
80 TB
Calculation:
Current Written / 80 TB = Used %
Remaining = 100% - Used
Safe target:
- < 10 TB per year
- < 50 TB in 5 years
- Switch cron → systemd timer
- Add logrotate
- Add daily delta calculation
- Add projected lifespan curve
- Improve UI to dashboard style
- Add NVMe support auto-detection
Many lightweight devices (like early GPD Pocket) use eMMC with limited TBW.
This tool provides:
✔ Visibility
✔ Trend awareness
✔ Early anomaly detection
✔ Peace of mind
MIT (or choose your preferred license)
This project is intentionally simple.
No Prometheus.
No database.
No heavy monitoring stack.
Just a clean, long-running, low-impact wear dashboard.
Your eMMC deserves transparency.