gitea-migration/setup/pi-monitoring

Pi Monitoring Stack

Purpose: turn a Raspberry Pi 4 (8GB) into a low-power monitoring/control plane for your Gitea migration environment.

This module deploys:

• Portainer (single admin view)
• Grafana (dashboards)
• Prometheus (metrics)
• Uptime Kuma (service checks)
• Node Exporter + cAdvisor (Pi host + container metrics)

Folder Contents

• bootstrap_pi.sh: first-time host prep (packages, Docker, firewall, hardening)
• mount_ssd.sh: format/mount SSD and create persistent data paths
• deploy_stack.sh: deploy monitoring stack with Docker Compose
• upgrade_stack.sh: pull new images and recreate stack
• backup_stack.sh: backup stack data/config to OPS_ROOT/backups
• restore_stack.sh: restore from backup archive
• status.sh: show service status and endpoint reachability
• teardown_stack.sh: stop/remove stack; optionally delete stack data
• install_portainer_agent_remote.sh: install Portainer Agent on Fedora/Unraid
• docker-compose.yml: stack definition
• stack.env.example: environment template
• prometheus/prometheus.yml: Prometheus config
• USAGE_GUIDE.md: full setup and operations guide

Quick Start

Run on the Raspberry Pi host:

cd /path/to/gitea-migration/setup/pi-monitoring

./bootstrap_pi.sh --yes
./mount_ssd.sh --device=/dev/sda1 --yes

cp stack.env.example stack.env
# edit stack.env and set a strong GRAFANA_ADMIN_PASSWORD

./deploy_stack.sh --yes
./status.sh

Then from your admin machine, install Portainer agent on remote Docker hosts:

./install_portainer_agent_remote.sh --host=<unraid-ip> --user=<unraid-user> --port=22 --yes
./install_portainer_agent_remote.sh --host=<fedora-ip> --user=<fedora-user> --port=22 --yes

In Portainer UI (https://<pi-ip>:9443), add environments using:

• tcp://<unraid-ip>:9001
• tcp://<fedora-ip>:9001

Security Notes

• stack.env contains secrets; do not commit it.
• Portainer Agent exposes Docker control on 9001; keep it inside trusted LAN/VPN.
• Keep UFW enabled and only expose required ports.
• Use SSD for durability; avoid long-term DB workloads on SD card.