When I started building my home lab, the Raspberry Pi 4B (4B) was my muse to self-host apps, test new tools, and try out Docker containers. But, when containers kept crashing, I opted for a mini PC as my home lab server, as I wanted a reliable method to track performance, spot issues early, and troubleshoot them with sufficient details.

That’s how I slowly built a stack of these Docker containers, which I use to monitor, track, troubleshoot, and optimize my entire home lab.

Portainer

Manage containerized services with an intuitive web GUI

Portainer is the easiest way to manage and troubleshoot Docker if you’re still getting familiar with containerized services. Even though I’ve grown to like Dockge over time, I still find myself going back to Portainer because of its cleaner UI and app deployments with a few clicks. It also helps me experiment with resource limits, volumes, and networks without using CLI to bring containers down and back up. As I expand my home lab, Portainer will continue to play as the central control panel for other containers and across multiple servers.

Beszel

Get a straightforward overview of system resources

Beszel has been a game-changer, offering a simple and clean approach that makes it my must-have monitoring tool. Its minimal interface provides a glance at my home server, the VMs running on it, and the self-hosted servers and containers. Its multi-platform capabilities make it a convenient option to monitor even my desktop and laptop. Thanks to Beszel, I learned how easily my M1 MacBook Air with 8GB of RAM can get overwhelmed when running multiple Docker containers.

Uptime Kuma

Monitoring the self-hosted apps and services

If my Immich, Firefly III, or Mealie containers stop responding, Uptime Kuma is the first place I check. That gives me a fair idea of what's going on with my services and apps. It supports HTTP(S), DNS, TCP, ping, Docker containers, and more, making it a solid alarm system for my self-hosted services. I often refer to it to notify me whenever critical servers on my home network, such as my router, go down. I no longer wait for someone from my family to tell me that Immich or Home Assistant isn’t working. The real-time alerts and their uptime history help me troubleshoot services faster.

Netdata

Deep-diving with real-time system metrics

When I deploy a new container or project, I refer to Netdata’s metrics, which offer a second-by-second view through various dashboards. That’s how I understand the impact of deployment through real-time updates on CPU, memory, disk, and network usage. Whenever something feels off, Netdata's visualizations help me troubleshoot and resolve the issue. Spinning it up in Docker is straightforward, and I can use it locally, without signing up for its cloud service. Netdata performs best on x86 hardware with decent memory. At least, that's what I experienced. It struggled on my Raspberry Pi 4B (4GB), I run it only on my home server to let it capture node metrics without compromise.

Pi-hole

Monitoring the LAN network and IoT devices

In my home lab, Pi-hole serves as more than an ad blocker. It’s an excellent container for monitoring the behavior of different machines, especially IoT devices. After spinning up the container, I was shocked to discover how chatty the cheap IoT gadgets were and tried to reach out to questionable domains. Smart TVs and smart speakers were top-tier offenders. Pi-hole logs network activity across the network and pairs well with Unbound. That’s how I use it for recursive DNS resolution without third-party snooping.

Dozzle

Beautiful view of container logs

Dozzle completely changed how I deal with Docker container logs. No more juggling between multiple Terminal windows to view container logs. Dozzle streams container logs in real time. That has helped me spot misconfiguration issues, especially with the databases. The search and filter functions have saved me countless hours and helped me learn from my past mistakes when writing Docker Compose files. It may seem simple, but it helps container management run more efficiently across multiple hosts.

Prometheus and Grafana

Long-term metrics and actionable dashboards

Beszel, Uptime Kuma, and Netdata handle my daily monitoring needs. That said, I rely on Prometheus and Grafana dashboards to view long-term history. As my home lab grows, I leverage those detailed dashboards and numbers to make data-driven decisions based on actual usage patterns. For instance, that data helped me decide to add a dual-port NIC to my Windows 11 PC rather than my home server. The memory usage graphs, which consistently showed memory reaching its limit, made it evident that my mini PC needed a RAM upgrade. Of course, I tried Zabbix, but it felt overkill for my home lab setup.

A monitoring stack that scales with my needs

After spending a lot of time building my home lab, I realized that it takes more than just deploying containers and virtual machines. These Docker containers play specific roles, ranging from tracking resources and visualizing data to performing log inspections. From keeping an eye on resource spikes to discovering the crashes caused by my YAML indentation errors, I get to learn while I experiment and level up my home lab. Of course, this stack evolves as I get more comfortable breaking things fearlessly.

For convenience, I have pinned the web UI addresses of these containers to my Heimdall dashboard. The insights these containers collectively provide help me experiment efficiently and make smarter upgrades to my home lab.