Self-Hosting
How to run your own servers, Docker stacks, and self-hosted services without losing weekends to config files.
Containerize Your Entire Dev Environment with Distrobox: A Complete Guide
Want to test a build on Ubuntu 24.04 while running Arch? Want CUDA 12.x on a stable Debian host without touching the host drivers? Want six Node.js versions that don’t fight each other? Distrobox is the shortest path there. It’s a POSIX shell wrapper around Podman , Docker , or Lilipod . The containers feel like native shells, and they run just as smoothly inside a terminal built for instant redraws as on a plain console. Your home directory, Wayland socket, GPU, SSH keys, Git config, and audio all wire in for you. GUI apps you install inside show up in the host menu.
sched_ext: Write a Custom Linux Kernel Scheduler in eBPF
sched_ext (SCX) is a Linux kernel framework that lets you implement CPU schedulers in eBPF and hot-swap them at runtime without rebooting or recompiling the kernel. It merged into mainline in Linux 6.12 and matured through 7.0, which tightened its interaction with the default EEVDF class. On any distro shipping a kernel with CONFIG_SCHED_CLASS_EXT=y, loading a new scheduler takes a single command, for example sudo scx_loader --start scx_lavd, and you confirm it is active by reading /sys/kernel/sched_ext/root/ops.
Systemd Services from Scratch: Write, Enable, and Debug Custom Unit Files
Build a solid systemd
service by writing a .service unit file in /etc/systemd/system/ with [Unit], [Service], and [Install] sections, then enable it with systemctl enable --now. Add resource caps, security sandboxing, and auto-restart so the service stays up. Then use journalctl and systemd-analyze security to debug it. Systemd v260 is the current stable release, and it ships on every major distro.
Why Systemd Unit Files Beat Init Scripts
Many developers still write shell wrapper scripts to run their apps. A 30-line bash script juggles PID files, log setup, restarts, and privilege drops. That’s a lot of code just to keep one process alive. A systemd unit file replaces all of it with a short, declarative config, often under 20 lines.
COSMIC Desktop 1.0: One Month of Daily Driving System76's Rust DE
Thirty days of COSMIC Desktop
1.0 on Pop!_OS 24.04 LTS, and I am keeping it. Switch if you are a keyboard-first developer who wants a real tiling-plus-floating hybrid, appreciates Rust-grade stability, and likes a UI that sits under 900 MB at idle. Wait a release or two if you depend on a big GNOME extension collection, niche input methods (CJK/IBus edge cases), or a heavy accessibility stack. The COSMIC Store’s catalog is still smaller than Flathub’s GNOME Circle or the KDE offerings, and only a handful of third-party cosmic-ext-* applets exist in 2026. Everyone else should at least boot the live ISO before deciding. COSMIC 1.0 is the first new Linux desktop in a decade that does not feel like a fork of something older.
n8n and Ollama Local AI: 0ドル/Month, Honest Hardware Math
Running private n8n and Ollama AI automations at home costs 0ドル/month in software, but the hardware bill is real. The honest anchor: a used 64GB Mac Studio near EUR1,995 can replace a 90ドル to 125ドル monthly cloud bill, yet local tool-calling stays broken until you raise Ollama’s default num_ctx from 2048 to 8192.
Key Takeaways
- “0ドル/month” covers software only. The hardware and electricity are still real costs.
- Dockerized n8n reaches Ollama at host.docker.internal:11434, never localhost.
- Ollama’s 2048 context default cuts off tool results. Raise it to 8192.
- qwen2.5:14b is the most reliable local model for the AI Agent node.
- Once set up, a local n8n stack runs for months without babysitting.
What is the n8n and Ollama local AI stack?
Ollama is the local engine that runs language models on your own machine. It serves them over port 11434, so anything on your network can send prompts to it. The same engine powers other local builds, like an Ollama-driven terminal assistant wired into shell scripts. n8n is the workflow orchestrator. It has over 400 integrations and dedicated AI nodes, so you can chain a model into real automations.
Komodo vs Portainer vs Dockge: A 2026 Homelab Decision Guide
Pick Komodo for Git-driven deploys across many Docker servers from one screen. Choose Portainer if you run Kubernetes, which Komodo does not support. Pick Dockge for a single lightweight host. Komodo added a dedicated Docker Swarm resource in 2026, closing what used to be the single most-cited reason people held off, a complaint that once drew 168 votes on Reddit.
Key Takeaways
- Komodo wins on Git-driven deploys across many servers from one screen.
- Portainer stays ahead for Kubernetes and mature production tooling.
- Dockge is the lightest pick if you run a single host.
- Komodo now manages Docker Swarm; Kubernetes is the remaining orchestration gap.
- Komodo’s default VPS setup is insecure until you lock the agent port.
What is Komodo and what problem does it solve?
Komodo is an open-source tool that builds and deploys Docker software across many servers from one place. It is licensed under GPL-3.0 and written in Rust and TypeScript. The project lives at moghtech/komodo and was renamed from “Monitor” before the rebrand.