This is a personal blog focused on computer software and hardware. Most projects are implementing software and hardware for a homelab. What is a homelab? I would say a homelab could be a single computer or dozens of computers connected in a network. You can also integrate with computers in the Cloud.
New disclaimer I am adding: I used an LLM to help create this post but afterwards I spent more than an hour editing it to the final form.
This tool n8n allows you to build automated workflows with AI agents through a “node” based UI in the web. It also has a REST API and you can define the workflows in JSON. We can configure webhooks to allow systems to trigger workflows in n8n.
Prometheus installations may eventually run into scale limits such as short retention windows or high state cardinality costs. VictoriaMetrics provides a compact time-series database that accepts Prometheus remote write traffic and exposes the same query APIs. This post walks through deploying the single-node container (via docker run or Docker Compose), wiring it into an existing Prometheus and Grafana stack, and highlighting the trade-offs you should validate before production use.
I will be deploying this in my homelab with Docker Compose. There are other installation methods and always consult the official documentation for the latest guidance on installing VictoriaMetrics. If you are not familiar with Docker or containers, check out a previous post to get started.
This post was written by a human but here is an AI generated glossary for the terms I throw around.
LLM (Large Language Model)
A type of artificial intelligence model trained on vast amounts of text data to understand and generate human-like language. LLMs power tools like ChatGPT, enabling tasks such as answering questions, summarizing, and writing code.
MCP (Model Context Protocol)
An emerging protocol that standardizes how AI models communicate with external tools, applications, and data sources. MCP allows an AI system to extend its abilities by connecting to different services in a structured and secure way.
If you are not familiar with Grafana Loki, it is an open-source system for aggregating application, system, and other log files for querying and potentially configuring alert notifications when something goes wrong. Check out a previous post where I set up Loki in my homelab.
There are multiple ways to install Grafana Loki. I have in the past run it on a Debian based Linux VM. While building a new server for my logs and metrics, I spun up Loki as a Docker container on my Mac Mini. It is very straightforward to set up a single container for Grafana Loki using Docker Compose, the container includes a default config file for running local. If you are not familiar with Docker or containers, check out a previous post to get started.
Home Assistant is an open source tool for managing IoT/smart home devices on your network and also cloud based home services. You can create automated workflows using this software such as turning on lights when something happens or turning off all lights when you leave home.
I have used Home Assistant on and off for over 5 years. It supports all of my smart home gadgets ranging from light bulbs to bluetooth sensors. I have chosen not to integrate any of my locks, doors, or security system even though it supports them. I just do not like the idea of a compromised software that can unlock my house and open my garage.
In my homelab, Proxmox is the main operating system that I use for servers. It is Debian Linux with some extra packages related to virtual machines and managing virtual machines. If you are not using Proxmox, I recommend checking out a previous post that introduces Proxmox and how to install it.
I am performing an in-place upgrade of a Proxmox VE 8.x node to 9.x.
If you are following along, before you begin, create a verified backup of all your VMs and containers. An upgrade failure without a backup can result in data loss.