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title: "Homemade Kubernetes"
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date: 2025-08-18T10:30:00-03:00
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draft: false
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summary: Why I went with k3s for local homelab.
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---
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tl;dr: wanted to learn k8s properly and wanted some high availability for some services. Also solves loneliness ;)
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---
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I started to have some issues in regards to high availability for some services. I wanted to make sure that my self-hosted applications would remain accessible even if one of my servers went down (like Jellyfin). This led me to explore Kubernetes as a solution.
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As you may or may not know, k8s is a container orchestration platform that automates the deployment, scaling, and management of containerized applications. However it comes with a lot of complexity and operational overhead. I tried to set up a k8s cluster using [k3s](https://k3s.io/), which is a lightweight version of Kubernetes. It seems to be a good starting point, I'm using it since then and has been working wonders so far.
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Currently I'm running them while all config files are on a NFS server, this makes managing configurations easier and backup-ready. For this, I'm using `nfs-subdir-external-provisioner` to manage PVCs through NFS. I have also setup 2 backup cronjobs: one for local servers and another for a remote server.
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## Pros and cons
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Pros that I have noticed:
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* **Easy to set up and manage**: k3s is designed to be lightweight and easy to install
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* **High availability**: if a server goes down, I can still access the services in there
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* I haven't been able to properly set a HA k3s cluster yet as I need more hardware
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* Currently, I'm using a single master-node setup
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* **Backups** are easy to manage if you have all configurations under one place.
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* **Cronjobs** are a breeze to set up and manage, mainly if you need to perform backup rituals.
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* **"Enterprise-grade"** cluster in your home!
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* **Have fun :)**
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Cons:
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* **Complexity**: While k3s simplifies many aspects of Kubernetes, it still requires a certain level of understanding of container orchestration concepts.
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* **Single-point of failure**: In my current setup, the single master node is a potential point of failure. If it goes down, the entire cluster becomes unavailable.
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* This can be solved with a multi-master setup, but it requires additional hardware.
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* **Learning curve**: Kubernetes has a steep learning curve -- which is good for people like me.
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## Current setup
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This is my current (might be outdated) setup:
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* 2 Orange Pi running k3s
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- Each with 4 GB RAM, 4C/4T, 256GB SD card on each.
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* 1 Mini PC
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- 6 GB RAM, 2C/4T, 64GB internal memory + 512GB SD Card
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* Proxmox
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- 32 GB RAM, 6C/12T, 1 TB SSD
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- Currently I run these VMs with k3s:
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- 1 prod-like VM
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- 1 dev-like VM
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- 1 work sandbox VM
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At a tech level, I haven't made my setup / scripts / configurations public yet.
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---
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I believe that everyone should try this at home, be in a dedicated hardware/server or in a VM. It's a great way to learn and experiment with Kubernetes in a controlled environment.
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I'm still running some services on Docker itself, but I'm slowly migrating them to k8s. Some services like DNS and Traefik Reverse Proxy are a bit more complex to set up.
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