Planning

Resource Planning My five node cluster currently consists of: Three control plane nodes (cp1, cp2 and cp3: 16GB ram Raspberry Pi 5s): all running Raspberry Pi OS (Debian 13) in headless mode so are lightweight and Pi optimised. Etcd requires the most RAM (3GB for small clusters like mine with <100 pods), while other components should typically stay under 1GB each (with Prometheus at roughly 3gb as an exception) with my multi-node control plane set up which distributes load, so 16GB handles 20-50 pods across nodes without OOM issues. Two worker nodes (wn1, wn2), one runs Debian and the other Ubuntu. I have mixed 8GB and 36GB worker nodes which work fine for my Kubernetes homelab, as schedulers automatically balance pods based on allocatable resources (node taints/labels also help). 8GB should handle 20-40 pods (e.g., Prometheus targets, Home Assistant), while 36GB can take heavier workloads like databases or future AI experiments without OOM issues.​ ...