Almost Done With My Build

Almost Done With My Build: The Art of Homelab Infrastructure Management

Introduction

The phrase “almost done with my build” resonates deeply with every system administrator and DevOps engineer who’s ever constructed a homelab or self-hosted environment. That tantalizing state of near-completion - with just a few more components to add, cables to shorten, or configurations to optimize - represents both the challenge and allure of infrastructure management.

In today’s DevOps landscape, where cloud-native technologies dominate professional workflows, personal computing clusters remain crucial for hands-on learning, experimentation, and skill development. The Reddit user’s “WRTK8S” build - featuring a mix of GMKtec Nucbox, Raspberry Pi nodes, and PoE networking - exemplifies the modern approach to building flexible, cost-effective infrastructure that bridges the gap between consumer hardware and enterprise-grade systems.

This comprehensive guide will explore:

1. The architecture and design principles behind effective homelab builds
2. Hardware selection strategies balancing performance and power efficiency
3. Cluster management techniques using industry-standard DevOps tools
4. Network configuration for mixed-architecture environments
5. Future-proofing considerations for expanding capabilities

Whether you’re running a Raspberry Pi cluster for Kubernetes experiments or building a hybrid x86/ARM development platform, these infrastructure management principles apply equally to personal labs and production environments.

Understanding Homelab Infrastructure Architecture

The Evolution of Personal Computing Clusters

Homelab infrastructure has evolved dramatically from the single-server setups of the early 2000s. Modern builds like the referenced WRTK8S cluster combine:

• Heterogeneous compute: Mixing x86 mini-PCs (GMKtec Nucbox) with ARM-based Raspberry Pis
• Power-over-Ethernet (PoE): Simplifying power delivery to edge nodes
• NVMe storage: Leveraging PCIe interfaces even on SBCs (Single Board Computers)
• Modular expansion: Planning for future components like eGPUs and KVMs

Hardware Selection Considerations

Component	Considerations	Example from Build
Main Compute	x86 vs ARM, thermal design, I/O ports	GMKtec Nucbox M6
Edge Nodes	Power efficiency, expansion capabilities	Raspberry Pi 4/5 with PoE
Networking	Managed features, PoE budget, throughput	TP-Link 8-port PoE+
Power	Efficiency rating, modular cabling	Planned 250W PSU
Expansion	PCIe bandwidth, compatibility	Planned eGPU/JetKVM

The ARM vs x86 Balance

The Raspberry Pi 5’s NVMe capability (through PCIe 2.0 x1) demonstrates ARM’s growing competitiveness in storage performance:

# Checking NVMe performance on Raspberry Pi 5
sudo hdparm -Tt /dev/nvme0n1

# Sample output:
# Timing cached reads:   1584 MB in  2.00 seconds = 792.43 MB/sec
# Timing buffered disk reads: 742 MB in  3.00 seconds = 247.23 MB/sec

Meanwhile, the GMKtec Nucbox M6 (AMD Ryzen 7 7735HS) provides x86 compatibility for workloads requiring Intel/AMD architecture.

Networking Architecture

The TP-Link PoE+ switch enables both power delivery and network connectivity through a single cable. Key configuration considerations include:

# Typical managed switch configuration for VLAN segmentation
configure terminal
vlan 10
name Servers
vlan 20
name IoT
interface range gigabitEthernet 1/0/1-4
switchport mode access
switchport access vlan 10
interface range gigabitEthernet 1/0/5-8
switchport mode access
switchport access vlan 20
end
write memory

Prerequisites for a Production-Grade Homelab

Hardware Requirements

1. Compute Nodes:
   • Minimum: 4-core CPU, 8GB RAM, Gigabit Ethernet
   • Recommended: 8-core CPU, 16GB+ RAM, 2.5GbE
2. Storage:
   • Boot: 64GB+ SSD/USB 3.0
   • Persistent: NVMe SSD for high-I/O workloads
3. Networking:
   • Managed switch with VLAN support
   • PoE+ (802.3at) for powered devices
   • Minimum 1Gbps backplane

Software Requirements

Component	Minimum Version	Notes
Operating System	Ubuntu 22.04 LTS	ARM64/x86_64 kernel 5.15+
Container Runtime	Docker 24.0	Or containerd 1.7+ for Kubernetes
Orchestration	Kubernetes 1.28	Or Docker Swarm for lighter setups
Provisioning	Ansible 2.15	Infrastructure-as-Code foundation

Security Pre-Checks

1. Physical Security:
   • Disable unused physical ports (USB, HDMI)
   • Enable BIOS/UEFI passwords
   • Implement secure boot where supported
2. Network Security:
   • Change default switch credentials
   • Implement 802.1X port authentication
   • Configure firewall zones (public/private/dmz)

Installation & Configuration Walkthrough

Base Operating System Setup

For ARM devices like Raspberry Pi:

# Raspberry Pi OS Lite 64-bit installation
sudo apt update && sudo apt full-upgrade -y
sudo apt install -y docker.io kubeadm kubelet kubectl
sudo usermod -aG docker $USER

For x86 nodes (GMKtec Nucbox):

# Ubuntu Server 22.04 minimal install
sudo apt update && sudo apt full-upgrade -y
sudo apt install -y \
    docker.io \
    docker-compose-plugin \
    qemu-user-static \
    binfmt-support

Cross-Architecture Container Support

Enable multi-arch builds on x86 host:

# Register ARM containers on x86 host
docker run --privileged --rm tonistiigi/binfmt --install arm64

Kubernetes Cluster Initialization

On the control plane node (GMKtec Nucbox):

sudo kubeadm init --pod-network-cidr=10.244.0.0/16 \
    --apiserver-advertise-address=192.168.1.100 \
    --control-plane-endpoint=cluster.local

On worker nodes (Raspberry Pi 4/5):

sudo kubeadm join 192.168.1.100:6443 --token <token> \
    --discovery-token-ca-cert-hash <hash>

Persistent Storage Configuration

Create an NVMe storage class for Raspberry Pi 5 nodes:

# nvme-sc.yaml
apiVersion: storage.k8s.io/v1
kind: StorageClass
metadata:
  name: nvme-ssd
provisioner: kubernetes.io/no-provisioner
volumeBindingMode: WaitForFirstConsumer

Configuration & Optimization Techniques

Network Performance Tuning

For Raspberry Pi PoE setups:

# Enable NIC offloading
sudo ethtool -K eth0 tx-checksum-ip-generic on
sudo ethtool -C eth0 rx-usecs 100

# Optimize TCP stack
sudo sysctl -w net.core.rmem_max=268435456
sudo sysctl -w net.core.wmem_max=268435456
sudo sysctl -w net.ipv4.tcp_fastopen=3

Thermal Management

Create a systemd service for fan control:

# /etc/systemd/system/fan-control.service
[Unit]
Description=Raspberry Pi Fan Control
After=multi-user.target

[Service]
Type=simple
ExecStart=/usr/bin/python3 /usr/local/bin/fan_control.py
Restart=always

[Install]
WantedBy=multi-user.target

With accompanying Python script:

# fan_control.py
import RPi.GPIO as GPIO
import time

FAN_PIN = 18
TEMP_THRESHOLD = 55  # Celsius

GPIO.setmode(GPIO.BCM)
GPIO.setup(FAN_PIN, GPIO.OUT)

try:
    while True:
        temp = float(open('/sys/class/thermal/thermal_zone0/temp').read()) / 1000
        if temp > TEMP_THRESHOLD:
            GPIO.output(FAN_PIN, True)
        else:
            GPIO.output(FAN_PIN, False)
        time.sleep(30)
finally:
    GPIO.cleanup()

Security Hardening

1. Container Runtime Security:

   # Create Docker daemon.json with security settings
   {
     "userns-remap": "default",
     "no-new-privileges": true,
     "iptables": true,
     "live-restore": true,
     "log-driver": "json-file",
     "log-opts": {
       "max-size": "10m",
       "max-file": "3"
     }
   }
   

2. Kubernetes Pod Security: ```yaml

   psa.yaml

   apiVersion: apiserver.config.k8s.io/v1 kind: AdmissionConfiguration plugins:

   • name: PodSecurity configuration: apiVersion: pod-security.admission.config.k8s.io/v1 kind: PodSecurityConfiguration defaults: enforce: “restricted” enforce-version: “latest” exemptions: usernames: [“system:serviceaccount:kube-system:calico-node”] ```

Day-to-Day Operations

Monitoring Mixed-Architecture Clusters

Prometheus configuration snippet for heterogeneous nodes:

# prometheus.yml
scrape_configs:
  - job_name: 'node'
    static_configs:
      - targets: ['amd64-node:9100', 'pi4-node:9100', 'pi5-node:9100']
    relabel_configs:
      - source_labels: [__address__]
        target_label: __scheme__
        replacement: https
      - source_labels: [__meta_kubernetes_pod_node_name]
        target_label: node

Backup Strategy

Versioned backups using Restic and systemd timers:

# /etc/systemd/system/backup.service
[Unit]
Description=Filesystem Backup
Requires=network-online.target
After=network-online.target

[Service]
Type=oneshot
ExecStart=/usr/bin/restic backup /var/lib/docker/volumes \
    --exclude="*.tmp" \
    --tag docker-volumes
ExecStartPost=/usr/bin/restic forget \
    --keep-daily 7 \
    --keep-weekly 4 \
    --keep-monthly 12

Container Management Commands

Using Docker with safe variable names:

# List containers with formatted output
docker ps --format "table $CONTAINER_ID\t$CONTAINER_IMAGE\t$CONTAINER_STATUS\t$CONTAINER_PORTS"

# Inspect container resource usage
docker stats --format "table $CONTAINER_NAMES\t$CONTAINER_CPU\t$CONTAINER_MEM"

# Cleanup unused containers
docker container prune --filter "until=24h"

Troubleshooting Common Issues

Cross-Architecture Build Failures

Symptoms: exec format error when running ARM containers on x86 hosts

Solution: Verify QEMU static binary support:

# Check binfmt_misc registrations
ls /proc/sys/fs/binfmt_misc/

# Re-register ARM interpreters
docker run --privileged --rm tonistiigi/binfmt --install arm64,arm

PoE Power Budget Exceeded

Diagnosis: Switch logs show power-overload events

Calculation:

• Raspberry Pi 4 + PoE Hat: 15W max
• Raspberry Pi 5 + NVMe + PoE: 20W max
• Total required: (2×15W) + (2×20W) = 70W
• TP-Link PoE+ switch (TL-SG1008P): 123W budget

Mitigation: Ensure firmware updated for optimal power management

Thermal Throttling

Diagnostic commands:

# Raspberry Pi thermal status
vcgencmd measure_temp
vcgencmd get_throttled

# x86 temperature monitoring
sudo apt install lm-sensors
sensors

Resolution: Implement active cooling or reduce CPU governor aggressiveness:

sudo cpufreq-set -g powersave

Conclusion

Building and maintaining a heterogeneous homelab like the WRTK8S cluster demonstrates essential DevOps principles: infrastructure-as-code, automated provisioning, monitoring-driven operations, and security-by-design. This guide has covered the full lifecycle from hardware selection to day-to-day operations, emphasizing practical techniques for managing mixed-architecture environments.

Key takeaways:

1. Strategic Hardware Selection: Balance x86 performance with ARM efficiency
2. Unified Management: Use tools like Ansible and Kubernetes across architectures
3. Observability: Implement metrics collection tailored to heterogeneous nodes
4. Security: Apply defense-in-depth from hardware to application layer
5. Scalability: Design for incremental expansion with PoE and modular components

For those continuing their homelab journey, consider exploring:

• GPU Acceleration: Integrating eGPUs for machine learning workloads
• Edge Computing: Deploying cluster nodes across physical locations
• Energy Monitoring: Implementing real-time power usage metrics
• Bare-Metal Kubernetes: Projects like Talos Linux for immutable infrastructure

Further resources:

• Official Kubernetes Documentation on Heterogeneous Clusters
• Raspberry Pi PCIe Interface Documentation
• Docker Multi-Platform Build Documentation

The state of being “almost done” with your build isn’t an endpoint - it’s an acknowledgement that infrastructure is living architecture, continually evolving to meet new challenges.