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Home Lab Setup Details

Hardware Configuration

Server Specifications

  • Server Model: Custom-built server
  • Processor: Intel i5 7600 (4 cores, 4 threads)
  • RAM: 32GB DDR4 2600MHZ
  • Storage:
  • 1x 256GB SATA SSD for OS
  • 2x 3TB HDDs in LVM pool
  • Network: 1GbE network interface
  • Case: Dell OptiPlex 790
  • Power Supply: 400W
  • Cooling: Air cooling

Network Infrastructure

  • Router: Sunrise Connect box 3 fiber-optic
  • VLANs: Separate networks for management, services, IoT, and guest access
  • Firewall Rules: Granular control over traffic between VLANs

Software Configuration

Operating System

  • Primary OS: Proxmox with Kubernetes (previously TrueNAS SCALE)
  • Kubernetes Version: v1.33 (latest stable release)
  • Deployment Method: OpenTofu (manual deployment without CI/CD)

Storage Configuration

  • File Systems: LVM for main storage pool (previously ZFS)
  • Pool Configuration: 6TB without redundancy
  • Persistent Volumes: Kubernetes PVCs with SMB share access

Virtualization

  • Hypervisor: Proxmox
  • Resource Allocation: Dedicated CPU cores and memory for Kubernetes VM

Container Management

  • Container Platform: Kubernetes (single-node cluster)
  • Deployment Method: Kubernetes manifests with OpenTofu
  • Storage Integration: Local path provisioner for persistent storage
  • Networking: Traefik for ingress

Management & Monitoring

Management Interfaces

  • Primary Interface: k9s CLI tool for PC management
  • Mobile Management: kubenav mobile app
  • SSH Access: Enabled
  • Remote Access: VPN (WireGuard Easy) for secure remote management

Monitoring Solutions

  • System Monitoring: Prometheus + Grafana
  • Service Monitors: Custom service monitors for application metrics
  • Alerting: AlertManager with notifications via email and messaging platforms
  • Performance Metrics: Custom Grafana dashboards for CPU, RAM, network, and disk usage
  • Kubernetes Metrics: Kube State Metrics for cluster health monitoring

Backup Strategy

  • Current Status: No formal backup solution implemented yet
  • Future Plans: Planning to implement Kubernetes-native backup solutions
  • Application Data: Some applications have their own backup mechanisms

Power Management

Power Optimization

  • Sleep States: Configured for optimal power usage
  • Scheduled Tasks: Non-critical tasks during off-peak hours
  • Component Selection: Focus on energy-efficient hardware
  • GPU undervolting: Undervolt GPUs to consume a lot less power but still deliver the same performance

Future Expansion Plans

  • Dedicated GPU for transcoding and AI workloads
  • 10GbE networking upgrade
  • Enhanced security monitoring and intrusion detection
  • More storage and better hardware