Dapper Cluster Documentation

This documentation covers the architecture, configuration, and operations of the Dapper Kubernetes cluster, a high-performance home lab infrastructure with GPU capabilities.

Cluster Overview

graph TD
    subgraph Control Plane
        CP1[Control Plane 1<br>4 CPU, 16GB]
        CP2[Control Plane 2<br>4 CPU, 16GB]
        CP3[Control Plane 3<br>4 CPU, 16GB]
    end

    subgraph Worker Nodes
        W1[Worker 1<br>16 CPU, 128GB]
        W2[Worker 2<br>16 CPU, 128GB]
        GPU[GPU Node<br>16 CPU, 128GB<br>4x Tesla P100]
    end

    CP1 --- CP2
    CP2 --- CP3
    CP3 --- CP1

    Control Plane --> Worker Nodes

Hardware Specifications

Control Plane

  • 3 nodes for high availability
  • 4 CPU cores per node
  • 16GB RAM per node
  • Dedicated to cluster control plane operations

Worker Nodes

  • 2 general-purpose worker nodes
  • 16 CPU cores per node
  • 128GB RAM per node
  • Handles general workloads and applications

GPU Node

  • Specialized GPU worker node
  • 16 CPU cores
  • 128GB RAM
  • 4x NVIDIA Tesla P100 GPUs
  • Handles ML/AI and GPU-accelerated workloads

Key Features

  • High-availability Kubernetes cluster
  • GPU acceleration support
  • Automated deployment using Flux CD
  • Secure secrets management with SOPS
  • NFS and OpenEBS storage integration
  • Comprehensive monitoring and observability
  • Media services automation

Infrastructure Components

graph TD
    subgraph Core Services
        Flux[Flux CD]
        Storage[Storage Layer]
        Network[Network Layer]
    end

    subgraph Applications
        Media[Media Stack]
        Monitor[Monitoring]
        GPU[GPU Workloads]
    end

    Core Services --> Applications

    Storage --> |NFS/OpenEBS| Applications
    Network --> |Ingress/DNS| Applications

Documentation Structure

  • Architecture: Detailed technical documentation about cluster design and components

    • High-availability control plane design
    • Storage architecture and configuration
    • Network topology and policies
    • GPU integration and management

  • Applications: Information about deployed applications and their configurations

    • Media services stack
    • Monitoring and observability
    • GPU-accelerated applications

  • Operations: Guides for installation, maintenance, and troubleshooting

    • Cluster setup procedures
    • Node management
    • GPU configuration
    • Maintenance tasks

Getting Started

For new users, we recommend starting with:

  1. Architecture Overview - Understanding the cluster design
  2. Installation Guide - Setting up the cluster
  3. Application Stack - Deploying applications