Installation Guide

Prerequisites

graph TD
    subgraph Hardware
        CP[Control Plane Nodes]
        GPU[GPU Worker Node]
        Worker[Worker Nodes]
    end

    subgraph Software
        OS[Operating System]
        Tools[Required Tools]
        Network[Network Setup]
    end

    subgraph Configuration
        Git[Git Repository]
        Secrets[SOPS Setup]
        Certs[Certificates]
    end

Hardware Requirements

Control Plane Nodes (3x)

  • CPU: 4 cores per node
  • RAM: 16GB per node
  • Role: Cluster control plane

GPU Worker Node (1x)

  • CPU: 16 cores
  • RAM: 128GB
  • GPU: 4x NVIDIA Tesla P100
  • Role: GPU-accelerated workloads

Worker Nodes (2x)

  • CPU: 16 cores per node
  • RAM: 128GB per node
  • Role: General workloads

Software Prerequisites

  1. Operating System

    • Linux distribution
    • Updated system packages
    • Required kernel modules
    • NVIDIA drivers (for GPU node)

  2. Required Tools

    • kubectl
    • flux
    • SOPS
    • age/gpg
    • task

Initial Setup

1. Repository Setup

# Clone the repository
git clone https://github.com/username/dapper-cluster.git
cd dapper-cluster

# Create configuration
cp config.sample.yaml config.yaml

2. Configuration

graph LR
    Config[Configuration] --> Secrets[Secrets Management]
    Config --> Network[Network Settings]
    Config --> Storage[Storage Setup]
    Secrets --> SOPS[SOPS Encryption]
    Network --> DNS[DNS Setup]
    Storage --> CSI[CSI Drivers]

Edit Configuration

cluster:
  name: dapper-cluster
  domain: example.com

network:
  cidr: 10.0.0.0/16

storage:
  nfs:
    server: nfs.example.com
    path: /export/nfs

3. Secrets Management

  • Generate age key
  • Configure SOPS
  • Encrypt sensitive files

4. Bootstrap Process

graph TD
    Start[Start Installation] --> CP[Bootstrap Control Plane]
    CP --> Workers[Join Worker Nodes]
    Workers --> GPU[Configure GPU Node]
    GPU --> Flux[Install Flux]
    Flux --> Apps[Deploy Apps]

Bootstrap Commands

# Initialize flux
task flux:bootstrap

# Verify installation
task cluster:verify

# Verify GPU support
kubectl get nodes -o wide
nvidia-smi # on GPU node

Post-Installation

1. Verify Components

  • Check control plane health
  • Verify worker node status
  • Test GPU functionality
  • Check storage provisioners
  • Verify network connectivity

2. Deploy Applications

  • Deploy core services
  • Configure monitoring
  • Setup backup systems
  • Deploy GPU-enabled workloads

3. Security Setup

  • Configure network policies
  • Setup certificate management
  • Enable monitoring and alerts
  • Secure GPU access

Troubleshooting

Common installation issues and solutions:

  1. Control Plane Issues

    • Verify etcd cluster health
    • Check control plane components
    • Review system logs

  2. Worker Node Issues

    • Verify node join process
    • Check kubelet status
    • Review node logs

  3. GPU Node Issues

    • Verify NVIDIA driver installation
    • Check NVIDIA container runtime
    • Validate GPU visibility in cluster

  4. Storage Issues

    • Verify NFS connectivity
    • Check storage class configuration
    • Review PV/PVC status

  5. Network Problems

    • Check DNS resolution
    • Verify network policies
    • Review ingress configuration

Maintenance

Regular Tasks

  1. System updates
  2. Certificate renewal
  3. Backup verification
  4. Security audits
  5. GPU driver updates

Health Checks

  • Component status
  • Resource usage
  • Storage capacity
  • Network connectivity
  • GPU health

Next Steps

After successful installation:

  1. Review Architecture Overview
  2. Configure Storage
  3. Setup Network
  4. Deploy Applications