Technology Lab

An enterprise-grade infrastructure environment built to evaluate emerging technologies , including AI-augmented operations, infrastructure automation, and open-source alternatives to commercial platforms.


Why Build a Lab?

Most IT executives talk about emerging technology. I build with it. When my CIO asked how AI could improve IT operations, I didn’t write a whitepaper. I built a complete enterprise environment to evaluate the concept firsthand. Before recommending AI integration for a production enterprise environment, I needed to understand the failure modes, security implications, and governance requirements.

The result is a working methodology , and a clear understanding of both the potential and the limitations , that I can bring to any organization on day one.


The Numbers

5 Nodes

Hyperconverged cluster
320 GB RAM, 80 cores, 10 TB NVMe

65 Hosts

Monitored endpoints with automated alerting and 8 operational dashboards

8 API Servers

Custom integration servers with 336+ tools for unified infrastructure management

$240/yr

Total software cost replacing $75K–$109K in commercial equivalents


Case Studies

Detailed examinations of how this platform delivers measurable results:

Enterprise Infrastructure Management Platform

8 custom API integration servers, 336 tools, 48 tracked sessions measuring a 7-10x productivity improvement , the complete architecture, implementation, and measured business case for AI-augmented IT operations.


What I Built

Hyperconverged Infrastructure

A 5-node Proxmox VE cluster with live migration, shared NFS storage, and N+2 fault tolerance , demonstrating enterprise virtualization at $0 software licensing cost. 15 virtual machines run the complete operational stack. Read the full cost analysis →

API-First Operations Platform

8 custom Model Context Protocol (MCP) servers providing 336+ API tools that enable unified infrastructure management through natural language. This isn’t chatbot automation , it’s a unified operations platform where AI can query NetBox for asset data, deploy configurations via Ansible, manage firewall rules in pfSense, create documentation in MediaWiki, and monitor services through Naemon , all in a single conversation. How the API architecture works →

Event-Driven Automation Pipeline

Event-driven automation architecture showing webhook-triggered Ansible deployment from NetBox to Naemon monitoring
When a device is updated in NetBox, a webhook triggers Ansible to regenerate and deploy monitoring configuration automatically , typically completing in under 5 seconds.

Full-Stack Observability

Naemon monitoring across 65 endpoints with automated alerting, plus Loki/Grafana centralized logging covering 13 hosts and 12 Docker containers with 8 operational dashboards and 30-day retention. The entire monitoring stack was deployed and configured using automation and infrastructure-as-code methodology. How I automated monitoring for 65 hosts → | Loki vs Splunk comparison →

Zero-Trust Security Architecture

Network Access Control with automated device quarantine, NAC policy enforcement via custom Ansible collection (4 modules, 2 roles), VLAN segmentation across 5 security zones, centralized secrets management via Vaultwarden, and pfSense firewall with granular rule management. Full NAC architecture deep dive →

Infrastructure as Code

Ansible automation managing 16 hosts with a custom UniFi Ansible Collection for network device configuration. Every configuration change is repeatable, auditable, and version-controlled.

Operational Governance

50+ documentation pages, 8 standard operating procedures, formal project tracking (24 projects, 88 tasks), device naming standards, credential migration standards, and self-maintaining documentation with automated staleness detection. What 48 tracked sessions taught me about governance →


What I’d Do Differently in Production

A lab environment is intentionally permissive. Here’s what changes in an enterprise deployment:

  • Governance first: Formal change management, approval workflows, and audit trails before any AI-assisted operation touches production systems
  • Restricted access scope: I wouldn’t give AI the same access in a corporate environment , and understanding why is exactly the point
  • Human-in-the-loop: AI suggests, humans approve. Every destructive or state-changing operation requires explicit authorization
  • Compliance alignment: SOC 2, PCI-DSS, and industry-specific frameworks integrated from day one, not bolted on after

The ROI Model

This isn’t a hobby , it’s a validated business case.

Open-Source Stack ($240/yr)

  • Proxmox VE (virtualization)
  • NetBox (IPAM/DCIM)
  • Naemon + Loki/Grafana (monitoring)
  • Ansible (automation)
  • pfSense (firewall)
  • Vaultwarden (secrets)
  • MediaWiki (documentation)

Commercial Equivalent ($75K–$109K/yr)

  • VMware vSphere
  • ServiceNow CMDB
  • SolarWinds + Splunk
  • Red Hat Ansible Tower
  • Palo Alto Networks
  • CyberArk / HashiCorp
  • Confluence

5-year projected net benefit: $706K at 1,117% ROI.


Deep Dives

Explore the technical details behind each component: