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awdemos/README.md

AI Infrastructure & Automation Expert | Nvidia Certified

🎯 Quick Navigation


💡 About This Portfolio

Hi, I'm Drew— a DevOps Architect specializing in AI/ML infrastructure and Kubernetes operations.

What you'll find here:

  • Production-grade infrastructure code and architectural patterns
  • 100+ Kubernetes deployment implementations
  • AI/ML infrastructure with deep Nvidia expertise
  • Open-source tools and automation frameworks

My Focus:

  • Cloud infrastructure optimization (it is not unusual to reduce cloud spend by 50% for clients)
  • Production-ready Kubernetes deployments
  • LLM deployment and optimization
  • Infrastructure as Code
  • Unix philosophy, GNU ethos, cypherpunk minded, polymath of the old school.

🎖️ Nvidia Certification & Expertise

Thousands of Hours of Nvidia Training and Practice

This portfolio demonstrates practical application of Nvidia technologies across multiple projects:

Project Nvidia Technologies Used
LLM Deployment Demos Nvidia GPUs, CUDA optimization
AI Infrastructure Demos Nvidia container runtime, MIG (Multi-Instance GPU)
MLOps Pipelines Nvidia Triton Inference Server, RAPIDS

Certifications: Multiple Nvidia Deep Learning and GPU Computing certifications

Looking for engineers with Nvidia expertise? My code demonstrates hands-on production experience.


👔 For Recruiters & Hiring Managers

Why Consider This Portfolio?

Deep Technical Expertise:

  • Nvidia Technologies: Production experience with GPU-optimized infrastructure
  • Kubernetes: 100+ deployment patterns across AWS, GCP, Azure
  • AI/ML Infrastructure: Production LLM deployments, MLOps pipelines
  • Modern IaC: Pulumi (Go), Terraform, GitOps practices

Open Source Contributions:

Technical Skills Demonstrated:

Cloud & Infrastructure: Kubernetes AWS GCP Azure

AI & ML: Nvidia LLM MLOps

Languages & Tools: Rust Go Python Pulumi

Contact for Recruiting:

  • 🐙 GitHub Issues — Create an issue to reach out
  • 📧 Use GitHub's email contact feature (if public on my profile)

💼 For Consulting Clients

I help organizations:

  • Reduce cloud costs by up to 50%
  • Accelerate AI/ML infrastructure deployment
  • Migrate to Kubernetes with zero downtime
  • Build production-ready MLOps pipelines

Proven Results:

"Reduced our AI costs by 60% while improving performance. The infrastructure overhaul was seamless and team training was invaluable." — CTO, FinTech Startup

"Helped us transition from legacy systems to Kubernetes with zero downtime. The migration strategy was brilliant and execution flawless." — VP Engineering, SaaS Company

How to Work With Me:

  • Initial Consultation: Free 10-minute discovery call
  • Engagement Models:
    • Tier 1: Strategy & Planning — $250/hr, 10-hour minimum
      • Infrastructure Assessment
      • Cost Optimization Analysis
      • Technology Roadmap
      • Team Training
    • Tier 2: Full Implementation — $5,000/project, exclusive to one client
      • Complete Infrastructure Overhaul
      • AI/ML Pipeline Development
      • Kubernetes Migration
      • Ongoing Support (retainer-based)

📅 Schedule Free Consultation: cal.com/aiconsulting

What You Get:

  • Production-ready code (see demos in this repo)
  • Knowledge transfer and team training
  • Ongoing support and optimization
  • Transparent pricing and clear timelines

📂 What's In This Repository

Production-Grade Infrastructure Patterns & Demos

Directory Description Technologies Highlights
kubernetes/ 100+ deployment patterns K8s, EKS, GKE, Talos, Cilium Multi-cloud, zero-trust, GPU-optimized
llm/ AI/ML infrastructure Mistral, OpenAI, Nvidia GPUs Finetuning, inference, RAG pipelines
pulumi-azure-tenant/ Multi-tenant IaC Pulumi (Go), Azure Secure, scalable patterns
dagger-go-ci/ CI/CD pipelines Dagger, Tekton, Go Container-native, reproducible
rust/ Rust CLI tools Rust, Tokio Performance-critical tools
python/ Python best practices Poetry, Type hints Production-ready patterns

Quick Start

# Clone the repository
git clone https://github.com/awdemos/demos.git
cd demos

# Explore available demos
ls -la demos/

🚀 Nvidia Expertise in Action

Certified & Battle-Tested

My portfolio demonstrates production use of Nvidia technologies across multiple domains:

GPU Infrastructure

  • Container Optimization: Nvidia container runtime, GPU scheduling in Kubernetes
  • MIG (Multi-Instance GPU): Partitioning for cost efficiency
  • CUDA Workflows: GPU-accelerated ML pipelines

LLM Deployment

  • Inference Optimization: TensorRT, Triton Inference Server
  • Model Serving: Production deployments of Mistral, OpenAI models
  • Resource Management: GPU memory optimization, batch processing

Development

  • RAPIDS Integration: GPU-accelerated data processing
  • Jupyter on GPU: Production notebook environments
  • Monitoring: GPU metrics, DCGM integration

Explore the Demos:

  • demos/llm/ — LLM infrastructure with GPU optimization
  • demos/kubernetes/ — GPU-enabled Kubernetes deployments

🛠️ Featured Projects

🎯 AI & Development Tools

  • efrit — Native elisp coding agent running in Emacs. Nushell port in progress.
  • Voice of the Dead — SOTA TTS project

🖥️ Cutting-edge Operating System

  • RegicideOS — AI-native, Rust-first, Linux distribution based on Gentoo, BtrFS, Cosmic-Desktop

🧠 AI Knowledge Systems

🔧 LLM Utilities

  • Merlin — LLM router written in Rust. Utilizes RL to route LLM prompts. GPL 3.0 project.
  • Regicide Dotfiles — Configuration files and dotfiles for RegicideOS
  • DCAP — Dynamic Configuration and Application Platform

🛠️ Recommended Tools & Technologies

Infrastructure & Orchestration

  • Talos — Best in class Kubernetes OS
  • Pulumi — Infrastructure as Code in general purpose programming languages
  • vCluster — Virtual Kubernetes clusters
  • Cilium — eBPF-based networking and security
  • Cloudflare — Cost-effective cloud services
  • Railway — Instant deployments, effortless scale

AI & Development

Container & Workflow Tools

  • bincapz — Container image security
  • Colima — Container runtime for macOS/Linux
  • Dive — Docker image layer analysis
  • Podman — Daemonless container engine
  • nerdctl — Docker-compatible containerd CLI
  • slim — Container image optimization (30x reduction)

CI/CD & Automation

  • Tekton — Cloud-native CI/CD framework
  • Dagger.io — Programmable deployment pipelines

Development Environment

Security & Privacy


🤝 Let's Connect

For Recruiters:

  • 📧 Use GitHub's email (if public) or create an issue to reach out
  • 📋 Review the Featured Projects for evidence of expertise

For Consulting:

Open Source:

  • 🐙 Follow on GitHub for new projects
  • ⭐ Star interesting projects to show appreciation

🎓 AI School & Community

Exciting News! I'm launching my comprehensive AI School and Community on Patreon!

🔥 Limited Time Offer: Join our founding member community and get exclusive access to:

  • In-depth AI/ML tutorials and hands-on workshops
  • Live Q&A sessions with industry experts
  • Private community of AI practitioners and enthusiasts
  • Early access to cutting-edge AI tools and techniques
  • Personalized mentorship and career guidance

👉 Join Now: AI School & Community on Patreon

The Mudskippers AI School rise above the competition! Be among the first to shape the future of AI education!


📄 License & Contributing

Contributing

While this is my demo repository, create an issue if you would like to connect with me further!

License

All original code in this repository is released under the MIT License. Third-party components may have different licenses — please refer to their respective documentation.

© 2025 — Portfolio demonstrating AI infrastructure expertise.


🚀 Let's build something amazing together!

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