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In Memory of Tteck (1969-2024)
This page is dedicated to the memory of Tteck, whose Proxmox Helper Scripts have made home labs and self-hosting accessible to countless enthusiasts. His contributions to the community have been invaluable, and his work continues to live on through the community. If you've benefited from his work, please consider supporting his family through Ko-fi.
The scripts are now community-maintained at community-scripts.github.io/ProxmoxVE
Key Areas of Exploration
Home Infrastructure & Self-Hosting
Currently exploring and documenting:
- Building resilient home lab infrastructure
- Proxmox virtualization and container management
- Network architecture and security
- Self-hosted service management
Recommended Resources:
- Awesome-Selfhosted - Comprehensive list of self-hostable software
- HomelabOS - Your very own offline-first privacy-focused open-source data-center
- Self-Hosted Podcast - Jupiter Broadcasting's guide to self-hosting
Local AI & Machine Learning
Focus areas:
- Running large language models locally
- AI infrastructure optimization
- Model fine-tuning and quantization
- Privacy-focused AI implementations
Essential Projects:
- LocalAI - Self-hosted, community-driven AI solution
- PrivateGPT - Private document QA using LLMs
- Ollama - Get up and running with large language models locally
Development & Infrastructure
Experience with:
- Ghost CMS deployments
- Infrastructure as Code
- Container orchestration
- CI/CD implementation
My Contributions:
- Ghost + CloudFlare Setup Guide - Complete walkthrough for hosting a Ghost blog
Community Resources
Home Lab Essentials
Documentation:
GitHub Repositories:
Local AI Implementation
Projects & Tools:
- Text Generation WebUI
- LMStudio
- GGML - Tensor library for machine learning
Learning Resources:
Books Worth Reading
Technical Foundations
- "Designing Data-Intensive Applications" by Martin Kleppmann
Essential reading for understanding distributed systems - "Site Reliability Engineering" by Betsy Beyer et al.
Google's approach to managing large-scale systems - "Infrastructure as Code" by Kief Morris
Fundamental patterns for managing services
AI & Machine Learning
- "Deep Learning" by Ian Goodfellow et al.
Comprehensive overview of deep learning fundamentals - "Machine Learning Engineering" by Andriy Burkov
Practical guide to deploying ML systems
Future Explorations
Areas I'm currently researching and will be writing about:
- Optimizing home lab power consumption
- Local LLM deployment strategies
- Network segregation for AI workloads
- Automated backup solutions
Questions to Consider
- How do we balance system complexity with maintainability?
- What are the practical limits of home lab infrastructure?
- How can we make AI more accessible while maintaining privacy?
- Where is the sweet spot between automation and control?
Connect & Learn
- Engage with the Homelab Reddit Community
- Join Self-Hosted discussions
- Follow developments in LocalLLaMA
This hub is evolving as I explore and document new areas. Last updated: 17/02/2025