- Updated start-tdarr-gpu-podman-clean.sh to use mapped node with direct media access
- Changed container name from tdarr-node-gpu-unmapped to tdarr-node-gpu-mapped
- Changed node name from nobara-pc-gpu-unmapped to nobara-pc-gpu-mapped
- Updated volume mounts to map TV and Movies directories separately
- Preserved NVMe cache and temp directory configurations
- Updated documentation to reflect mapped node architecture
- Added comparison between mapped and unmapped configurations in examples
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Add Home Assistant deployment guide with container architecture
- Document platform analysis comparing Home Assistant, OpenHAB, and Node-RED
- Add voice automation architecture with local/cloud hybrid approach
- Include implementation details for Rhasspy + Home Assistant integration
- Provide step-by-step deployment guides and configuration templates
- Document privacy-focused voice processing with local wake word detection
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Document hybrid storage strategy for server (local DB/configs, network backups)
- Add production unmapped node configuration with NVMe cache optimization
- Document Docker→Podman migration benefits and GPU improvements
- Update cache paths to reflect actual NVMe location (/mnt/NV2/tdarr-cache)
- Add gaming-aware scheduler and enhanced monitoring system documentation
- Update configuration file paths to current production locations
- Document 100x database performance improvement with local storage
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
Complete documentation package for home lab infrastructure:
## New Documentation Files:
- **Tdarr Monitoring Configuration**: Complete setup guide for Discord-based Tdarr monitoring system
- **NAS Mount Configuration**: SMB/CIFS mount setup and troubleshooting for media storage
- **Discord Monitoring Setup**: Step-by-step guide for webhook configuration and notification testing
## Documentation Features:
- **Reference Architecture**: Best practices for distributed Tdarr deployments
- **Configuration Templates**: Copy-paste ready configurations with security considerations
- **Troubleshooting Guides**: Common issues and solutions for production environments
- **Integration Examples**: Real-world implementation patterns for home lab environments
## Coverage Areas:
- Docker container orchestration and monitoring
- Network storage integration and performance optimization
- Automated alerting and notification systems
- Production-ready configuration management
These documents support the enhanced monitoring system and provide comprehensive guidance for maintaining a robust home lab infrastructure.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
## Tdarr Plugin Stack Research & Configuration
- Research optimal H.265/HEVC plugin stacks for quality-focused transcoding
- Configure GPU threshold (95%) to prevent self-termination during transcoding
- Add Tdarr exception logic to distinguish transcoding from gaming GPU usage
- Update gaming detection to preserve active transcoding jobs
## Automated System Maintenance
- Add cron job for automatic cleanup of abandoned Tdarr temp directories
- Cleanup runs every 6 hours, preserves active jobs (< 6 hours old)
- Prevents /tmp filesystem bloat from interrupted transcoding jobs
- Safe cleanup only targets Tdarr-specific work directories
## Enhanced Documentation
- Add comprehensive Tdarr automation documentation in scripts/tdarr/README.md
- Document cleanup system and its relationship to main scheduler
- Update CLAUDE.md with Tdarr keyword triggers and context loading
- Add troubleshooting section for both scheduler and cleanup cron jobs
## System Architecture Improvements
- Organize Tdarr scripts under dedicated scripts/tdarr/ directory
- Maintain backwards compatibility with existing cron jobs
- Add gaming-aware scheduling with configurable time windows
- Implement robust GPU usage detection with Tdarr transcoding awareness
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Add working Podman-based GPU Tdarr startup script for Fedora systems
- Document critical Docker Desktop GPU issues on Fedora/Nobara systems
- Add comprehensive Tdarr configuration examples (CPU and GPU variants)
- Add GPU acceleration patterns and troubleshooting documentation
- Provide working solution for NVIDIA RTX GPU hardware transcoding
Key insight: Podman works immediately for GPU access on Fedora systems
where Docker Desktop fails due to virtualization layer conflicts.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Add SSH key management patterns with dual-key strategy and NAS backup architecture
- Add complete SSH home lab setup implementation with scripts and configurations
- Add SSH troubleshooting reference with common issues and emergency procedures
- Update CLAUDE.md with SSH keyword triggers for automatic context loading
- Add .gitignore to exclude temporary files
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
- Created structured documentation with /patterns/, /examples/, and /reference/ directories
- Implemented automatic context loading rules in CLAUDE.md based on file extensions, directories, and keywords
- Added technology-specific patterns for Docker, Python, Node.js, Vue.js, Bash, networking, databases, and VM management
- Included complete working examples for common workflows and troubleshooting references
- Designed for minimal context usage with precise loading triggers
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude <noreply@anthropic.com>
