5bd5e31798
- Add CONTEXT.md with GPU transcoding patterns - Add Jellyfin ubuntu-manticore setup guide (10.10.0.226) - Document GPU resource sharing with Tdarr 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
134 lines
3.6 KiB
Markdown
134 lines
3.6 KiB
Markdown
# Media Servers - Technology Context
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## Overview
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Media server infrastructure for home lab environments, covering streaming services like Jellyfin and Plex with hardware-accelerated transcoding, library management, and client discovery.
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## Current Deployments
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### Jellyfin on ubuntu-manticore
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- **Location**: 10.10.0.226:8096
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- **GPU**: NVIDIA GTX 1070 (NVENC/NVDEC)
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- **Documentation**: `jellyfin-ubuntu-manticore.md`
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### Plex (Existing)
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- **Location**: TBD (potential migration to ubuntu-manticore)
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- **Note**: Currently running elsewhere, may migrate for GPU access
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## Architecture Patterns
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### GPU-Accelerated Transcoding
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**Pattern**: Hardware encoding/decoding for real-time streaming
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```yaml
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# Docker Compose GPU passthrough
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deploy:
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resources:
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reservations:
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devices:
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- driver: nvidia
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count: all
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capabilities: [gpu]
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environment:
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- NVIDIA_DRIVER_CAPABILITIES=all
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- NVIDIA_VISIBLE_DEVICES=all
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```
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### Storage Strategy
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**Pattern**: Tiered storage for different access patterns
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- **Config**: Local SSD (small, fast database access)
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- **Cache**: Local NVMe (transcoding temp, thumbnails)
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- **Media**: Network storage (large capacity, read-only mount)
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### Multi-Service GPU Sharing
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**Pattern**: Resource allocation when multiple services share GPU
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- Limit background tasks (Tdarr) to fewer concurrent jobs
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- Prioritize real-time services (Jellyfin/Plex playback)
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- Consumer GPUs limited to 2-3 concurrent NVENC sessions
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## Common Configurations
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### NVIDIA GPU Setup
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```bash
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# Verify GPU in container
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docker exec <container> nvidia-smi
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# Check encoder/decoder utilization
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nvidia-smi dmon -s u
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```
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### Media Volume Mounts
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```yaml
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volumes:
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- /mnt/truenas/media:/media:ro # Read-only for safety
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```
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### Client Discovery
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- **Jellyfin**: UDP 7359
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- **Plex**: UDP 32410-32414, GDM
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## Integration Points
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### Watch History Sync
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- **Tool**: watchstate (ghcr.io/arabcoders/watchstate)
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- **Method**: API-based sync between services
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- **Note**: NFO files do NOT store watch history
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### Tdarr Integration
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- Tdarr pre-processes media for optimal streaming
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- Shared GPU resources require coordination
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- See `tdarr/CONTEXT.md` for transcoding system details
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## Best Practices
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### Performance
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1. Use NVMe for cache/transcoding temp directories
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2. Mount media read-only to prevent accidental modifications
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3. Enable hardware transcoding for all supported codecs
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4. Limit concurrent transcodes based on GPU capability
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### Reliability
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1. Use `restart: unless-stopped` for containers
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2. Separate config from cache (different failure modes)
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3. Monitor disk space on cache volumes
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4. Regular database backups (config directory)
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### Security
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1. Run containers as non-root (PUID/PGID)
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2. Use read-only media mounts
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3. Limit network exposure (internal LAN only)
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4. Regular container image updates
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## GPU Compatibility Notes
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### NVIDIA Pascal (GTX 10-series)
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- NVENC: H.264, HEVC (no B-frames for HEVC)
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- NVDEC: H.264, HEVC, VP8, VP9
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- Sessions: 2 concurrent (consumer card limit)
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### NVIDIA Turing+ (RTX 20-series and newer)
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- NVENC: H.264, HEVC (with B-frames), AV1
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- NVDEC: H.264, HEVC, VP8, VP9, AV1
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- Sessions: 3+ concurrent
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## Troubleshooting
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### Common Issues
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1. **No GPU in container**: Check Docker/Podman GPU passthrough config
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2. **Transcoding failures**: Verify codec support for your GPU generation
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3. **Slow playback start**: Check network mount performance
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4. **Cache filling up**: Monitor trickplay/thumbnail generation
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### Diagnostic Commands
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```bash
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# GPU status
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nvidia-smi
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# Container GPU access
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docker exec <container> nvidia-smi
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# Encoder/decoder utilization
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nvidia-smi dmon -s u
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# Container logs
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docker logs <container> 2>&1 | tail -50
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```
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