- Document Tdarr node setup on ubuntu-manticore - Include GPU configuration and container setup 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
163 lines
4.4 KiB
Markdown
163 lines
4.4 KiB
Markdown
# Tdarr Setup on ubuntu-manticore
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## Overview
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Tdarr server and GPU-accelerated node deployed on ubuntu-manticore (10.10.0.226) with NVIDIA GTX 1070 for hardware transcoding. Migrated from old server at 10.10.0.43.
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**Date**: 2025-12-04
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## Architecture
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```
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ubuntu-manticore (10.10.0.226)
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├── tdarr-server (container)
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│ ├── Web UI: http://10.10.0.226:8265
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│ ├── Node Port: 8266
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│ └── Data: ~/docker/tdarr/server-data/
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├── tdarr-node (container)
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│ ├── Node Name: manticore-gpu
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│ ├── GPU: GTX 1070 (NVENC/NVDEC)
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│ └── Cache: /mnt/NV2/tdarr-cache (NVMe)
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└── Media: /mnt/truenas/media (CIFS mount)
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```
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## Docker Compose Configuration
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**Location**: `~/docker/tdarr/docker-compose.yml`
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```yaml
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version: "3.8"
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services:
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tdarr:
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image: ghcr.io/haveagitgat/tdarr:latest
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container_name: tdarr-server
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restart: unless-stopped
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ports:
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- "8265:8265" # Web UI
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- "8266:8266" # Server port (for nodes)
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environment:
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- PUID=1000
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- PGID=1000
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- TZ=America/Chicago
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- serverIP=0.0.0.0
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- serverPort=8266
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- webUIPort=8265
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volumes:
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- ./server-data:/app/server
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- ./configs:/app/configs
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- ./logs:/app/logs
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- /mnt/truenas/media:/media
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tdarr-node:
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image: ghcr.io/haveagitgat/tdarr_node:latest
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container_name: tdarr-node
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restart: unless-stopped
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environment:
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- PUID=1000
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- PGID=1000
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- TZ=America/Chicago
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- serverIP=tdarr
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- serverPort=8266
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- nodeName=manticore-gpu
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volumes:
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- ./node-data:/app/configs
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- /mnt/truenas/media:/media
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- /mnt/NV2/tdarr-cache:/temp
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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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depends_on:
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- tdarr
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```
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## GPU Configuration
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### Hardware
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- **GPU**: NVIDIA GeForce GTX 1070 (Pascal architecture)
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- **Driver**: 570.195.03
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- **CUDA**: 12.8
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### NVENC Capabilities
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| Encoder | Supported | Working |
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|---------|-----------|---------|
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| h264_nvenc | Yes | Yes |
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| hevc_nvenc | Yes | Yes |
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| av1_nvenc | Yes | No (requires Turing+) |
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### Important Limitation: B-Frames
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**GTX 1070 does NOT support B-frames for HEVC encoding** (Pascal limitation).
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If using `Tdarr_Plugin_MC93_Migz1FFMPEG` or similar plugins:
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- Set `enable_bframes` to `false`
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- Otherwise you'll get: `Max B-frames 5 exceed 0` / `No capable devices found`
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B-frame support for HEVC NVENC requires RTX 20-series (Turing) or newer.
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## Migration from Old Server
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### Source
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- **Server**: 10.10.0.43 (ubuntu-ct, SSH alias: `tdarr`)
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- **Container**: tdarr-clean
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- **Data**: `/home/cal/container-data/tdarr/tdarr-clean/server/` (~4.4GB)
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### Migration Process
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```bash
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# Stop old server
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ssh tdarr "docker stop tdarr-clean"
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# Pull data to local workstation (relay)
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rsync -avz --progress tdarr:/home/cal/container-data/tdarr/tdarr-clean/server/ /tmp/tdarr-server-data/
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# Push to new server
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rsync -avz --progress /tmp/tdarr-server-data/ cal@10.10.0.226:/home/cal/docker/tdarr/server-data/
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# Start new server
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ssh cal@10.10.0.226 "cd ~/docker/tdarr && docker compose up -d"
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```
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## Performance
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### Observed Speeds
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- **1080p H.264 → HEVC**: 200+ fps (~8-9x real-time)
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- **GPU Utilization**: 30-60% encoder, 40-70% decoder
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- **Power Draw**: ~52W during transcoding (166W max)
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### Monitoring GPU Usage
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```bash
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# Basic status
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nvidia-smi
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# Detailed encoder/decoder utilization
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nvidia-smi dmon -s u
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```
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### Recommended Settings
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- **GPU Workers**: 1 (leaves headroom for Jellyfin)
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- **CPU Workers**: 0 (GPU-only transcoding)
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## Troubleshooting
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### Error: "Max B-frames X exceed 0"
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**Cause**: Plugin configured with B-frames, but GTX 1070 doesn't support them for HEVC
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**Fix**: Disable `enable_bframes` in the plugin settings
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### Error: "No capable devices found"
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**Cause**: Usually means incompatible encoding parameters, not missing GPU
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**Check**: Run `nvidia-smi` inside container to verify GPU access:
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```bash
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docker exec tdarr-node nvidia-smi
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```
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### Slow File Copy (0% progress)
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**Cause**: Large files copying from network share to local cache
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**Expected**: ~90 seconds for 10GB file over gigabit
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**Note**: This is normal for mapped node architecture - file must copy before transcoding starts
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## Related Documentation
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- Server inventory: `networking/server-inventory.md`
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- Tdarr technology context: `tdarr/CONTEXT.md`
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- Tdarr troubleshooting: `tdarr/troubleshooting.md`
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