df3d22b218
- Add comprehensive Tdarr troubleshooting and GPU transcoding documentation - Create /scripts directory for active operational scripts - Archive mapped node example in /examples for reference - Update CLAUDE.md with scripts directory context triggers - Add distributed transcoding patterns and NVIDIA troubleshooting guides - Enhance documentation structure with clear directory usage guidelines 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
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NVIDIA Container Toolkit Troubleshooting
Installation by Distribution
Fedora/Nobara (DNF)
# Remove conflicting packages
sudo dnf remove golang-github-nvidia-container-toolkit
# Add official repository
curl -s -L https://nvidia.github.io/libnvidia-container/stable/rpm/nvidia-container-toolkit.repo | \
sudo tee /etc/yum.repos.d/nvidia-container-toolkit.repo
# Install toolkit
sudo dnf install -y nvidia-container-toolkit
# Configure Docker
sudo nvidia-ctk runtime configure --runtime=docker
Ubuntu/Debian (APT)
# Add repository
curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | \
sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit-keyring.gpg
echo "deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] \
https://nvidia.github.io/libnvidia-container/stable/deb/\$(ARCH) /" | \
sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list
sudo apt-get update && sudo apt-get install -y nvidia-container-toolkit
sudo nvidia-ctk runtime configure --runtime=docker
Common Issues
Docker Service Won't Start
# Check daemon logs
sudo journalctl -xeu docker.service
# Common fixes:
sudo systemctl stop docker.socket
sudo systemctl start docker.socket
sudo systemctl start docker
# Or reset configuration
sudo mv /etc/docker/daemon.json /etc/docker/daemon.json.backup
sudo systemctl restart docker
GPU Not Detected
# Verify nvidia-smi works
nvidia-smi
# Check runtime registration
docker info | grep -i runtime
# Test with simple container
docker run --rm --gpus all nvidia/cuda:11.8-base-ubuntu20.04 nvidia-smi
CDI Method (Alternative)
# Generate CDI spec
sudo nvidia-ctk cdi generate --output=/etc/cdi/nvidia.yaml
# Use in compose
services:
app:
devices:
- nvidia.com/gpu=all
Configuration Patterns
daemon.json Structure
{
"runtimes": {
"nvidia": {
"args": [],
"path": "nvidia-container-runtime"
}
}
}
Testing GPU Access
# Test with Tdarr node image
docker run --rm --gpus all ghcr.io/haveagitgat/tdarr_node:latest nvidia-smi
# Expected output: GPU information table
Fallback Strategies
- Start with CPU-only configuration
- Verify container functionality first
- Add GPU support incrementally
- Keep Intel/AMD GPU fallback enabled