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d5d32fe91f
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Port Frigate NVR to ringtail k3s with GPU acceleration (#217)
## Summary
- Enable NVIDIA container toolkit on ringtail NixOS and configure k3s containerd with nvidia runtime
- Add NVIDIA device plugin ArgoCD app (RuntimeClass + DaemonSet) to expose `nvidia.com/gpu` resources
- Re-target Frigate from indri minikube (arm64, ZMQ detector) to ringtail k3s (x86_64, TensorRT/ONNX)
- Switch Frigate image to `-tensorrt` variant with GPU resource limits and increased shared memory
## Manual Prerequisites
1. **NFS access**: Verify ringtail can mount `sifaka:/volume1/frigate`
```fish
ssh ringtail 'sudo mount -t nfs sifaka:/volume1/frigate /mnt/storage1 && ls /mnt/storage1 && sudo umount /mnt/storage1'
```
2. **YOLO model**: Verify `/volume1/frigate/models/yolov9m.onnx` exists on sifaka
## Deployment Steps
1. Provision ringtail: `mise run provision-ringtail`
2. Sync ArgoCD apps: `argocd app sync apps --prune`
3. Deploy NVIDIA device plugin: `argocd app sync nvidia-device-plugin`
4. Verify GPU: `kubectl --context=k3s-ringtail get nodes -o json | jq '.items[].status.capacity'`
5. Deploy Frigate: `argocd app sync frigate`
## Verification
- [ ] `nvidia.com/gpu: 1` visible in node capacity
- [ ] Frigate pod running with GPU allocated
- [ ] Frigate UI loads at `https://nvr.ops.eblu.me`
- [ ] Detector shows ONNX/TensorRT on System page
- [ ] Camera feed with bounding boxes in live view
- [ ] TensorRT engine build completes (watch logs on first start)
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Reviewed-on: https://forge.ops.eblu.me/eblume/blumeops/pulls/217
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2026-02-19 14:27:04 -08:00 |
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