Erich Blume
d5d32fe91f
## 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
18 lines
415 B
YAML
18 lines
415 B
YAML
---
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apiVersion: argoproj.io/v1alpha1
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kind: Application
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metadata:
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name: frigate
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namespace: argocd
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spec:
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project: default
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source:
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repoURL: ssh://forgejo@forge.ops.eblu.me:2222/eblume/blumeops.git
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targetRevision: main
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path: argocd/manifests/frigate
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destination:
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server: https://ringtail.tail8d86e.ts.net:6443
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namespace: frigate
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syncPolicy:
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syncOptions:
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- CreateNamespace=true
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