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
87 lines
2.3 KiB
YAML
87 lines
2.3 KiB
YAML
apiVersion: v1
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kind: ConfigMap
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metadata:
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name: frigate-config
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namespace: frigate
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data:
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config.yml: |
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mqtt:
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host: mosquitto.mqtt.svc.cluster.local
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port: 1883
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go2rtc:
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streams:
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# GableCam IP is reserved in UX7 DHCP config
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gablecam:
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- "rtsp://{FRIGATE_CAMERA_USER}:{FRIGATE_CAMERA_PASSWORD}@192.168.1.159:554/h264Preview_01_main"
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gablecam_sub:
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- "rtsp://{FRIGATE_CAMERA_USER}:{FRIGATE_CAMERA_PASSWORD}@192.168.1.159:554/h264Preview_01_sub"
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cameras:
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gablecam:
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enabled: true
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ffmpeg:
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inputs:
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- path: rtsp://127.0.0.1:8554/gablecam
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input_args: preset-rtsp-restream
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roles: [record]
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- path: rtsp://127.0.0.1:8554/gablecam_sub
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input_args: preset-rtsp-restream
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roles: [detect]
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detect:
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enabled: true
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stationary:
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max_frames:
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default: 1500
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motion:
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mask:
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- 0.401,0.026,0.4,0.078,0.587,0.072,0.585,0.02
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- 0.881,0.422,0.789,0.245,0.595,0.054,0.531,0,0.634,0,0.824,0.192,0.892,0.307
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zones:
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driveway_entrance:
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coordinates: 0.85,0.366,0.735,0.344,0.681,0.2,0.795,0.255
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objects: [car, dog, person]
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driveway:
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coordinates: 0.767,0.25,0.58,0.2,0.218,0.25,0.128,0.296,0.003,0.565,0.001,0.992,0.826,0.992,0.897,0.665,0.869,0.608,0.788,0.354
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review:
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alerts:
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labels: [person, car]
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required_zones:
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- driveway_entrance
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detections:
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required_zones:
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- driveway
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- driveway_entrance
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objects:
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track: [person, car, dog, cat, bird]
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detectors:
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onnx:
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type: onnx
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model:
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model_type: yolonas
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width: 320
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height: 320
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input_tensor: nchw
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input_dtype: int
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path: /media/frigate/models/yolo_nas_s.onnx
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labelmap_path: /labelmap/coco-80.txt
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record:
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enabled: true
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continuous:
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days: 3
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alerts:
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retain:
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days: 30
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mode: active_objects
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detections:
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retain:
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days: 14
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mode: motion
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snapshots:
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enabled: true
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retain:
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default: 14
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