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qdrant-landing/content/documentation/tutorials-build-essentials/video-anomaly-edge-part-2.md
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---
title: "Video Anomaly Detection Part II | Edge-to-Cloud Pipeline"
title: "Video Anomaly Detection Part 2: Edge-to-Cloud Pipeline"
weight: 10
partition: build
social_preview_image: /articles_data/video-anomaly-edge/preview/social_preview.jpg
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| Time: 90 min | Level: Advanced | Output: [GitHub](https://github.com/qdrant/video-anomaly-edge) |
| --- | ----------- | ----------- |
*This is Part II of a 3-part series on building real-time video anomaly detection from edge to cloud.*
*This is Part 2 of a 3-part series on building real-time video anomaly detection from edge to cloud.*
**Series:**
- [Part I | Architecture, Twelve Labs, and NVIDIA VSS](/documentation/tutorials-build-essentials/video-anomaly-edge-part-1/)
- Part II | Edge-to-Cloud Pipeline (here)
- [Part III | Scoring, Governance, and Deployment](/documentation/tutorials-build-essentials/video-anomaly-edge-part-3/)
- [Part 1 | Architecture, Twelve Labs, and NVIDIA VSS](/documentation/tutorials-build-essentials/video-anomaly-edge-part-1/)
- Part 2 | Edge-to-Cloud Pipeline (here)
- [Part 3 | Scoring, Governance, and Deployment](/documentation/tutorials-build-essentials/video-anomaly-edge-part-3/)
---
In [Part I](/documentation/tutorials-build-essentials/video-anomaly-edge-part-1/), we set up the project, covered why kNN anomaly detection in Qdrant outperforms classifiers, integrated Twelve Labs for video embeddings and Q&A, and connected NVIDIA VSS. Now we build the edge.
In [Part 1](/documentation/tutorials-build-essentials/video-anomaly-edge-part-1/), we set up the project, covered why kNN anomaly detection in Qdrant outperforms classifiers, integrated Twelve Labs for video embeddings and Q&A, and connected NVIDIA VSS. Now we build the edge.
## Why Qdrant Edge
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## Recap
In Part II, you built Qdrant Edge's two-shard architecture (immutable baseline + mutable live context), implemented edge triage that reduces cloud processing by ~6x, wired the escalation pipeline with ensemble scoring and temporal boosting, and added offline resilience. The edge is running. Now we need to turn raw scores into actionable incidents.
In Part 2, you built Qdrant Edge's two-shard architecture (immutable baseline + mutable live context), implemented edge triage that reduces cloud processing by ~6x, wired the escalation pipeline with ensemble scoring and temporal boosting, and added offline resilience. The edge is running. Now we need to turn raw scores into actionable incidents.
## What's Next
In **[Part III | Scoring, Governance, and Deployment](/documentation/tutorials-build-essentials/video-anomaly-edge-part-3/)**, we'll cover incident formation from raw scores, baseline governance to prevent poisoning, unified retrieval across cameras, evaluation results on UCF-Crime, and deployment on Vultr Cloud GPUs.
In **[Part 3 | Scoring, Governance, and Deployment](/documentation/tutorials-build-essentials/video-anomaly-edge-part-3/)**, we'll cover incident formation from raw scores, baseline governance to prevent poisoning, unified retrieval across cameras, evaluation results on UCF-Crime, and deployment on Vultr Cloud GPUs.
---
Additional Resources:
- **Project Repository**: [qdrant/video-anomaly-edge](https://github.com/qdrant/video-anomaly-edge)
- **Part I**: [Architecture, Twelve Labs, and NVIDIA VSS](/documentation/tutorials-build-essentials/video-anomaly-edge-part-1/)
- **Part III**: [Scoring, Governance, and Deployment](/documentation/tutorials-build-essentials/video-anomaly-edge-part-3/)
- **Part 1**: [Architecture, Twelve Labs, and NVIDIA VSS](/documentation/tutorials-build-essentials/video-anomaly-edge-part-1/)
- **Part 3**: [Scoring, Governance, and Deployment](/documentation/tutorials-build-essentials/video-anomaly-edge-part-3/)
- **Qdrant Edge Documentation**: [qdrant.tech/documentation/edge](/documentation/edge/)
- **Twelve Labs Documentation**: [docs.twelvelabs.io](https://docs.twelvelabs.io/)
- **Vultr Cloud GPUs**: [vultr.com/products/cloud-gpu](https://www.vultr.com/products/cloud-gpu/)