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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 | Stack: Qdrant Edge, Twelve Labs Marengo 3.0, NVIDIA VSS, Vultr | Output: [GitHub](https://github.com/qdrant/examples/tree/master/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/)
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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.
---
Check out the resources:
Additional Resources:
- **Project Repository**: [qdrant/examples/video-anomaly-edge](https://github.com/qdrant/examples/tree/master/video-anomaly-edge)
- **Part I**: [Architecture, Twelve Labs, and NVIDIA VSS](/documentation/tutorials-build-essentials/video-anomaly-edge-part-1/)
- **Part 1**: [Architecture, Twelve Labs, and NVIDIA VSS](/documentation/tutorials-build-essentials/video-anomaly-edge-part-1/)
- **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/)