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# From Factory Floor to Kubernetes Core: Building an Edge Platform One Step at a Time

Schwarz Group faced a critical challenge: securely bridging legacy industrial machinery with modern cloud environments. Discover how they architected a GitOps-driven Kubernetes edge platform to run local AI.

- **Speakers:** [Dean Oren](https://www.wearedevelopers.com/@dean-oren), [Stefan Belsch](https://www.wearedevelopers.com/@stefan-belsch)
- **Event:** World Congress 2025
- **Published:** August 20, 2025
- **Duration:** 17:34
- **URL:** https://www.wearedevelopers.com/videos/1415-from-factory-floor-to-kubernetes-core-building-an-edge-platform-one-step-at-a-time

## Summary

The Schwarz Group, encompassing massive retail and industrial operations like Kaufland and PreZero, faced a critical challenge: securely bridging the gap between legacy industrial factory floors and modern cloud environments. Escaping outdated connectivity paradigms, the engineering team architected a unified edge platform built on Kubernetes. Operating on a hub-and-spoke model, this critical infrastructure establishes highly available control planes running on-premise and scalable edge environments utilizing lightweight K3s deployments for smaller devices.

To ensure consistency across dozens of production facilities, the platform heavily relies on GitOps methodologies and robust automation. Azure DevOps pipelines govern infrastructure provisioning, instantly bootstrapping new edge locations and integrating them into the central control planes within minutes. Argo CD, utilizing an App of Apps deployment pattern, drives continuous application delivery and configuration management. The team prioritizes open-source tools to manage costs while retaining enterprise scalability, employing External Secrets linked with Azure Key Vault for security, and leveraging Node-RED alongside the Prometheus and Grafana stack for direct machine integration and distributed observability.

The platform's capabilities are practically demonstrated through AI-driven foreign object detection on meat processing conveyor belts. Edge devices continually process images via local AI models, immediately communicating intervention commands back to the manufacturing machinery via Node-RED. Moving forward, the team is building a centralized "control plane of control planes" to unify multi-domain management across the enterprise. Furthermore, they are developing a self-service interface that permits factory teams to automatically bootstrap secure edge devices and deploy applications on demand without requiring central IT intervention.

**Keywords:** industrial edge computing, kubernetes hub and spoke, k3s device deployment, gitops automated provisioning, argo cd app of apps, azure devops bootstrapping pipelines, node-red machine integration, edge observability stack, kubernetes external secrets, manufacturing iot architecture, on-premise control planes, edge ai object detection, ot cloud convergence, self-service cluster onboarding

## Chapters

1. **Industrial context and operational scale across manufacturing facilities** (02:24) — Managing vast manufacturing and retail operations requires a resilient digital backbone to support massive production lines.
1. **Origins of the edge connectivity platform using Kubernetes** (04:11) — The growing need for secure, highly available machine integration drove the transition to a robust Kubernetes-based platform.
1. **Core principles for building sustainable edge infrastructure topologies** (05:14) — A centralized hub-and-spoke model paired with GitOps methodologies ensures reliable scaling of remote factory devices.
1. **Evolving and automating infrastructure deployment pipelines at scale** (06:15) — Transitioning from manual deployment scripts to structured CI/CD pipelines significantly accelerates new infrastructure onboarding.
1. **Strategic tool selection and the evolution of technology stacks** (08:01) — Implementing architectural decision records and utilizing an open-source first strategy enables highly adaptable platform components.
1. **High-level platform architecture and distributed edge node design** (09:22) — Centralized control planes deployed on vSphere connect dynamically to lightweight k3s Kubernetes edge clusters.
1. **Bootstrapping infrastructure pipelines and continuous delivery security protocols** (10:27) — Automated pipeline workflows securely manage cluster secrets and orchestrate continuous application delivery across various endpoints.
1. **Deploying AI-driven foreign object detection in manufacturing environments** (11:40) — Deploying an edge AI application via Kubernetes enables real-time anomaly detection on continuous factory conveyor belts.
1. **Orchestrating automated edge device provisioning and application delivery** (14:15) — Ephemeral provisioning workflows fully automate edge environment setups and application deployments by monitoring connected Git repositories.
1. **Future architectural roadmaps for platform automation and self-service workflows** (16:11) — Building hierarchical control planes and self-service interfaces simplifies infrastructure onboarding for autonomous business-unit deployments.

## Related Moments

- [Adapting Kubernetes deployment patterns for heterogeneous edge device fleets](https://www.wearedevelopers.com/videos/100160-from-cloud-racks-to-control-cabinets-operating-kubernetes-on-edge-devices) (from "From Cloud Racks to Control Cabinets: Operating Kubernetes on Edge Devices")
- [Speaker background and open source Kubernetes edge computing projects](https://www.wearedevelopers.com/videos/100094-from-bytes-to-execution-writing-a-webassembly-runtime-in-rust) (from "From Bytes to Execution: Writing a WebAssembly Runtime in Rust")
- [Continuous deployment to edge devices using Argo CD](https://www.wearedevelopers.com/videos/1609-from-code-to-motion-building-an-autonomous-hat-hunting-robot-with-kubernetes-ml) (from "From Code to Motion: Building an Autonomous Hat-Hunting Robot with Kubernetes & ML")
- [Challenges of application edge deployment and containers](https://www.wearedevelopers.com/videos/1609-from-code-to-motion-building-an-autonomous-hat-hunting-robot-with-kubernetes-ml) (from "From Code to Motion: Building an Autonomous Hat-Hunting Robot with Kubernetes & ML")
- [Overview of the Edge AI ecosystem and tech stack](https://www.wearedevelopers.com/videos/1572-privacy-first-in-browser-generative-ai-web-apps-offline-ready-future-proof-standards-based) (from "Privacy-first in-browser Generative AI web apps: offline-ready, future-proof, standards-based")
- [Deploying algorithms and AI models to edge production](https://www.wearedevelopers.com/videos/100081-edge-orchestration-for-the-physical-world-connecting-cameras-sensors-and-devices-with-mqtt) (from "Edge Orchestration for the Physical World: Connecting Cameras, Sensors, and Devices with MQTT")

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