Cloud | Mobile | Edge
I am Jared Rhodes, a Microsoft Azure MVP and software architect. I build edge and hybrid cloud demo systems that run across Azure, AWS, and a basement private cloud lab of Tenstorrent and NVIDIA hardware. I write up the architecture here, including the parts that did not work.
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AI on the Edge series
This series builds the AI on the Edge demo system: cloud-governed, locally executed AI using a .NET gateway, policy-driven model routing, private RAG, camera fleet telemetry, Azure Arc operations, and...
Start with: AI on the Edge: Local AI Without Local Chaos
AI on the Edge project pageWestworld of Warcraft series
This series builds Westworld of Warcraft: a private World of Warcraft server populated by AI-driven characters that quest, group, raid, trade, and talk. It covers the injection and protocol runtimes,...
Westworld of Warcraft project page-
The AI on the Edge Reference Architecture
Final synthesis for AI on the Edge: gateway, router, policy, RAG, IoT operations assistant, Azure governance, Azure Local lane, private cloud lab, Tenstorrent lane, and conference-ready flow.
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Building the AI on the Edge Demo System
Engineering wrap-up for AI on the Edge: repo layout, make demo-laptop through make teardown targets, seed, reset, and smoke tests, shared health endpoints, and a repeatable 45-minute conference flow.
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Specialized Hardware Without an App Rewrite
AI on the Edge Demo 6: registering a Tenstorrent or mock accelerator as an OpenAI-compatible gateway backend with capability discovery, health checks, fallback, and accelerator-preferred routing - no application rewrite.
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When the Edge Has to Stand Alone
Demo 5 of AI on the Edge: disconnected operation, backend failures, malformed responses, cloud-blocked mode, local-only denial, smoke tests, and reset controls.
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Edge AI You Can Actually Operate
Demo 4 of AI on the Edge: operating local AI with Azure Arc, GitOps, Azure Monitor, Managed Prometheus, Grafana, Key Vault, policy events, KQL, and dashboard evidence.
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From Camera Events to Operator Guidance
Demo 3 of AI on the Edge: turning the existing cameras/# MQTT contract into an operations assistant using simulated, MQTT, and Event Hubs input modes.
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Private RAG That Cannot Leave the Edge
Demo 2 for AI on the Edge: document ingestion, local embeddings, vector search, citations, data classification, LocalOnly routing, and fail-closed cloud fallback.
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One App, Many Places to Run AI
Demo 1 for AI on the Edge: my .NET gateway, OpenAI-compatible facade, backend registry, route explanations, target backends, and LocalOnly denial behavior.
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AI on the Edge: Local AI Without Local Chaos
Why I built AI on the Edge: local execution, Azure governance, model routing, an IoT camera workload, my private cloud lab, and conference-ready demo modes.
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Cameras on Azure IoT Operations, Part 3: Data Flows, Connectors, and the Cloud
Forward camera telemetry to the cloud with Azure IoT Operations data flows to Event Hubs, then onboard ONVIF cameras as AIO assets through a connector and a bridge - all with no change to the control plane.