Guide — Updated August 2026

Foundry Local Architecture Guide

How Foundry Local runs private, sovereign, and disconnected AI on your own hardware.

Running AI on your own hardware — including air-gapped — has a specific architecture. This guide explains Foundry Local.

This guide explains Foundry Local on Azure Local: on-prem, edge, and disconnected (air-gapped) inference with the default ONNX-GenAI engine and a vLLM runtime for GPU serving, multi-node Kubernetes, multi-GPU model parallelism (tensor_parallel_size and pipeline_parallel_size), the automatic GPU inference planner, model caching, and inference-aware routing without outbound internet — for private and sovereign AI.

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This guide explains Foundry Local in practical terms — what it is, how it works on Azure day to day, the common production problems and how they are handled, and how professional support fits in. It reflects the Microsoft/Azure product state through August 2026 and is written for working Azure AI/ML professionals and candidates who want clear, real-world answers rather than marketing.

This is an educational guide. If you decide you want hands-on help, we also offer real-time Azure AI/ML job support, production issue support, interview assistance, and candidate marketing — but the guide itself is here to inform, and you can act on it however you like.

Azure AI Engineers, Microsoft Foundry engineers, Azure OpenAI developers, Azure ML and MLOps engineers, data scientists, and anyone preparing for Azure AI/ML roles or currently working on Azure AI projects who wants to understand the topic clearly and avoid common mistakes.

Reach out on WhatsApp describing your situation — your Azure stack, your role, and what you are stuck on. We will point you to the right support option, whether that is live job support, a production fix, interview help, or profile positioning.

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Beyond this guide, we offer Azure AI proxy job support for live Foundry Local projects and production issues, plus Foundry Local proxy interview support (technical preparation and mentoring; you attend your own interview). Talk to ProxyTechSupport on WhatsApp.

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