Microsoft Foundry: Your AI Command Center | Guided by A Guide to Cloud

What is Microsoft Foundry?

Simple explanation

Microsoft Foundry is your AI workshop — it’s where you go to build, test, and deploy everything AI in Azure.

Think of it like a fully equipped workshop. The model catalog is your tool shelf (hundreds of AI models to choose from). The playground is your workbench (test models without writing code). The project is your workspace (keeps everything organised).

You don’t need to install anything — it’s a web portal at ai.azure.com. Sign in with your Azure account and start building.

The Foundry portal layout

When you sign in to ai.azure.com, you’ll see:

Section	What It Contains
Home	Recent projects, quick actions, getting started guides
Model catalog	Browse and deploy hundreds of models (OpenAI, Microsoft, Meta, Mistral, etc.)
Playground	Chat with deployed models, test prompts, configure settings — no code needed
Build	Create agents, build apps, write and test prompts
Operate	Monitor deployments, view metrics, manage resources
Tools	Foundry Tools (AI services) — Speech, Vision, Language, Content Understanding

Key concepts

Foundry resource

A Foundry resource is the top-level Azure resource that contains everything. Think of it as your AI headquarters.

Projects

A project is a workspace within a Foundry resource. Each project has:

Its own deployed models
Its own agents
Its own API keys and endpoints
Its own monitoring and logs

Priya scenario: Priya creates a Foundry resource for her university work. Inside it, she creates two projects: one for her coursework chatbot and one for her thesis research assistant.

Model deployments

A deployment makes a model available through an API endpoint. When you deploy GPT-4o, you get a URL that your applications can call to send prompts and receive responses.

Deploying your first model — step by step

Here’s how Priya deploys GPT-4o in the Foundry portal:

Sign in to ai.azure.com
Select a project (or create one)
Go to Model catalog → search for “GPT-4o”
Click Deploy → choose deployment type (Global Standard is easiest)
Name your deployment (e.g., “gpt4o-coursework”)
Set configuration — rate limits, content filters
Deploy — within seconds, you have an API endpoint

The Playground: testing without code

The Playground is where you test your deployed model interactively:

Playground Feature	What You Can Do
Chat	Have a conversation with the model, just like ChatGPT
System prompt	Set the system message (role, rules, tone)
Parameters	Adjust temperature, max tokens, top-p in real time
View code	See the equivalent Python/C#/JavaScript code for your chat
Compare models	Run the same prompt against different deployments side by side

Key exam concept: The Playground is the fastest way to test prompts and parameters without writing any code. It generates the equivalent SDK code you can copy into your application.

Foundry evolution: what changed and why

Understanding the naming history helps on the exam:

Previous Name	Current Name
Azure AI Studio	Microsoft Foundry (portal)
Azure AI Services	Foundry Tools
Azure OpenAI Service	Part of Foundry (OpenAI models)
Hub + AI resource	Foundry resource + projects
Assistants API	Responses API

The exam may still reference older terminology in some questions. Know that “Foundry” is the current umbrella term.

Foundry Tools (formerly Azure AI Services)

Foundry Tools are the specialized AI services available within Foundry:

Tool	Capability
Azure AI Language	Text analysis — sentiment, entities, keywords, summarisation
Azure AI Speech	Speech-to-text, text-to-speech, translation
Azure AI Vision	Image analysis, OCR, face detection
Azure Content Understanding	Document, image, audio, video extraction
Azure OpenAI	GPT models, GPT-image, embeddings (model access, not a standalone tool)

🎬 Video walkthrough

🎬 Video coming soon

Microsoft Foundry Portal — AI-901 Module 13

~14 min

Flashcards

Question

What is Microsoft Foundry?

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Answer

Microsoft's unified Azure platform for building, deploying, and governing AI solutions. It combines model deployment, agent creation, evaluation, and monitoring. Access it at ai.azure.com.

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Question

What is a Foundry project?

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Answer

A workspace within a Foundry resource. Each project has its own deployed models, agents, API keys, endpoints, and monitoring. Think of it as a separate workspace for each AI initiative.

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Question

What is the Foundry Playground?

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Answer

An interactive testing environment where you can chat with deployed models, adjust parameters (temperature, max tokens), set system prompts, and view equivalent SDK code — all without writing code.

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Question

What are Foundry Tools?

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Answer

Specialised AI services within Foundry (formerly Azure AI Services): Language, Speech, Vision, Content Understanding, and Azure OpenAI. Each provides focused capabilities for specific AI workloads.

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Knowledge Check

Priya wants to test how GPT-4o responds to different system prompts and temperature settings before writing any code. Which Foundry feature should she use?

Knowledge Check

DataFlow Corp needs to organise their AI work: one team builds customer support bots, another works on document processing. How should they structure their Foundry setup?

Next up: Building a Chat App with the Foundry SDK — writing your first Python code to interact with AI.