Demystifying Azure AI Foundry: A Beginner's Guide
Are you ready to dive into the transformative world of Artificial Intelligence but unsure where to start? You landed at the right page. Welcome! Whether you’re just getting started or have a bit of experience under your belt, this read will provide you with the foundational knowledge needed to unlock the potential of Azure AI Foundry. Azure AI Foundry offers a powerful suite of tools and Machine Learning Models. Let’s start harnessing its capabilities as an initial step to create innovative AI solutions that can revolutionize your projects or business. As a Microsoft Technical Trainer, delivering classes on AI and Data for the past several years, I have witnessed the significant impact AI has had across various industries. My objective here is to equip you with the foundational knowledge and confidence necessary to embark on your AI journey. Azure AI Foundry (formerly Azure AI Studio) is a suite of tools that makes artificial intelligence accessible to everyone. It allows users to build, deploy, and manage AI solutions easily. Azure AI Foundry can be leveraged to address real-world business challenges and foster innovation. For instance, Azure AI Foundry can enhance predictive maintenance in manufacturing by analyzing sensor data to foresee equipment failures to minimize downtime and costs. In retail, it can perform customer sentiment analysis across social media, reviews, and surveys, offering insights into customer satisfaction and areas for improvement. For more ways that Azure AI Foundry can help your organization, see customer stories here: Azure AI Foundry - Generative AI Development Hub and here: Need inspirations? Real AI Apps stories by Azure customers to help you get started With Azure AI Foundry, you can explore and develop various AI models and services tailored to your goals. The platform supports scalability, enabling proof of concepts to become full production applications effortlessly. It also has support for continuous monitoring and refinement ensuring long-term success. Here's a brief overview of AI Foundry's main architectural components and their integration. Azure AI Foundry architecture - Azure AI Foundry At the top level, AI Foundry provides access to the following resources: Management Center: Used to manage AI Foundry resources like hubs, projects, connected resources, and deployments. It is a part of the Azure AI Foundry portal that streamlines governance and management activities. In the management center, you can view and manage: Projects and resources Quotas and usage metrics Govern access and permissions For more information see: Management center overview - Azure AI Foundry AI Foundry Hub: The main top-level resource in the AI Foundry portal, offering a centralized method for managing security, connectivity, and computing resources across playgrounds and projects. Once a hub is established, developers can create projects from it and access shared resources like storage accounts, key vaults, databases and others without requiring continuous assistance from an IT administrator. The hub uses the Azure Machine Learning service and this Azure Provider, Microsoft.MachineLearningServices/workspaces and the type is hub. It offers: Security features, including a managed network for projects and model endpoints. Computer resources for development, fine-tuning, open-source, and serverless model deployments. Connections to other Azure services, such as Azure OpenAI and Azure AI Search. An Azure storage account for data and artifacts. AI Foundry Project: A project is part of the hub. Projects help organize work, save state across tools like prompt flow and enable collaboration. You can share files and data source connections within a project. Hubs support multiple projects and users. Projects manage billing, access, and provide data isolation, using dedicated storage containers to securely share files among project members. Once you have a project, you can connect to it from your code. You can explore models and capabilities before creating a project, but once you're ready to build, customize, test, and operationalize, a project is where you'll want to be. The Azure provider for a project is Microsoft.MachineLearningServices/workspaces, and the type is Project. The project offers: Reusable assets like datasets, models, and indexes. A container for uploading data within the hub's storage. Private data access for project members. Model deployments from the catalog and adjusted model endpoints. Connections: AI Foundry hubs and projects use connections to access resources from other services, such as an Azure Storage Account, Azure OpenAI, or other Azure AI services. Once you have setup the Azure Foundry Hub, Project and Connection, its time to start exploring and deploying the models. Model Catalog: Available in Azure AI Foundry portal to discover and use a wide range of models for building generative AI applications. The model catalog features hundreds of models across model providers such as Azure OpenAI Service, Meta, NVIDIA, Hugging Face, DeepSeek, and of course the models trained by Microsoft like Phi. Azure AI Model Catalog – Foundation Models You can search and discover models that meet your needs. The model catalog also offers the model performance benchmark metrics which can be accessed by using Compare Models feature or from the model card Benchmark tab. Models need to be deployed to make them available for receiving inference requests. Azure AI Foundry offers a comprehensive suite of deployment options for those models depending on your needs and model requirements. Prompt Flow: This feature can be used to generate, customize, or run a flow. A flow is an executable instruction set that can implement the AI logic. Flows can be created or run via multiple tools, like a prebuilt canvas, LangChain, etc. Iterations of a flow can be saved as assets; once deployed a flow becomes an API. Prompt flow in Azure AI Foundry portal - Azure AI Foundry A prompt is sent to a model, consisting of the user input, system message, and any examples. User input is text submitted in the chat window. System message is a set of instructions to the model scoping its behaviors and functionality. Evaluators: Helpful tools to assess the frequency and severity of content risks or undesirable behavior in AI responses. Performing iterative, systematic evaluations with the right evaluators can help teams measure and address potential response quality, safety, or security concerns throughout the AI development lifecycle. You can explore Azure AI Foundry benchmarks to evaluate and compare models on publicly available datasets. Deploy: Remember to deploy your model setup. Deployments are hosted within an endpoint and can receive data from clients and send responses back in real-time. You can invoke the endpoint for real-time inference for chat, copilot or another generative AI application. AI Foundry has all the needed capabilities including content filters, Responsible AI factors and Security. More about these aspects in my next article. Playgrounds: Be sure to test your model using the Playgrounds on Azure AI Foundry. The portal offers a chat playground for deploying and interacting with AI chat models, allowing you to refine them before production deployment. Hear and speak with chat models in the Azure AI Foundry portal chat playground - Azure AI Foundry Now that you have the foundational knowledge, I encourage you to begin using Azure AI Foundry by following the resources and guidelines provided. Ready to get started with Azure AI Foundry? Here are some tutorials to guide you: Use the chat playground in Azure AI Foundry portal Tutorial: Deploy an enterprise chat web app in the Azure AI Foundry portal playground Explore, learn, and transform your ideas into reality with Azure AI Foundry. Stay tuned for more! Happy Learning!
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The AZ-500 certification provides professionals with the skills and knowledge needed to secure Azure infrastructure, services, and data. The exam covers identity and access management, data protection, platform security, and governance in Azure. Learners can prepare for the exam with Microsoft's self-paced curriculum, instructor-led course, and documentation. The certification measures the learner’s knowledge of managing, monitoring, and implementing security for resources in Azure, multi-cloud, and hybrid environments. Azure Firewall, Key Vault, and Azure Active Directory are some of the topics covered in the exam.S2:E4 Understanding AI Developer Experiences with Leo Yao
This week in Model Mondays, we put the spotlight on the AI Toolkit for Visual Studio Code - and explore the tools and workflows that make building generative AI apps and agents easier for developers. Read on for my recap. This post was generated with AI help and human revision & review. To learn more about our motivation and workflows, please refer to this document in our website. About Model Mondays Model Mondays is a weekly series designed to help you grow your Azure AI Foundry Model IQ step by step. Each week includes: 5-Minute Highlights – Quick news and updates about Azure AI models and tools on Monday 15-Minute Spotlight – Deep dive into a key model, protocol, or feature on Monday 30-Minute AMA on Friday – Live Q&A with subject matter experts from the Monday livestream If you're looking to grow your skills with the latest in AI model development, this series is a great place to begin. Useful links: Register for upcoming livestreams Watch past episodes Join the AMA on AI Developer Experiences Visit the Model Mondays forum Spotlight On: AI Developer Experiences 1. What is this topic and why is it important? AI Developer Experiences focus on making the process of building, testing, and deploying AI models as efficient as possible. With the right tools—such as the AI Toolkit and Azure AI Foundry extensions for Visual Studio Code—developers can eliminate unnecessary friction and focus on innovation. This is essential for accelerating the real-world impact of generative AI. 2. What is one key takeaway from the episode? The integration of Azure AI Foundry with Visual Studio Code allows developers to manage models, run experiments, and deploy applications directly from their preferred development environment. This unified workflow enhances productivity and simplifies the AI development lifecycle. 3. How can I get started? Here are a few resources to explore: Install the AI Toolkit for VS Code Explore Azure AI Foundry Documentation Join the Microsoft Tech Community to follow and contribute to discussions 4. What’s New in Azure AI Foundry? Azure AI Foundry continues to evolve to meet developer needs with more power, flexibility, and productivity. Here are some of the latest updates highlighted in this week’s episode: AI Toolkit for Visual Studio Code Now with deeper integration, allowing developers to manage models, run experiments, and deploy applications directly within their editor—streamlining the entire workflow. Prompt Shields Enhanced security capabilities designed to protect generative AI applications from prompt injection and unsafe content, improving reliability in production environments. Model Router A new intelligent routing system that dynamically directs model requests to the most suitable model available—enhancing performance and efficiency at scale. Expanded Model Catalog The catalog now includes more open-source and proprietary models, featuring the latest from Hugging Face, OpenAI, and other leading providers. Improved Documentation and Sample Projects Newly added guides and ready-to-use examples to help developers get started faster, understand workflows, and build confidently. My A-Ha Moment Before watching this episode, setting up an AI development environment always felt like a challenge. There were so many moving parts—configurations, integrations, and dependencies—that it was hard to know where to begin. Seeing the AI Toolkit in action inside Visual Studio Code changed everything for me. It was a realization moment: “That’s it? I can explore models, test prompts, and deploy apps—without ever leaving my editor?” This episode made it clear that building with AI doesn’t have to be complex or intimidating. With the right tools, experimentation becomes faster and far more enjoyable. Now, I’m genuinely excited to build, test, and explore new generative AI solutions because the process finally feels accessible. Coming Up Next Week In the next episode, we’ll be exploring Fine-Tuning and Distillation with Dave Voutila. This session will focus on how to adapt Azure OpenAI models to your unique use cases and apply best practices for efficient knowledge transfer. Register here to reserve your spot and be part of the conversation. Join the Community Building in AI is better when we do it together. That’s why the Azure AI Developer Community exists—to support your journey and provide resources every step of the way. Join the Discord for real-time discussions, events, and peer learning Explore the Forum to catch up on AMAs, ask questions, and connect with other developers About Me I'm Sharda, a Gold Microsoft Learn Student Ambassador passionate about cloud technologies and artificial intelligence. I enjoy learning, building, and helping others grow in tech. Connect with me: LinkedIn GitHub Dev.to Microsoft Tech CommunityAll-in-One Content Creation with the New Microsoft 365 Dashboard
🎨 Discover the new Microsoft 365 Dashboard creation experience! In this video, I’ll walk you through the redesigned interface that makes it easier than ever to create and manage content—whether it’s images, posters, documents, videos, and more. Microsoft is transforming M365 into a true creative hub, perfect for both personal productivity and professional branding. ✅ Learn how to navigate the new dashboard ✅ Explore templates for visuals, documents, and multimedia ✅ See how AI and design tools integrate into your workflow ✅ Tips to boost your productivity with Microsoft 365 💬 Don’t forget to like, subscribe, and share your thoughts in the comments! 📌 Perfect for creators, marketers, educators, and business users. #Microsoft365 #ContentCreation #ProductivityTools #MicrosoftDashboard #M365Tips #Office365 #WorkSmarter #MicrosoftTemplates #DigitalCreativity #CreateWithMicrosoftMicrosoft Purview Data Loss Prevention AMA: What's New in Endpoint DLP?
Catch up on the latest innovations in Microsoft Purview Data Loss Prevention (DLP) for endpoint devices. In this session, you'll get to dive deeper into new capabilities & enhancements with our product experts. Have any burning questions? Following the demos, our experts will open up the floor for the AMA session. RSVP today to learn how to: Expand visibility and protection beyond Microsoft 365 Simplify the day-to-day admin experience Further strengthen existing DLP protections What is an AMA? An 'Ask Microsoft Anything' (AMA) session is an opportunity for you to engage directly with Microsoft employees! This AMA will consist of a short presentation followed by taking questions on-camera from the comment section down below! Ask your questions/give your feedback and we will have our awesome Microsoft Subject Matter Experts engaging and responding directly in the video feed. We know this timeslot might not work for everyone, so feel free to ask your questions at any time leading up to the event and the experts will do their best to answer during the live hour. This page will stay up so come back and use it as a resource anytime. We hope you enjoy! Scroll down to ask questions!This National Small Business Week, make sure everyone in your company understands AI
Whether you are running a startup or an already thriving small business, harnessing AI-driven solutions will help you discover new opportunities, streamline operations, and make data-driven decisions with confidence. Understanding and exploring the possibilities of AI is essential for small businesses and key to unlocking growth, driving innovation, and maintaining a competitive edge. The first step is understanding the potential of AI for your business. Microsoft has developed several online resources to help. In recognition of National Small Business Week, we have curated a list of those resources that may be helpful for small business professionals who want to get started with AI. Establish an AI foundation Start your AI journey by visiting the Microsoft WorkLab and examining a rich collection of content that addresses the real-world scenarios of how AI is impacting work today. New articles are regularly added that will help you understand not just AI’s high-level capabilities, but also the nuances of AI and how to directly apply AI to your day-to-day work. Key resources include: Up-to-date market research on all the ways that AI is impacting work, like our latest, the AI Data Drop. This study provides insights into how employees feel about AI and how long it takes most employees to build effective AI habits. Regular podcasts with business leaders, like our recent discussion with Bryan Hancock, McKinsey’s Global Talent Leader, on the different ways that managers can unlock AI’s potential for their teams. In-depth guides that detail how AI can help the different parts of your business, such as How Sellers Can Use AI to Better Engage with Customers and How Marketers Can Use AI to Unlock Breakthrough Creativity. Build your AI skills When you're ready to build a deeper AI skill, you explore the Microsoft AI Learning Hub. You’ll find a variety of tools to help you go from understanding AI to preparing for it. You can learn the mechanics of using the technology and even how to build it into your own apps and services. Start with the learning journey for Business Users, which is foundational for getting an underlying understanding of AI, and then move into a more detailed guidance on how to use and implement its capabilities. If you’re an IT professional, look at the learning journey for IT Professionals, which provides a thorough grounding on the particulars of AI adoption, deployment, and small business concerns, like data classification and regulatory considerations. To define your own path, get skilling recommendations based on your job responsibilities and objectives. No matter where you want to go, you can use the AI learning assessment to define a customized learning journey to get you there. Put AI to work To put your AI skills into practice or if you’re already using Copilot for Microsoft 365, visit the Microsoft Copilot Lab. This site provides easy, visual introductions into what Copilot is and how it helps you do more no matter which Microsoft 365 app you are using. These tools are designed for professionals that need a fast, tactical grounding so they can benefit from AI every day. One example is the prompt writing guide, which explains how to write effective prompts so Copilot can deliver exactly what you need. This toolkit teaches the art and science of prompting. It walks through a series of easy initial prompting exercises like writing an AI-powered email or creating an image, so you’ll understand how to edit a prompt to tailored it to your scenario. Microsoft Learn has a series of freely available, advanced courses to help you gain a deeper understanding of Copilot, how it works with the apps in Microsoft 365 and best practices for everyday use. Get started National Small Business Week may be an annual event, but you can build your AI skills year-round. Join the Microsoft SMB Tech Community to network with other professionals using Copilot. You can come here anytime to ask questions, get help, keep up with the latest AI news specific to small and medium-sized businesses and find out about upcoming online or local events.
