Announcing the IQ Series: Foundry IQ
AI agents are rapidly becoming a new way to build applications. But for agents to be truly useful, they need access to the knowledge and context that helps them reason about the world they operate in. That’s where Foundry IQ comes in. Today we’re announcing the IQ Series: Foundry IQ, a new set of developer-focused episodes exploring how to build knowledge-centric AI systems using Foundry IQ. The series focuses on the core ideas behind how modern AI systems work with knowledge, how they retrieve information, reason across sources, synthesize answers, and orchestrate multi-step interactions. Instead of treating retrieval as a single step in a pipeline, Foundry IQ approaches knowledge as something that AI systems actively work with throughout the reasoning process. The IQ Series breaks down these concepts and shows how they come together when building real AI applications. You can explore the series and all the accompanying samples here: 👉 https://aka.ms/iq-series What is Foundry IQ? Foundry IQ helps AI systems work with knowledge in a more structured and intentional way. Rather than wiring retrieval logic directly into every application, developers can define knowledge bases that connect to documents, data sources, and other information systems. AI agents can then query these knowledge bases to gather the context they need to generate responses, make decisions, or complete tasks. This model allows knowledge to be organized, reused, and combined across applications, instead of being rebuilt for each new scenario. What's covered in the IQ Series? The Foundry IQ episodes in the IQ Series explore the key building blocks behind knowledge-driven AI systems from how knowledge enters the system to how agents ultimately query and use it. The series is released as three weekly episodes: Foundry IQ: Unlocking Knowledge for Your Agents — March 18, 2026: Introduces Foundry IQ and the core ideas behind it. The episode explains how AI agents work with knowledge and walks through the main components of the Foundry IQ that support knowledge-driven applications. Foundry IQ: Building the Data Pipeline with Knowledge Sources — March 25, 2026: Focuses on Knowledge Sources and how different types of content flow into Foundry IQ. It explores how systems such as SharePoint, Fabric, OneLake, Azure Blob Storage, Azure AI Search, and the web contribute information that AI systems can later retrieve and use. Foundry IQ: Querying the Multi-Source AI Knowledge Bases — April 1, 2026: Dives into the Knowledge Bases and how multiple knowledge sources can be organized behind a single endpoint. The episode demonstrates how AI systems query across these sources and synthesize information to answer complex questions. Each episode includes a short executive introduction, a tech talk exploring the topic in depth, and a visual recap with doodle summaries of the key ideas. Alongside the episodes, the GitHub repository provides cookbooks with sample code, summary of the episodes, and additinal learning resources, so developers can explore the concepts and apply them in their own projects. Explore the Repo All episodes and supporting materials live in the IQ Series repository: 👉 https://aka.ms/iq-series Inside the repository you’ll find: The Foundry IQ episode links Cookbooks for each episode Links to documentation and additional resources If you're building AI agents or exploring how AI systems can work with knowledge, the IQ Series is a great place to start. Watch the episodes and explore the cookbooks! We’re excited to see what you build and welcome your feedback & ideas as the series evolves.Agents League: Two Weeks, Three Tracks, One Challenge
We're inviting all developers to join Agents League, running February 16-27. It's a two-week challenge where you'll build AI agents using production-ready tools, learn from live coding sessions, and get feedback directly from Microsoft product teams. We've put together starter kits for each track to help you get up and running quickly that also includes requirements and guidelines. Whether you want to explore what GitHub Copilot can do beyond autocomplete, build reasoning agents on Microsoft Foundry, or create enterprise integrations for Microsoft 365 Copilot, we have a track for you. Important: Register first to be eligible for prizes and your digital badge. Without registration, you won't qualify for awards or receive a badge when you submit. What Is Agents League? It's a 2-week competition that combines learning with building: 📽️ Live coding battles – Watch Product teams, MVPs and community members tackle challenges in real-time on Microsoft Reactor 💻 Async challenges – Build at your own pace, on your schedule 💬 Discord community – Connect with other participants, join AMAs, and get help when you need it 🏆 Prizes – $500 per track winner, plus GitHub Copilot Pro subscriptions for top picks The Three Tracks 🎨 Creative Apps — Build with GitHub Copilot (Chat, CLI, or SDK) 🧠 Reasoning Agents — Build with Microsoft Foundry 💼 Enterprise Agents — Build with M365 Agents Toolkit (or Copilot Studio) More details on each track below, or jump straight to the starter kits. The Schedule Agents League starts on February 16th and runs through Feburary 27th. Within 2 weeks, we host live battles on Reactor and AMA sessions on Discord. Week 1: Live Battles (Feb 17-19) We're kicking off with live coding battles streamed on Microsoft Reactor. Watch experienced developers compete in real-time, explaining their approach and architectural decisions as they go. Tue Feb 17, 9 AM PT — 🎨 Creative Apps battle Wed Feb 18, 9 AM PT — 🧠 Reasoning Agents battle Thu Feb 19, 9 AM PT — 💼 Enterprise Agents battle All sessions are recorded, so you can watch on your own schedule. Week 2: Build + AMAs (Feb 24-26) This is your time to build and ask questions on Discord. The async format means you work when it suits you, evenings, weekends, whatever fits your schedule. We're also hosting AMAs on Discord where you can ask questions directly to Microsoft experts and product teams: Tue Feb 24, 9 AM PT — 🎨 Creative Apps AMA Wed Feb 25, 9 AM PT — 🧠 Reasoning Agents AMA Thu Feb 26, 9 AM PT — 💼 Enterprise Agents AMA Bring your questions, get help when you're stuck, and share what you're building with the community. Pick Your Track We've created a starter kit for each track with setup guides, project ideas, and example scenarios to help you get started quickly. 🎨 Creative Apps Tool: GitHub Copilot (Chat, CLI, or SDK) Build innovative, imaginative applications that showcase the potential of AI-assisted development. All application types are welcome, web apps, CLI tools, games, mobile apps, desktop applications, and more. The starter kit walks you through GitHub Copilot's different modes and provides prompting tips to get the best results. View the Creative Apps starter kit. 🧠 Reasoning Agents Tool: Microsoft Foundry (UI or SDK) and/or Microsoft Agent Framework Build a multi-agent system that leverages advanced reasoning capabilities to solve complex problems. This track focuses on agents that can plan, reason through multi-step problems, and collaborate. The starter kit includes architecture patterns, reasoning strategies (planner-executor, critic/verifier, self-reflection), and integration guides for tools and MCP servers. View the Reasoning Agents starter kit. 💼 Enterprise Agents Tool: M365 Agents Toolkit or Copilot Studio Create intelligent agents that extend Microsoft 365 Copilot to address real-world enterprise scenarios. Your agent must work on Microsoft 365 Copilot Chat. Bonus points for: MCP server integration, OAuth security, Adaptive Cards UI, connected agents (multi-agent architecture). View the Enterprise Agents starter kit. Prizes & Recognition To be eligible for prizes and your digital badge, you must register before submitting your project. Category Winners ($500 each): 🎨 Creative Apps winner 🧠 Reasoning Agents winner 💼 Enterprise Agents winner GitHub Copilot Pro subscriptions: Community Favorite (voted by participants on Discord) Product Team Picks (selected by Microsoft product teams) Everyone who registers and submits a project wins: A digital badge to showcase their participation. Beyond the prizes, every participant gets feedback from the teams who built these tools, a valuable opportunity to learn and improve your approach to AI agent development. How to Get Started Register first — This is required to be eligible for prizes and to receive your digital badge. Without registration, your submission won't qualify for awards or a badge. Pick a track — Choose one track. Explore the starter kits to help you decide. Watch the battles — See how experienced developers approach these challenges. Great for learning even if you're still deciding whether to compete. Build your project — You have until Feb 27. Work on your own schedule. Submit via GitHub — Open an issue using the project submission template. Join us on Discord — Get help, share your progress, and vote for your favorite projects on Discord. Links Register: https://aka.ms/agentsleague/register Starter Kits: https://github.com/microsoft/agentsleague/starter-kits Discord: https://aka.ms/agentsleague/discord Live Battles: https://aka.ms/agentsleague/battles Submit Project: Project submission templateRethinking Documentation Translation: Treating Translations as Versioned Software Assets
Rethinking Documentation Translation: Treating Translations as Versioned Software Assets This article is written from the perspective of maintaining large, open-source documentation repositories in the Microsoft ecosystem. I am the maintainer of Co-op Translator, an open-source tool for automating multilingual documentation translation, used across multiple large documentation repositories, including Microsoft’s For Beginners series. In large documentation repositories, translation problems rarely fail loudly. They fail quietly, and they accumulate over time. Recently, we made a fundamental design decision in how Co-op Translator handles translations. Translations are treated as versioned software assets, not static outputs. This article explains why we reached that conclusion, and what this perspective enables for teams maintaining large, fast-moving documentation repositories. When translations quietly become a liability In most documentation projects, translations are treated as finished outputs. Once a file is translated, it is assumed to remain valid until someone explicitly notices a problem. But documentation rarely stands still. Text changes. Code examples evolve. Screenshots are replaced. Notebooks are updated to reflect new behavior. The problem is that these changes are often invisible in translated content. A translation may still read fluently, while the information it contains is already out of date. At that point, the issue is no longer about translation quality. It becomes a maintenance problem. Reframing the question Most translation workflows implicitly ask: Is this translation correct? In practice, maintainers struggle with a different question: Is this translation still synchronized with the current source? This distinction matters. A translation can be correct and still be out of sync. Once we acknowledged this, it became clear that treating translations as static content was no longer sufficient. The design decision: translations as versioned assets Starting with Co-op Translator 0.16.2, we made a deliberate design decision: Translations are treated as versioned software assets. This applies not only to Markdown files, but also to images, notebooks, and any other translated artifacts. Translated content is not just text. It is an artifact generated from a specific version of a source. To make this abstraction operational rather than theoretical, we did not invent a new mechanism. Instead, we looked to systems that already solve a similar problem: pip, poetry, and npm. These tools are designed to track artifacts as their sources evolve. We applied the same thinking to translated content. Closer to dependency management than translation jobs The closest analogy is software dependency management. When a dependency becomes outdated: it is not suddenly “wrong,” it is simply no longer aligned with the current version. Translations behave the same way. When the source document changes: the translated file does not immediately become incorrect, it becomes out of sync with its source version. This framing shifts the problem away from translation output and toward state and synchronization. Why file-level versioning matters Many translation systems operate at the string or segment level. That model works well for UI text and relatively stable resources. Documentation is different. A Markdown file is an artifact. A screenshot is an artifact. A notebook is an artifact. They are consumed as units, not as isolated strings. Managing translation state at the file level allows maintainers to reason about translations using the same mental model they already apply to other repository assets. What changed in practice From embedded markers to explicit state Previously, translation metadata lived inside translated files as embedded comments or markers. This approach had clear limitations: translation state was fragmented, difficult to inspect globally, and easy to miss as repositories grew. We moved to language-scoped JSON state files that explicitly track: the source version, the translated artifact, and its synchronization status. Translation state is no longer hidden inside content. It is a first-class, inspectable part of the repository. Extending the model to images and notebooks The same model now applies consistently to: translated images, localized notebooks, and other non-text artifacts. If an image changes in the source language, the translated image becomes out of sync. If a notebook is updated, its translated versions are evaluated against the new source version. The format does not matter. The lifecycle does. Once translations are treated as versioned assets, the system remains consistent across all content types. What this enables This design enables: Explicit drift detection See which translations are out of sync without guessing. Consistent maintenance signals Text, images, and notebooks follow the same rules. Clear responsibility boundaries The system reports state. Humans decide action. Scalability for fast-moving repositories Translation maintenance becomes observable, not reactive. In large documentation sets, this difference determines whether translation maintenance is sustainable at all. What this is not This system does not: judge translation quality, determine semantic correctness, or auto-approve content. It answers one question only: Is this translated artifact synchronized with its source version? Who this is for This approach is designed for teams that: maintain multilingual documentation, update content frequently, and need confidence in what is actually up to date. When documentation evolves faster than translations, treating translations as versioned assets becomes a necessity, not an optimization. Closing thought Once translations are modeled as software assets, long-standing ambiguities disappear. State becomes visible. Maintenance becomes manageable. And translations fit naturally into existing software workflows. At that point, the question is no longer whether translation drift exists, but: Can you see it? Reference Co-op Translator repository https://github.com/Azure/co-op-translatorLeverage AI for faster, more productive coding with GitHub Copilot
GitHub Copilot serves as an invaluable learning tool for developers, especially those who are still learning a particular programming language or framework. By providing context-aware suggestions, it helps learners understand the syntax, structure, and logic behind different code snippets. While fundamental knowledge of programming concepts and syntax services should remain a prerequisite, a developer exploring a new framework would be able to describe the functionality they want to implement, and GitHub Copilot will generate code that demonstrates how to achieve it. This accelerates the learning process and empowers developers to gain proficiency in new technologies more efficiently.AI Dev Days 2025: Your Gateway to the Future of AI Development
What’s in Store? Day 1 – 10 December: Video Link Building AI Applications with Azure, GitHub, and Foundry Explore cutting-edge topics like: Agentic DevOps Azure SRE Agent Microsoft Foundry MCP Models for AI innovation Day 2 – 11 December Agenda: Video Link Using AI to Boost Developer Productivity Get hands-on with: Agent HQ VS Code & Visual Studio 2026 GitHub Copilot Coding Agent App Modernisation Strategies Why Join? Hands-on Labs: Apply the latest product features immediately. Highlights from Microsoft Ignite & GitHub Universe 2025: Stay ahead of the curve. Global Reach: Local-language workshops for LATAM and EMEA coming soon. You’ll recognise plenty of familiar faces in the lineup – don’t miss the chance to connect and learn from the best! 👉 Register now and share widely across your networks – there’s truly something for everyone! https://aka.ms/ai-dev-days
Amazing opportunity provided by MICROSOFT
Hi everyone recently I had found an amazing opportunity provided by Microsoft to the learn which most of us don't know please share this opportunity in your connection so that they also get benefited. https://learn.microsoft.com/en-us/training/browse/?resource_type=course&wt.mc_id=studentamb_478312 Thank youAMA Spotlight: Build Smarter with Azure Developer CLI 'AZD'
Weekly AMA 'Ask Me Anything': Build Smarter with Azure Developer CLI Calling all AI engineers, developers, and builders of the future, this is your backstage pass to the tools shaping scalable, agentic AI deployments. Join Kristen Womack, Product Manager for the Azure Developer CLI (azd) Developer CLI (azd), and the engineering team behind azd for a live Ask Me Anything session every Thursday at 12:30pm PT in the Azure AI Foundry Discord. Whether you're: 🧠 Orchestrating multi-agent systems 📦 Deploying LLM-powered apps with Azure AI Foundry 🔐 Navigating least-privilege infrastructure setups 🛠️ Debugging and optimizing reproducible workflows …this AMA is your chance to connect directly with the team building the CLI that powers it all. 💡 Why Join? Real-time answers from the azd engineers and product team Deployment walkthroughs for Foundry templates, from chatbots to document processors Tips for CI/CD, debugging, and reproducibility in enterprise environments Community-first mindset: bring your feedback, challenges, and ideas Kristen Womack brings deep insight into developer experience and product strategy; this is a rare opportunity to learn from the source and shape the future of AI tooling. 🔧 Get Ready Before you join: Install azd 👉 Install Guide Explore Kristen’s work 👉 www.kristenwomack.io Join the Discord 👉 Azure AI Foundry Community 🗓️ Weekly Schedule 🕧 Thursdays at 12:30pm PT 📍 Azure AI Foundry Discord Bring your questions. Bring your curiosity. Build with the best. Additional resources: check out the AZD for Beginners course https://aka.ms/azd-for-beginnersEssential Microsoft Resources for MVPs & the Tech Community from the AI Tour
Unlock the power of Microsoft AI with redeliverable technical presentations, hands-on workshops, and open-source curriculum from the Microsoft AI Tour! Whether you’re a Microsoft MVP, Developer, or IT Professional, these expertly crafted resources empower you to teach, train, and lead AI adoption in your community. Explore top breakout sessions covering GitHub Copilot, Azure AI, Generative AI, and security best practices—designed to simplify AI integration and accelerate digital transformation. Dive into interactive workshops that provide real-world applications of AI technologies. Take it a step further with Microsoft’s Open-Source AI Curriculum, offering beginner-friendly courses on AI, Machine Learning, Data Science, Cybersecurity, and GitHub Copilot—perfect for upskilling teams and fostering innovation. Don’t just learn—lead. Access these resources, host impactful training sessions, and drive AI adoption in your organization. Start sharing today! Explore now: Microsoft AI Tour Resources.Practical ways to use AI in your Data Science and ML journey
Are you ready to take your learning from “just reading” to “actively doing”? We are launching a series of interactive events designed to help you bridge the gap between theory and practice, connect with peers, and learn directly from experts, all in a vibrant, supportive Discord community. The series will guide you on practical ways to use AI in your learning journey with Data Science and Machine Learning. Join the series on Discord at: https://aka.ms/ds4beginners/discord Why You Should Join Guided Pathways: Move seamlessly from the popular Data Science for Beginners and Machine Learning for Beginners curriculums to interact with fellow learners in the Azure AI Foundry Discord community. We’ve designed study plans, office hours sessions, and showcases so you can learn, ask questions, and get feedback in real time. Practical AI Skills: See how Artificial Intelligence can supercharge your learning. . Community & Collaboration: Find peer learners with similar goals, collaborate on projects, and get support from experienced moderators and MVPs. Machine Learning AMA 1 Theme: Learning Machine Learning with AI, responsibly. Date: Tuesday, 23 September (10AM PST | 1PM ET | 5PM GMT | 8PM EAT) What to Expect: Curriculum overview, hands-on AI demos, critique and correct a simple classifier, and peer collaboration. Link: https://aka.ms/learnwithai/ml Data Science AMA 2 Theme: Learning Data Science with AI, responsibly. Date: Tuesday, 30 September (10AM PST | 1PM ET | 5PM GMT | 8PM EAT) What to Expect: Curriculum overview, integrating AI into your learning, live Q&A, and practical tips for responsible AI use. Link: https://aka.ms/learnwithai/ds Showcase 1: GitHub Copilot for Data Science Theme: Hands-on AI Agents for Data Scientists Date: Thursday, 25 September (10AM PST | 1PM ET | 5PM GMT | 8PM EAT) What to Expect: Learn to use Copilot’s advanced features in Python and Jupyter Notebooks, customize agents, and extend your analyses. Link: https://aka.ms/learnwithai/agents How to Get Involved Join the Discord Channels: https://aka.ms/ds4beginners/discord https://aka.ms/ml4beginners/discord Prepare: Make sure you have a GitHub account, VS Code, Data Wrangler, ready for hands-on sessions. What Makes This Program Different? Discord first learning: Experience higher engagement and deeper connections. Curriculum-anchored activities: Every event is designed to build on what you’ve learned in the open-source curriculums. AI-powered study plans and resources: Get starter notebooks, prompt cards, and recap templates to accelerate your progress. Resources Hands-on workshop: https://aka.ms/ds-agents Data Science for beginner's curriculum: https://aka.ms/ds4beginners Machine Learning for beginner's curriculum: https://aka.ms/ml4beginners Ready to transform your learning journey? Join us for these exciting events and join us in the Azure AI Foundry Discord community. Whether you’re just starting out or looking to deepen your skills, there’s a place for you here!Announcing MSGraph Provider Public Preview and the Microsoft Terraform VSCode Extension
We are thrilled to announce two exciting developments in the Microsoft ecosystem for Terraform infrastructure-as-code (IaC) practitioners: the public preview of the Terraform Microsoft Graph (MSGraph) provider and the release of the Microsoft Terraform Visual Studio Code (VSCode) extension. These innovations are designed to streamline your workflow, empower your automation, and make managing Microsoft cloud resources easier than ever. Public Preview: Terraform Microsoft Graph (MSGraph) Provider The Terraform MSGraph provider empowers you to manage Entra APIs like privileged identity management as well as M365 Graph APIs like SharePoint sites from day 0 by leveraging the power and flexibility of HashiCorp Configuration Language (HCL) in Terraform. resource "msgraph_resource" "application" { url = "applications" body = { displayName = "My Application" } response_export_values = { all = "@" app_id = "appId" } } output "app_id" { value = msgraph_resource.application.output.app_id } output "all" { // it will output the whole response value = msgraph_resource.application.output.all } Historically, Terraform users could utilize the `azuread` provider to manage Entra features like users, groups, service principals, and applications. The new `msgraph` provider also supports these features and extends functionality to all beta and v1 Microsoft Graph endpoints. Querying role assignments for a service principal The below example shows how to use the `msgraph` provider to grant app permissions to a service principal: locals { MicrosoftGraphAppId = "00000003-0000-0000-c000-000000000000" # AppRoleAssignment userReadAllAppRoleId = one([for role in data.msgraph_resource.servicePrincipal_msgraph.output.all.value[0].appRoles : role.id if role.value == "User.Read.All"]) userReadWriteRoleId = one([for role in data.msgraph_resource.servicePrincipal_msgraph.output.all.value[0].oauth2PermissionScopes : role.id if role.value == "User.ReadWrite"]) # ServicePrincipal MSGraphServicePrincipalId = data.msgraph_resource.servicePrincipal_msgraph.output.all.value[0].id TestApplicationServicePrincipalId = msgraph_resource.servicePrincipal_application.output.all.id } data "msgraph_resource" "servicePrincipal_msgraph" { url = "servicePrincipals" query_parameters = { "$filter" = ["appId eq '${local.MicrosoftGraphAppId}'"] } response_export_values = { all = "@" } } resource "msgraph_resource" "application" { url = "applications" body = { displayName = "My Application" requiredResourceAccess = [ { resourceAppId = local.MicrosoftGraphAppId resourceAccess = [ { id = local.userReadAllAppRoleId type = "Scope" }, { id = local.userReadWriteRoleId type = "Scope" } ] } ] } response_export_values = { appId = "appId" } } resource "msgraph_resource" "servicePrincipal_application" { url = "servicePrincipals" body = { appId = msgraph_resource.application.output.appId } response_export_values = { all = "@" } } resource "msgraph_resource" "appRoleAssignment" { url = "servicePrincipals/${local.MSGraphServicePrincipalId}/appRoleAssignments" body = { appRoleId = local.userReadAllAppRoleId principalId = local.TestApplicationServicePrincipalId resourceId = local.MSGraphServicePrincipalId } } SharePoint & Outlook Notifications With your service principals properly configured, you can set up M365 endpoint workflows such an outlook notification template list as shown below. The actual service principal setup has been omitted from this code sample for the sake of brevity, but you will need Sites.Manage.All, Sites.ReadWrite.All, User.Read, and User.Read.All permissions for this example to work: data "msgraph_resource" "sharepoint_site_by_path" { url = "sites/microsoft.sharepoint.com:/sites/msgraphtest:" response_export_values = { full_response = "@" site_id = "id || ''" } } resource "msgraph_resource" "notification_templates_list" { url = "sites/${msgraph_resource.sharepoint_site_by_path.output.site_id}/lists" body = { displayName = "DevOps Notification Templates" description = "Centrally managed email templates for DevOps automation" template = "genericList" columns = [ { name = "TemplateName" text = { allowMultipleLines = false appendChangesToExistingText = false linesForEditing = 1 maxLength = 255 } }, { name = "Subject" text = { allowMultipleLines = false appendChangesToExistingText = false linesForEditing = 1 maxLength = 500 } }, { name = "HtmlBody" text = { allowMultipleLines = true appendChangesToExistingText = false linesForEditing = 10 maxLength = 10000 } }, { name = "Recipients" text = { allowMultipleLines = true appendChangesToExistingText = false linesForEditing = 3 maxLength = 1000 } }, { name = "TriggerConditions" text = { allowMultipleLines = true appendChangesToExistingText = false linesForEditing = 5 maxLength = 2000 } } ] } response_export_values = { list_id = "id" list_name = "displayName" web_url = "webUrl" } } The MSGraph provider is to AzureAD as the AzAPI provider is to AzureRM. Since support for resource types is automatic, you can access the latest features and functionality as soon as they're released via the provider. AzureAD will continue to serve as the convenience layer implementation of a subset of Entra APIs. We invite you to try the new provider today: - Deploy your first msgraph resources - Check out the registry page - Visit the provider GitHub Introducing the Microsoft Terraform VSCode Extension The new official Microsoft Terraform extension for Visual Studio Code consolidates AzureRM, AzAPI, and MSGraph VSCode support into a single powerful extension. The extension supports exporting Azure resources as Terraform code, as well as IntelliSense, syntax highlighting, and code sample generation. It replaces the Azure Terraform and AzAPI VSCode extensions and adds some new features. Installation & Migration New users can install the extension by searching “Microsoft Terraform” within Visual Studio Marketplace or their “Extensions” tab. Users can also click this link to the Visual Studio marketplace. Users of the “Azure Terraform” extension can navigate to “Extensions” tab and selecting the old extension. Select the “Migrate” button to move to the new extension. Users of the “Terraform AzAPI Provider” extension will be directed to the new extension: New Features Export Azure Resources As Terraform This feature allows you to export existing Azure resources as Terraform configuration blocks using Azure Export for Terraform. This helps you migrate existing Azure resources to Terraform-managed infrastructure. Open the Command Palette (Command+Shift+P on macOS and Ctrl+Shift+P on Windows/Linux). Search for and select the command Microsoft Terraform: Export Azure Resource as Terraform. Follow the prompts to select the Azure subscription and resource group containing the resources you want to export. Select the azurerm provider or the azapi provider to export the resources. The extension will generate the Terraform configuration blocks for the selected resources and display them in a new editor tab. Support for MSGraph The new extension comes fully equipped with intellisense, code completion, and code samples just like the AzAPI provider. See the next section for recorded examples of these features within the AzureRM & AzAPI providers. Preexisting Features Intelligent Code Completion: Benefit from context-aware suggestions, like property names or resource types. Code Samples: Quickly insert code samples for your resources: Paste as AzAPI: Copy your existing resource JSON or ARM Templates into VSCode with the Microsoft Terraform extension, and it will automatically convert your code into AzAPI. The below example takes a resource JSON from the Azure Portal and pastes it into VSCode as AzAPI: Migrate AzureRM to AzAPI: Move existing AzureRM code to the AzAPI provider whenever you wish to. Read more in the Guide to migrate AzureRM resources to AzAPI Feedback We value your feedback! You can share your experience with the Microsoft Terraform extension by running the command Microsoft Terraform: Show Survey from the Command Palette. Your input helps us improve the extension and better serve your needs. Conclusion Whether you are managing traditional Azure resources, modern Microsoft Graph environments, or a combination of both, the new MSGraph provider and Microsoft Terraform VS Code extension are designed to help you deliver robust, reliable infrastructure—faster and with greater confidence. Stay tuned for further updates, workshops, and community events as we continue to evolve these offerings. Your feedback and participation are invaluable as we build the next generation of infrastructure automation together.
