Introducing Azure Local: cloud infrastructure for distributed locations enabled by Azure Arc
Today at Microsoft Ignite 2024 we're introducing Azure Local, cloud-connected infrastructure that can be deployed at your physical locations and under your operational control. With Azure Local, you can run the foundational Azure compute, networking, storage, and application services locally on hardware from your preferred vendor, providing flexibility to meet your requirements and budget.Introducing Azure AI Agent Service
Introducing Azure AI Agent Service at Microsoft Ignite 2024 Discover how Azure AI Agent Service is revolutionizing the development and deployment of AI agents. This service empowers developers to build, deploy, and scale high-quality AI agents tailored to business needs within hours. With features like rapid development, extensive data connections, flexible model selection, and enterprise-grade security, Azure AI Agent Service sets a new standard in AI automation
Introducing Local emulator for Azure Service Bus
Azure Service Bus is a fully managed enterprise message broker offering queues and publish-subscribe topics. It decouples applications and services, providing benefits like load-balancing across workers, safe data and control routing, and reliable transactional coordination. In response to your feedback, we are pleased to announce the introduction of a local emulator for Azure Service Bus. This emulator is intended to facilitate local development experience for Service Bus, allowing developers to develop and test their code against Azure Service Bus, in isolation away from cloud interference. Why emulator? Developers across the globe love emulators! While there are numerous compelling reasons to use emulators, here are just a few of those reasons to consider: Optimized development loop: The emulator speeds up dev/testing against Azure Service Bus. Pre-migration trial: Try Azure Service Bus using your existing AMQP applications before migrating to the cloud. Isolated environment: Use the emulator for dev/test setup without network latency or cloud resource constraints. Cost-efficient: The emulator is free and can be run on your local machine for dev/test scenarios. Note: The emulator is intended only for development and testing. It should not be used for production workloads. Official support is not provided, and any issues or suggestions should be reported via GitHub. Get started with Service Bus emulator The emulator is accessible as a Docker image on Microsoft Artifact Registry, and it is platform-independent, capable of running on Windows, macOS, and Linux. You can use our automated scripts from the Installer repository or initiate the emulator container using the docker compose command. The emulator is compatible with the latest service bus client SDKs and supports a wide variety of features within Azure Service Bus. For more details, please visit aka.ms/servicebusemulator Read more about Azure Service Bus: Introduction to Azure Service Bus, an enterprise message broker - Azure Service Bus | Microsoft Learn We appreciate your feedback and encourage you to share it with us. Please provide feedback or report any issues on our GitHub repository. Wishing you a smooth ride with the Service Bus emulator, making all your tests pass! 😊Announcing General Availability: Windows Server Management enabled by Azure Arc
Windows Server Management enabled by Azure Arc offers customers with Windows Server licenses that have active Software Assurances or Windows Server licenses that are active subscription licenses the following key benefits: Azure Update Manager Azure Change Tracking and Inventory Azure Machine Configuration Windows Admin Center in Azure for Arc Remote Support Network HUD Best Practices Assessment Azure Site Recovery (Configuration Only) Upon attestation, customers receive access to the following at no additional cost beyond associated networking, compute, storage, and log ingestion charges. These same capabilities are also available for customers enrolled in Windows Server 2025 Pay as you Go licensing enabled by Azure Arc. Learn more at Windows Server Management enabled by Azure Arc - Azure Arc | Microsoft Learn or watch Video: Free Azure Services for Non-Azure Windows Servers Covered by SA Powered by Azure Arc! To get started, connect your servers to Azure Arc, attest for these benefits, and deploy management services as you modernize to Azure's AI-enabled set of server management capabilities across your hybrid, multi-cloud, and edge infrastructure!Unlock New AI and Cloud Potential with .NET 9 & Azure: Faster, Smarter, and Built for the Future
.NET 9, now available to developers, marks a significant milestone in the evolution of the .NET platform, pushing the boundaries of performance, cloud-native development, and AI integration. This release, shaped by contributions from over 9,000 community members worldwide, introduces thousands of improvements that set the stage for the future of application development. With seamless integration with Azure and a focus on cloud-native development and AI capabilities, .NET 9 empowers developers to build scalable, intelligent applications with unprecedented ease. Expanding Azure PaaS Support for .NET 9 With the release of .NET 9, a comprehensive range of Azure Platform as a Service (PaaS) offerings now fully support the platform’s new capabilities, including the latest .NET SDK for any Azure developer. This extensive support allows developers to build, deploy, and scale .NET 9 applications with optimal performance and adaptability on Azure. Additionally, developers can access a wealth of architecture references and sample solutions to guide them in creating high-performance .NET 9 applications on Azure’s powerful cloud services: Azure App Service: Run, manage, and scale .NET 9 web applications efficiently. Check out this blog to learn more about what's new in Azure App Service. Azure Functions: Leverage serverless computing to build event-driven .NET 9 applications with improved runtime capabilities. Azure Container Apps: Deploy microservices and containerized .NET 9 workloads with integrated observability. Azure Kubernetes Service (AKS): Run .NET 9 applications in a managed Kubernetes environment with expanded ARM64 support. Azure AI Services and Azure OpenAI Services: Integrate advanced AI and OpenAI capabilities directly into your .NET 9 applications. Azure API Management, Azure Logic Apps, Azure Cognitive Services, and Azure SignalR Service: Ensure seamless integration and scaling for .NET 9 solutions. These services provide developers with a robust platform to build high-performance, scalable, and cloud-native applications while leveraging Azure’s optimized environment for .NET. Streamlined Cloud-Native Development with .NET Aspire .NET Aspire is a game-changer for cloud-native applications, enabling developers to build distributed, production-ready solutions efficiently. Available in preview with .NET 9, Aspire streamlines app development, with cloud efficiency and observability at its core. The latest updates in Aspire include secure defaults, Azure Functions support, and enhanced container management. Key capabilities include: Optimized Azure Integrations: Aspire works seamlessly with Azure, enabling fast deployments, automated scaling, and consistent management of cloud-native applications. Easier Deployments to Azure Container Apps: Designed for containerized environments, .NET Aspire integrates with Azure Container Apps (ACA) to simplify the deployment process. Using the Azure Developer CLI (azd), developers can quickly provision and deploy .NET Aspire projects to ACA, with built-in support for Redis caching, application logging, and scalability. Built-In Observability: A real-time dashboard provides insights into logs, distributed traces, and metrics, enabling local and production monitoring with Azure Monitor. With these capabilities, .NET Aspire allows developers to deploy microservices and containerized applications effortlessly on ACA, streamlining the path from development to production in a fully managed, serverless environment. Integrating AI into .NET: A Seamless Experience In our ongoing effort to empower developers, we’ve made integrating AI into .NET applications simpler than ever. Our strategic partnerships, including collaborations with OpenAI, LlamaIndex, and Qdrant, have enriched the AI ecosystem and strengthened .NET’s capabilities. This year alone, usage of Azure OpenAI services has surged to nearly a billion API calls per month, illustrating the growing impact of AI-powered .NET applications. Real-World AI Solutions with .NET: .NET has been pivotal in driving AI innovations. From internal teams like Microsoft Copilot creating AI experiences with .NET Aspire to tools like GitHub Copilot, developed with .NET to enhance productivity in Visual Studio and VS Code, the platform showcases AI at its best. KPMG Clara is a prime example, developed to enhance audit quality and efficiency for 95,000 auditors worldwide. By leveraging .NET and scaling securely on Azure, KPMG implemented robust AI features aligned with strict industry standards, underscoring .NET and Azure as the backbone for high-performing, scalable AI solutions. Performance Enhancements in .NET 9: Raising the Bar for Azure Workloads .NET 9 introduces substantial performance upgrades with over 7,500 merged pull requests focused on speed and efficiency, ensuring .NET 9 applications run optimally on Azure. These improvements contribute to reduced cloud costs and provide a high-performance experience across Windows, Linux, and macOS. To see how significant these performance gains can be for cloud services, take a look at what past .NET upgrades achieved for Microsoft’s high-scale internal services: Bing achieved a major reduction in startup times, enhanced efficiency, and decreased latency across its high-performance search workflows. Microsoft Teams improved efficiency by 50%, reduced latency by 30–45%, and achieved up to 100% gains in CPU utilization for key services, resulting in faster user interactions. Microsoft Copilot and other AI-powered applications benefited from optimized runtime performance, enabling scalable, high-quality experiences for users. Upgrading to the latest .NET version offers similar benefits for cloud apps, optimizing both performance and cost-efficiency. For more information on updating your applications, check out the .NET Upgrade Assistant. For additional details on ASP.NET Core, .NET MAUI, NuGet, and more enhancements across the .NET platform, check out the full Announcing .NET 9 blog post. Conclusion: Your Path to the Future with .NET 9 and Azure .NET 9 isn’t just an upgrade—it’s a leap forward, combining cutting-edge AI integration, cloud-native development, and unparalleled performance. Paired with Azure’s scalability, these advancements provide a trusted, high-performance foundation for modern applications. Get started by downloading .NET 9 and exploring its features. Leverage .NET Aspire for streamlined cloud-native development, deploy scalable apps with Azure, and embrace new productivity enhancements to build for the future. For additional insights on ASP.NET, .NET MAUI, NuGet, and more, check out the full Announcing .NET 9 blog post. Explore the future of cloud-native and AI development with .NET 9 and Azure—your toolkit for creating the next generation of intelligent applications.Announcing Azure HBv5 Virtual Machines: A Breakthrough in Memory Bandwidth for HPC
Discover the new Azure HBv5 Virtual Machines, unveiled at Microsoft Ignite, designed for high-performance computing applications. With up to 7 TB/s of memory bandwidth and custom 4th Generation EPYC processors, these VMs are optimized for the most memory-intensive HPC workloads. Sign up for the preview starting in the first half of 2025 and see them in action at Supercomputing 2024 in AtlantaAnnouncing comprehensive guidance for AI adoption and architecture
The pace of AI innovation is moving incredibly fast with new models and solutions emerging regularly. To meet the pace of technological advancements, organizations are striving to meet the demand for scalable, efficient AI solutions. The rapidity of change places enormous pressure on organizations to scale quickly while also ensuring reliability, security, performance and cost-efficiency needs are met along the way. According to Rand Research, over 80% of early AI adoptions fail because customers miss critical steps in preparing their organizations to consider all aspects of building and running AI workloads. Microsoft is committed to helping organizations successfully navigate this journey of cloud and AI transformation. Over the past 18 months, Microsoft has published design patterns, baseline reference architectures, application landing zones, and a variety of Azure service guides for Azure OpenAI workloads. We have also developed specific financial best practices, as well as pricing and cost management features to make it easier to optimize AI investments. This guidance and features have been pulled together within Azure Essentials. Azure Essentials brings together curated best practices and product experiences from customers and partners along with reference architectures, skilling, tools, and resources into a single destination to help you maximize the value of your cloud investments. The Azure Essentials resource kit includes detailed guidance tailored to specific use cases and business scenarios including achieving secure migration, activating your data for AI innovation, and building and modernizing AI applications. As you prepare to adopt AI at scale, the guidance within the Azure Essentials resource kit helps you become AI-ready. This week, we are excited to announce industry-leading guidance for AI adoption and architectural design. This guidance ties together all of the content from the past 18 months into a comprehensive methodical approach that sets up the organization for AI success, while ensuring that AI workloads are well-architected. Through thousands of customer engagements focused on AI adoption, teams of Microsoft cloud solution architects, product engineers and content developers have developed specific guidance for the Microsoft Cloud Adoption Framework for Azure (CAF) and Microsoft Azure Well-Architected Framework (WAF). As a result, all of the recommendations and best practices are based on customer-proven experience that future customers can count on. New: Cloud Adoption Framework (CAF) – AI scenario The AI scenario within the Cloud Adoption Framework provides prescriptive guidance that prepares organizations to adopt AI at scale. Over the past nine months, we’ve had over 100 Microsoft’s solution architects contribute their AI adoption knowledge to this guidance. The result of this collaboration is a roadmap comprised of checklists that are segmented for “Startups” or “Enterprises”. These checklists make it possible to start your adoption at any phase, while also double-checking that you haven’t missed anything along the way. One hallmark of this guidance is the technology strategy decision tree. It provides very succinct and consumable logic to decide which AI technology works best for your specific AI strategy. To see the full tree, click on this link. Most (if not all) customers want to implement and adopt AI responsibly. The ramifications and risk of not doing so are just too costly. Thus, the CAF methodologies have also been adapted to Responsible AI principles so organizations can build an AI foundation that supports the design, governance, and ongoing management of responsible AI workloads. It helps users with everything from developing an adoption strategy through managing AI workloads in production. NEW: Well-Architected Framework (WAF) – AI workloads The AI workload guidance within the Azure Well-Architected Framework is a new set of best practices that allows AI architects to meet the functional and non-functional requirements for reliability, security, performance efficiency, operational excellence, and cost optimization. Designed to instill confidence in workload teams to make intelligent decisions when designing their AI workloads, the new WAF guidance for AI workloads takes a broader view covering architectural considerations at all levels of the stack, including infrastructure, data layers, and application logic. Thus, you’ll find guidance about each of the WAF pillars blended into all levels. The WAF AI enhancements we’re announcing this week build upon the Azure Well-Architected Framework refresh we launched last year. We’ve added checklists and tradeoffs to all pillars which helps make the guidance more actionable for workload teams, including solution architects, DevOps engineers, and data scientists. And the WAF components are more actionable through workload designs, reference architectures, assessments, Azure Advisor recommendations, and Azure service guides. The WAF AI workload guidance also covers both traditional machine learning and generative AI architectures – ensuring comprehensive support for your AI projects. Prepare to scale your AI adoption We are confident that this comprehensive guidance will support your organization in building and deploying AI solutions responsibly and effectively. Stay tuned for more updates and resources to help you on your AI adoption journey. The CAF and WAF AI adoption and architecture guidance makes it possible to adopt AI at scale while fully aligning to Trustworthy AI principles. This guidance is also embedded within Azure Essentials which provides detailed step-by-step guidance through the AI adoption journey, thus providing organizations with a clear path to maximize the value of their AI investment. As you prepare to become AI-ready, these are some great resources to get you started. Access the Cloud Adoption Framework for AI scenario documentation to get the guidance you need to ensure you’re ready to adopt AI at scale. Leverage the Azure Well-Architected Framework for AI workloads documentation to obtain the necessary guidance to securely design, build and manage your AI workloads. Discover comprehensive skilling with free, self-paced Azure AI Plans on Learn to further develop your Azure adoption skills so you can begin your AI adoption journey with confidence. Learn more about Azure Innovate and Azure Migrate and Modernize and Azure Essentials to understand how they can help you accelerate AI adoption and drive innovation in your business. Ready to take action? Connect with Microsoft Azure sales or reach out to a qualified partner. If you have a Unified Contract with Microsoft Support, there are multiple engagements opportunities that are based on CAF and WAF to help you accelerate your Azure and AI deployments.
Ignite 2024: Streamlining AI Development with an Enhanced User Interface, Accessibility, and Learning Experiences in Azure AI Foundry portal
Announcing Azure AI Foundry, a unified platform that simplifies AI development and management. The platform portal (formerly Azure AI Studio) features a revamped user interface, enhanced model catalog, new management center, improved accessibility and learning, making it easier than ever for Developers and IT Admins to design, customize, and manage AI apps and agents efficiently.Ground your AI agents with knowledge from Bing Search, Microsoft Fabric, SharePoint and more
Today, we are thrilled to announce the upcoming preview of Azure AI Agent Service, a comprehensive suite of capabilities designed to empower developers to securely build, deploy, and scale high-quality, extensible, and reliable AI agents. By leveraging an extensive ecosystem of models, tools, and capabilities from OpenAI, Microsoft, and industry-leading partners such as Meta, Azure AI Agent Service enables developers to efficiently create agents for a wide range of generative AI use cases. In this blog, we will explore the Knowledge Integration capabilities of Azure AI Agent Service, designed not only to streamline the creation of Retrieval-Augmented Generation (RAG) workflow, but also to empower developers to build intelligent, knowledge-driven AI agents. Grounding AI Agents with Knowledge Knowledge is the foundation of generating accurate, grounded responses, allowing Azure AI Agent Service to make informed decisions with confidence. By integrating comprehensive and accurate data, Azure AI Agent Service enhances precision and provides effective solutions, elevating the overall customer experience. With the preview of Azure AI Agent Service, you can ground your agent’s responses using data from Bing Search, Microsoft Fabric, SharePoint, Azure AI Search, Azure Blob Storage, your local files, and even your own licensed data. These data sources enable grounding with diverse data types, from enterprise private data and public web data to your own licensed data, structured or unstructured. Enterprise-grade security features, such as On-Behalf-Of (OBO) authorization, ensures your data is stored, retrieved and accessed, meeting the highest standards of privacy and protection. Key Capabilities Leverage Real-Time Public Web Data with Grounding with Bing Search LLMs can sometimes generate outdated content. By grounding your agent with Bing Search, you can overcome this limitation and create more reliable and trustworthy applications. Grounding with Bing Search allows your agents to integrate real-time public web data, ensuring their response is accurate and up to date. By including supporting URLs and search query links, Grounding with Bing Search enhances trust and transparency, empowering the users to verify responses with the original sources. Empower Data-Driven Decisions with Microsoft Fabric Integrate your Azure AI Agent with Fabric AI Skill to unlock powerful data analysis capabilities. Fabric AI Skill transforms enterprise data into conversational Q&A systems, allowing users to interact with the data through chat and uncover data-driven and actionable insights effortlessly. With OBO authorization, this integration simplifies access to enterprise data in Fabric while maintaining robust security, ensuring proper access control and enterprise-grade protection. Connect Private Data Securely with SharePoint Azure AI Agent Service supports grounding response with your data in SharePoint (coming soon). This integration makes your SharePoint content more accessible to your end users. Enterprise-grade security features, such as OBO authorization for SharePoint, ensure secure and controlled access for end users. Ground Private Data with Azure AI Search, Azure Blob Storage and Your Local Files Azure AI Agent Service supports connecting private data from various sources, such as Azure AI Search, Azure Blob Storage, and local files, to enhance responses. Bring your existing Azure AI Search index or create a new one using the improved File Search tool. This tool leverages a built-in ingestion pipeline to process files from your local system or Azure Blob Storage. With the new File Search tool, your files remain in your own storage, and your Azure AI Search resource is used to ingest them, ensuring you maintain complete control over your data. Enrich Responses with Your Licensed Data Azure AI Agent Service also integrates your own licensed data from specialized data providers, such as Tripadvisor. Enhance the quality of your agent’s responses with high-quality, fresh data, such as travel guidance and reviews. These insights empower your agents to deliver nuanced, informed solutions tailored to specific use cases. “We’re excited to partner with Microsoft as the first data and intelligence provider for its Azure AI Agent Service," said Rahul Todkar, Vice President, Head of Data and AI at Tripadvisor. “At Tripadvisor, we are focused on leveraging the power of Data and Generative AI to benefit all travelers and partners across the globe. With this new partnership we are making available to developers a set of APIs that provide access to granular Tripadvisor data, content and intelligence. This will allow developers and AI engineers/scientists to use our robust travel data across a broad array of AI and ML use cases including building AI agents, contextually relevant recommendations and drive increased personalization." What’s Next Sign up for the private preview: Contact your account executive Learn More: Watch our breakout session on Azure AI Agent Service. See it in action: Check out our demo session on building custom agents with models and tools. Start building: Explore single and multi-agent solutions with our Azure AI Agent Service code samples.
