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.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 AtlantaEnter new era of enterprise communication with Microsoft Translator Pro & document image translation
Microsoft Translator Pro: standalone, native mobile experience We are thrilled to unveil the gated public preview of Microsoft Translator Pro, our robust solution designed for enterprises seeking to dismantle language barriers in the workplace. Available on iOS, Microsoft Translator Pro offers a standalone, native experience, enabling speech-to-speech translated conversations among coworkers, users, or clients within your enterprise ecosystem. Watch how Microsoft Translator Pro transforms a hotel check-in experience by breaking down language barriers. In this video, a hotel receptionist speaks in English, and the app translates and plays the message aloud in Chinese for the traveler. The traveler responds in Chinese, and the app translates and plays the message aloud in English for the receptionist. Key features of the public preview Our enterprise version of the app is packed with features tailored to meet the stringent demands of enterprises: Core feature - speech-to-speech translation: Break language barriers: Real-time speech-to-speech translation allows you to have seamless communication with individuals speaking different languages. Unified experience: View or hear both transcription and translation simultaneously on a single device, ensuring smooth and efficient conversations. On-device translation: Harness the app's speech-to-speech translation capability without an internet connection in limited languages, ensuring your productivity remains unhampered. Full administrator control: Enterprise IT Administrators wield extensive control over the app's deployment and usage within your organization. They can fine-tune settings to manage conversation history, audit, and diagnostic logs, with the ability to disable history or configure automatic exportation of the history to cloud storage. Uncompromised privacy and security: Microsoft Translator Pro provides enterprises with a high level of translation quality and robust security. We know that Privacy and security are top priorities for you. Once granted access by your organization's admin, you can sign in the app with your organizational credentials. Your conversational data remains strictly yours, safeguarded within your Azure tenant. Neither Microsoft nor any external entities have access to your data. Join the Preview To embark on this journey with us, please complete the gating form . Upon meeting the criteria, we will grant your organization access to the paid version of the Microsoft Translator Pro app, which is now available in the US. Learn more and get started: Microsoft Translator Pro documentation. Document translation translates text embedded in images Our commitment to advancing cross-language communication takes a major step forward with a new enhancement in Azure AI Translator’s Document Translation (DT) feature. Previously, Document Translation supported fully digital documents and scanned PDFs. Starting January 2025, with this latest update, the service can also process mixed-content documents, translating both digital text and text embedded within images. Sample document translated from English to Spanish: (Frames in order: Source document, translated output document (image not translated), translated output document with image translation) How It Works To enable this feature, the Document Translation service now leverages Microsoft Azure AI Vision API to detect, extract, and translate text from images within documents. This capability is especially useful for scenarios where documents contain a mix of digital text and image-based text, ensuring complete translations without manual intervention. Getting Started To take advantage of this feature, customers can use the new optional parameter when setting up a translation request: Request A new parameter under "options" called "translateTextWithinImage" has been introduced. This parameter is of type Boolean, accepting "true" or "false." The default value is "false," so you’ll need to set it to "true" to activate the image text translation capability. Response: When this feature is enabled, the response will include additional details for transparency on image processing: totalImageScansSucceeded: The count of successfully translated image scans. totalImageScansFailed: The count of image scans that encountered processing issues. Usage and cost For this feature, customers will need to use the Azure AI Services resource, as this new feature leverages Azure AI Vision services along with Azure AI Translator. The OCR service incurs additional charges based on usage. Pricing details for the OCR service can be found here: Pricing details Learn more and get started (starting January 2025): Translator Documentation These new advancements reflect our dedication to pushing boundaries in Document Translation, empowering enterprises to connect and collaborate more effectively, regardless of language. Stay tuned for more innovations as we continue to expand the reach and capabilities of Microsoft Azure AI Translator.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.Extending Azure's AI Platform with an adaptive cloud approach
Authored by Derek Bogardus and Sanjana Mohan, Azure Edge AI Product Management Ignite 2024 is here, and nothing is more top of mind for customers than the potential to transform their businesses with AI wherever they operate. Today, we are excited to announce the preview of two new Arc-enabled services that extend the power of Azure’s AI platform to on-premises and edge environments. Sign up to join the previews here! An adaptive cloud approach to AI The goal of Azure’s adaptive cloud approach is to extend just enough Azure to customers’ distributed environments. For many of these customers, valuable data is generated and stored locally, outside of the hyperscale cloud, whether due to regulation, latency, business continuity, or simply the large volume of data being generated in real time. AI inferencing can only occur where the data exists. So, while the cloud has become the environment of choice for training models, we see a tremendous need to extend inferencing services beyond the cloud to enable complete cloud-to-edge AI scenarios. Search on-premises data with generative AI Over the past couple of years, generative AI has come to the forefront of AI innovation. Language models give any user the ability to interact with large, complex data sets in natural language. Public tools like ChatGPT are great for queries about general knowledge, but they can’t answer questions about private enterprise data on which they were not trained. Retrieval Augmented Generation, or "RAG", helps address this need by augmenting language models with private data. Cloud services like Azure AI Search and Azure AI Foundry simplify how customers can use RAG to ground language models in their enterprise data. Today, we are announcing the preview of a new service that brings generative AI and RAG to your data at the edge. Within minutes, customers can deploy an Arc extension that contains everything needed to start asking questions about their on-premises data, including: Popular small and large language models running locally with support for both CPU and GPU hardware A turnkey data ingestion and RAG pipeline that keeps all data completely local, with RBAC controls to prevent unauthorized access An out-of-the-box prompt engineering and evaluation tool to find the best settings for a particular dataset Azure-consistent APIs to integrate into business applications, as well as a pre-packaged UI to get started quickly This service is available now in gated private preview for customers running Azure Local infrastructure, and we plan to make it available on other Arc-enabled infrastructure platforms in the near future. Sign up here! Deploy curated open-source AI models via Azure Arc Another great thing about Azure’s AI platform is that it provides a catalog of curated AI models that are ready to deploy and provide consistent inferencing endpoints that can be integrated directly into customer applications. This not only makes deployment easy, but customers can also be confident that the models are secure and validated These same needs exist on the edge as well, which is why we are now making a set of curated models deployable directly from the Azure Portal. These models have been selected, packaged, and tested specifically for edge deployments, and are currently available on Azure Local infrastructure. Phi-3.5 Mini (3.8 billion parameter language model) Mistral 7B (7.3 billion parameter language model) MMDetection YOLO (object detection) OpenAI Whisper Large (speech to text) Google T5 Base (translation) Models can be deployed from a familiar Azure Portal wizard to an Arc AKS cluster running on premises. All available models today can be run on just a CPU. Phi-3.5 and Mistral 7B also have GPU versions available for better performance. Once complete, the deployment can be managed directly in Azure ML Studio, and an inferencing endpoint is available on your local network. Wrap up Sign up now to join either of the previews at the link below or stop by and visit us in person in the Azure Arc and Azure Local Expert Meet Up station in the Azure Infrastructure neighborhood at Ignite. We’re excited to get these new capabilities into our customers’ hands and hear from you how it’s going. Sign up to join the previews hereAzure SQL Managed Instance pools: General Availability
We are happy to announce new features and General Availability for instance pools. Instance pools are a deployment option in Azure SQL Managed instance service to provision small, cost-effective 2-vCore instances. This way, small instances can cost 50% less compared to non-pooled instances, making it an attractive PaaS target when migrating small on-premises servers or modernizing SQL VMs.Simplified & lower pricing for Azure SQL Database and Azure SQL Managed Instance backup storage
Today as you deploy your Azure SQL database or Azure SQL managed instance, one of the important decisions to be made is the choice for your backup storage redundancy (BSR). I say it's important because the availability of your database depends on the availability of your backups. Here’s why. Consider the scenario where your DB has high availability configured via zone redundancy. And, let's say, your backups are configured non-zone redundant. In the event of a failure in the zone, your database fails over to another zone within the region, however your backups won't, because of their storage setting. Now, in the new zone, the backup service attempts to backup your database but cannot reach the backups in the zone where the failure happened causing the logs to become full and eventually impacting the availability of the database itself. As you create the Azure SQL database, the choices for backup storage redundancy are: Locally Redundant Storage (LRS) Zone Redundant Storage (ZRS) Geo Redundant Storage (GRS) and Geo Zone Redundant Storage (GZRS) Each of these storage types provides different levels of durability, resiliency and availability for your databases and database backups. Not surprisingly, each storage type also has different levels of pricing, and the price increases significantly as the protection level increases with GZRS storage type almost 4-5x LRS. Choosing between resilience and cost optimization is an extremely difficult choice that the DB owner must make. We are thrilled to announce that, starting from Nov 01, 2024, the backup storage pricing is now streamlined and simplified across Azure SQL database and Azure SQL Managed Instance. Bonus – we even reduced the prices 😊 The price changes apply to the Backup Storage Redundancy configuration for both Point-in-time and Long-Term Retention backups, across the following tiers of Azure SQL Database and Azure SQL Managed Instance: Product Service Tier Azure SQL Database General Purpose Business Critical Hyperscale Azure SQL Managed Instance General Purpose Business Critical Next Generation General Purpose (preview) As we made the changes, following were the principles we adhered to: No price increase BSR pricing for ZRS is reduced to match the BSR pricing for LRS BSR pricing for GZRS is reduced to match the BSR pricing of GRS BSR pricing for GRS/GZRS will be 2x that of LRS/ZRS Type of backups What is Changing PITR BSR pricing for ZRS is reduced by 20% to match pricing for LRS for all service tiers in Azure SQL Database and Azure SQL Managed Instance except for Azure SQL Database Hyperscale service tier. BSR pricing for GZRS is reduced by 41% to match pricing for GRS for all service tiers in Azure SQL Database and Azure SQL Managed Instance. LTR BSR pricing for ZRS is reduced by 20% to match pricing for LRS for all service tiers in Azure SQL Database and Azure SQL Managed Instance. BSR pricing for GZRS is reduced by 41% to match pricing for GRS for all service tiers in Azure SQL Database and Azure SQL Managed Instance. As an example, lets take East US as the region and look at the pricing for backup storage redundancy for Point in Time storage before and after the changes: For General Purpose/Business Critical service tiers the pricing would now be: Backup Storage Redundancy Current price New Price Price change LRS $0.10 $0.10 None ZRS $0.125 $0.10 20% less GRS $0.20 $0.20 None GZRS $0.34 $0.20 41% less For Hyperscale service tier, the new pricing would now be: Backup Storage Redundancy Current price New Price Price change LRS $0.08 $0.08 None ZRS $0.1 $0.10 None GRS $0.20 $0.20 None GZRS $0.34 $0.20 41% less Similarly, Backup storage redundancy prices for Long Term Retention backups in East US would be as follows: Backup Storage Redundancy Current price New Price Price change LRS $0.025 $0.025 None ZRS $0.0313 $0.025 20% less GRS $0.05 $0.05 None GZRS $0.0845 $0.05 41% less As a customer, the decision now becomes much easier for you. If you need regional resiliency: choose Zone Redundant Storage (ZRS) If you need regional and/or geo resiliency: choose Geo Zone Redundant Storage (GZRS). If the Azure region does not support Availability Zones, then choose Local Redundant Storage for regional resiliency, and Geo Redundant Storage for geo resiliency respectively. Please Note: The Azure pricing page and Azure pricing calculator will be updated with these new prices soon. The actual pricing meters have already been updated. Additionally, the LTR pricing change for Hyperscale will be in effect from January 1, 2025.Secure Unique Default Hostnames: GA on App Service Web Apps and Public Preview on Functions
Back in May 2024, we announced the Public Preview of Secure Unique Default Hostnames on Web Apps. We are excited to announce that this feature is now in General Availability on Web Apps and is now in Public Preview for Functions! This feature works similarly for both Web Apps and Functions, so you can refer to the Public Preview announcement for more in-depth information regarding this feature. Secure unique default hostname feature is a long-term solution to protect your resources from dangling DNS entries and subdomain takeover. If you have this feature enabled for your App Service resources, then no one outside of your organization would be able to recreate resources with the same default hostname. This means that malicious actors can no longer take advantage of your dangling DNS entries and takeover your subdomains. We highly encourage everyone to enable secure unique default hostnames on their net-new App Service deployments. Addressing pre-existing resources without secure unique default hostnames enabled Since this feature can only be enabled upon resource creation, if you’d like to use this feature for your pre-existing resources, you can: Clone a pre-existing app to a new app with secure unique default hostname enabled Screenshot of cloning pre-existing app to an app that's about to be created with secure unique default hostname enabled. Use a backup of a pre-existing app to restore to a new app with secure unique default hostname enabled Screenshot of using a backup of a pre-existing app to restore to an app that's about to be created with secure unique default hostname enabled. Looking ahead We highly encourage everyone to enable secure unique default hostnames on all net-new App Service deployments. This is the time to integrate and to adopt this feature to your testing and production environments so that you can build more secure App Service resources to prevent dangling DNS entries and avoid subdomain takeover. Keep an eye out for future announcements where we will launch secure unique default hostnames in Public Preview for Logic Apps (Standard)!
