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 AtlantaExtending 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 hereSecure 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)!
What's New in Azure App Service at Ignite 2024
Learn about the GA of sidecar extensibility on Linux and see team members demonstrating the latest tools for AI assisted web application migration and modernization as well as the latest updates to Java JBoss EAP on Azure App Service. Team members will also demonstrate integrating the Phi-3 small language model with a web application via the new sidecar extensibility using existing App Service hardware! Also new for this year’s Ignite, many topics that attendees see in App Service related sessions are also available for hands-on learning across multiple hands-on labs (HoLs). Don’t just watch team members demonstrating concepts on-stage, drop by one of the many HoL sessions and test drive the functionality yourself! Azure App Service team members will also be in attendance at the Expert Meetup area on the third floor in the Hub – drop by and chat if you are attending in-person! Additional demos, presentations and hands-on labs covering App Service are listed at the end of this blog post for easy reference. Sidecar Extensibility GA for Azure App Service on Linux Sidecar extensibility for Azure App Service on Linux is now GA! Linux applications deployed from source-code as well as applications deployed using custom containers can take advantage of sidecar extensibility. Sidecars enable developers to attach additional capabilities like third-party application monitoring providers, in-memory caches, or even local SLM (small language model) support to their applications without having to bake that functionality directly into their applications. Developers can configure up to four sidecar containers per application, with each sidecar being associated with its own container registry and (optional) startup command. Examples of configuring an OpenTelemetry collector sidecar are available in the documentation for both container-based applications and source-code based applications. There are also several recent blog posts demonstrating additional sidecar scenarios. One example walks through using a Redis cache sidecar as an in-memory cache to accelerate data retrieval in a web application (sample code here). Another example demonstrates adding a sidecar containing the Phi-3 SLM to a custom container web application (sample code here). Once the web app is running with the SLM sidecar, Phi-3 processes text prompts directly on the web server without the need to call remote LLMs or host models on scarce GPU hardware. Similar examples for source deployed applications are available in the Ignite 2024 hands on lab demonstrating sidecars. Exercise three walks through attaching an OTel sidecar to a source-code based application, and exercise four shows how to attach a Phi-3 sidecar to a source-code based application. Looking ahead to the future, App Service will be adding “curated sidecars” to the platform to make it easier for developers to integrate common sidecar scenarios. Development is already underway to include options for popular third-party application monitoring providers, Redis cache support, as well as a curated sidecar encapsulating the Phi-3 SLM example mentioned earlier. Stay tuned for these enhancements in the future! If you are attending Microsoft Ignite 2024 in person, drop by the theater session “Modernize your apps with AI without completely rewriting your code” (session code: THR 614) which demonstrates using sidecar extensibility to add Open Telemetry monitoring as well as Phi-3 SLM support to applications on App Service for Linux! .NET 9 GA, JBoss EAP and More Language Updates! With the recent GA of .NET 9 last week developers can deploy applications running .NET 9 GA on both Windows and Linux variants of App Service! Visual Studio, Visual Studio Code, Azure DevOps and GitHub Actions all support building and deploying .NET 9 applications onto App Service. Start a new project using .NET 9 or upgrade your existing .NET applications in-place and take advantage of .NET 9! For JBoss EAP on App Service for Linux, customers will soon be able to bring their existing JBoss licenses with them when moving JBoss EAP workloads onto App Service for Linux. This change will make it easier and more cost effective than ever for JBoss EAP customers to migrate existing workloads to App Service, including JBoss versions 7.3, 7.4 and 8.0! As a quick reminder, last month App Service also announced reduced pricing for JBoss EAP licenses (for net-new workloads) as well as expanded hardware support (both memory-optimized and Free tier are now supported for JBoss EAP applications). App Service is planning to release both Node 22 and Python 3.13 onto App Service for Linux with expected availability in December! Python 3.13 is the latest stable Python release which means developers will be able to leverage this version with confidence given long term support runs into 2029. Node 22 is the latest active LTS release of Node and is a great version for developers to adopt with its long-term support lasting into 2026. A special note for Linux Python developers, App Service now supports “auto-instrumentation” in public preview for Python versions 3.8 through 3.12. This makes it trivial for source-code based Python applications to enable Application Insights monitoring for their applications by simply turning the feature “on” in the Azure Portal. If you ever thought to yourself that it can be a hassle setting up application monitoring and hence find yourself procrastinating, this is the monitoring feature for you! Looking ahead just a few short weeks until December, App Service also plans to release PHP 8.4 for developers on App Service for Linux. This will enable PHP developers to leverage the latest fully supported PHP release with an expected support cycle stretching into 2028. For WordPress customers Azure App Service has added support for managed identities when connecting to MySQL database as well as storage accounts. The platform has also transitioned WordPress from Alpine Linux to Debian, aligning with App Service for Linux to offer a more secure platform. Looking ahead, App Service is excited to introduce some new features by the end of the year, including an App Service plugin for WordPress! This plugin will enable users to manage WordPress integration with Azure Communication Services email, set up Single Sign-On using Microsoft Entra ID, and diagnose performance bottlenecks. Stay tuned for upcoming WordPress announcements! End-to-End TLS & Min TLS Cipher Suite are now GA End-to-end TLS encryption for public multi-tenant App Service is now GA! When E2E TLS is configured, traffic between the App Service frontends and individual workers is secured using a platform supplied TLS certificate. This additional level of security is available for both Windows and Linux sites using Standard SKU and above as well as Isolatedv2 SKUs. You can enable this feature easily in the Azure Portal by going to your resource, clicking the “Configuration” blade and turning the feature “On” as shown below: Configuration of the minimum TLS cipher suite for a web application is also GA! With this feature developers can choose from a pre-determined list of cipher suites. When a minimum cipher suite is selected, the App Service frontends will reject any incoming requests that use a cipher suite weaker than the selected minimum cipher suite. This feature is supported for both Windows and Linux applications using Basic SKU and higher as well as Isolatedv2 SKUs. You configure a minimum TLS cipher suite in the Azure Portal by going to the “Configuration” blade for a website and selecting “Change” for the Minimum Inbound TLS Cipher Suite setting. In the resulting blade (shown below) you can select the minimum cipher suite for your application: To learn more about these and other TLS features on App Service, please refer to the App Service TLS overview. AI-Powered Conversational Diagnostics Building on the Conversational Diagnostics AI-powered tool and the guided decision making path introduced in Diagnostic Workflows, the team has created a new AI-driven natural language-based diagnostics solution for App Service on Linux. The new solution brings together previous functionality to create an experience that comprehends user intent, selects the appropriate Diagnostic Workflow, and keeps users engaged by providing real-time updates and actionable insights through chat. Conversational Diagnostics also provides the grounding data that the generative AI back-end uses to produce recommendations thus empowering users to check the conclusions. The integration of Conversational Diagnostics and Diagnostic Workflows marks a significant advancement in the platform’s diagnostic capabilities. Stay tuned for more updates and experience the transformative power of Generative AI-driven diagnostics firsthand! App Service Migration and Modernization The team just recently introduced new architectural guidance around evolving and modernizing web applications with the Modern Web Application pattern for .NET and Java! This guidance builds on the Reliable Web App pattern for .NET and Java as well as the Azure Migrate application and code assessment tool. With the newly released Modern Web Application guidance, there is a well-documented path for migrating web applications from on-premises/VM deployments using the application and code assessment tool, iterating and evolving web applications with best practices using guidance from the Reliable Web App pattern, and subsequently going deeper on modernization and re-factoring following guidance from the Modern Web Application pattern. Best of all customers can choose to “enter” this journey at any point and progress as far down the modernization path as needed based on their unique business and technical requirements! As a quick recap on the code assessment tool, it is a guided experience inside of Visual Studio with GitHub Copilot providing actionable guidance and feedback on recommended changes needed to migrate applications to a variety of Azure services including Azure App Service. Combined with AI-powered Conversational Diagnostics (mentioned earlier), developers now have AI-guided journeys supporting them from migration all the way through deployment and runtime operation on App Service! Networking and ASE Updates As of November 1, 2024, we are excited to announce that App Service multi-plan subnet join is generally available across all public Azure regions! Multi-plan subnet join eases network management by reducing subnet sprawl, enabling developers to connect multiple app service plans to a single subnet. There is no limit to the number of app service plans that connect to a single subnet. However, developers should keep in mind the number of available IPs since tasks such as changing the SKU for an app service plan will temporarily double the number of IP addresses used in a connected subnet. For more information as well as examples on using multi-plan subnet join see the documentation! App Service also recently announced GA of memory optimized options for Isolatedv2 on App Service Environment v3. The new memory-optimized options range from two virtual cores with 16 GB RAM in I1mv2 (compared to two virtual cores, 8 GB RAM in I1v2) all the way up to 32 virtual cores with 256 GB RAM in I5mv2. The new plans are available in most regions. Check back regularly to see if your preferred region is supported. For more details on the technical specifications of these plans, as well as information on the complete range of tiers and plans for Microsoft Azure App Service, visit our pricing page. Using services such as Application Gateway and Azure Front Door with App Service as entry points for client traffic is a common scenario that many of our customers implement. However, when using these services together, there are integration challenges around the default cookie domain for HTTP cookies, including the ARRAffinity cookie used for session affinity. App Service collaborated with the Application Gateway team to introduce a simple solution that addresses the session affinity problem. App Service introduced a new session affinity proxy configuration setting in October which tells App Service to always set the hostname for outbound cookies based on the upstream hostname seen by Application Gateway or Azure Front Door. This simplifies integration with a single-click experience for App Service developers who front-end their websites using one of Azure’s reverse proxies, and it solves the challenge of round-tripping the ArrAffinity cookie when upstream proxies are involved. Looking ahead to early 2025, App Service will shortly be expanding support for IPv6 to include both inbound and outbound connections (currently only inbound connections are supported). The current public preview includes dual-stack support for both IPv4 and IPv6, allowing for a smooth transition and compatibility with existing systems. Read more about the latest status of the IPv6 public preview on App Service here ! Lastly, the new application naming and hostname convention that was rolled out a few months earlier for App Service is now GA for App Service. The platform has also extended this new naming convention to Azure Functions where it is now available in public preview for newly created functions. To learn more about the new naming convention and the protection it provides against subdomain takeover take a look at the introductory blog post about the unique default hostname feature. Upcoming Availability Zone Improvements New Availability Zone features are currently rolling out that will make zone redundant App Service deployments more cost efficient and simpler to manage in early 2025! The platform will be changing the minimum requirement for enabling Availability Zones to two instances instead of three, while still maintaining a 99.99% SLA. Many existing app service plans with two or more instances will also automatically become capable of supporting Availability Zones without requiring additional setup. Additionally, the zone redundant setting will be mutable throughout the life of an app service plan. This upcoming improvement will allow customers on Premium V2, Premium V3, or Isolated V2 plans, to toggle zone redundancy on or off as needed. Customers will also gain enhanced visibility into Availability Zone information, including physical zone placement and counts. As a sneak peek into the future, the screenshot below shows what the new experience will look like in the Azure Portal: Stay tuned for Availability Zone updates coming to App Service in early 2025! Next Steps Developers can learn more about Azure App Service at Getting Started with Azure App Service. Stay up to date on new features and innovations on Azure App Service via Azure Updates as well as the Azure App Service (@AzAppService) X feed. There is always a steady stream of great deep-dive technical articles about App Service as well as the breadth of developer focused Azure services over on the Apps on Azure blog. Azure App Service (virtually!) attended the recently completed November .Net Conf 2024. App Service functionality was featured showing a .NET 9.0 app using Azure Sql’s recently released native vector data type support that enables developers to perform hybrid text searches on Azure Sql data using vectors generated via Azure OpenAI embeddings! And lastly take a look at Azure App Service Community Standups hosted on the Microsoft Azure Developers YouTube channel. The Azure App Service Community Standup series regularly features walkthroughs of new and upcoming features from folks that work directly on the product! Ignite 2024 Session Reference (Note: some sessions/labs have more than one timeslot spanning multiple days). (Note: all times below are listed in Chicago time - Central Standard Time). Modernize your apps with AI without completely rewriting your code Modernize your apps with AI without completely rewriting your code [Note: this session includes a demonstration of the Phi-3 sidecar scenario] Wednesday, November 20 th 1:00 PM - 1:30 PM Central Standard Time Theater Session – In-Person Only (THR614) McCormick Place West Building – Level 3, Hub, Theater C Unlock AI: Assess your app and data estate for AI-powered innovation Unlock AI: Assess your app and data estate for AI-powered innovation Wednesday, November 20 th 1:15 PM – 2:00 PM Central Time McCormick Place West Building – Level 1, Room W183c Breakout and Recorded Session (BRK137) Modernize and scale enterprise Java applications on Azure Modernize and scale enterprise Java applications on Azure Thursday, November 21 st 8:30 AM - 9:15 AM Central Time McCormick Place West Building – Level 1, Room W183c Breakout and Recorded Session (BRK147) Assess apps with Azure Migrate and replatform to Azure App Service Assess apps with Azure Migrate and replatform to Azure App Service Tuesday, November 19 th 1:15 PM - 2:30 PM Central Time McCormick Place West Building – Level 4, Room W475 Hands on Lab – In-Person Only (LAB408) Integrate GenAI capabilities into your .NET apps with minimal code changes Integrate GenAI capabilities into your .NET apps with minimal code changes [Note: Lab participants will be able to try out the Phi-3 sidecar scenario in this lab.] Wednesday, November 20 th 8:30 AM - 9:45 AM Central Time McCormick Place West Building – Level 4, Room W475 Hands on Lab – In-Person Only (LAB411) Assess apps with Azure Migrate and replatform to Azure App Service Assess apps with Azure Migrate and replatform to Azure App Service Wednesday, November 20 th 6:30 PM - 7:45 PM Central Time McCormick Place West Building – Level 4, Room W470b Hands on Lab – In-Person Only (LAB408-R1) Integrate GenAI capabilities into your .NET apps with minimal code changes Integrate GenAI capabilities into your .NET apps with minimal code changes [Note: Lab participants will be able to try out the Phi-3 sidecar scenario in this lab.] Thursday, November 21 st 10:15 AM - 11:30 AM Central Time McCormick Place West Building – Level 1, Room W180 Hands on Lab – In-Person Only (LAB411-R1) Assess apps with Azure Migrate and replatform to Azure App Service Assess apps with Azure Migrate and replatform to Azure App Service Friday, November 22 nd 9:00 AM – 10:15 AM Central Time McCormick Place West Building – Level 4, Room W474 Hands on Lab – In-Person Only (LAB408-R2)New Da/Ea/Fav6 VMs with increased performance and Azure Boost are now generally available
By Sasha Melamed, Senior Product Manager, Azure Compute We are excited to announce General Availability of new Dalsv6, Dasv6, Easv6, Falsv6, Fasv6, and Famsv6-series Azure Virtual Machines (VMs) based on the 4th Gen AMD EPYC™ processor (Genoa). These VMs deliver significantly improved performance and price/performance versus the prior Dasv5 and Easv5 VMs, NVMe connectivity for faster local and remote storage access, and Azure Boost for improved performance and enhanced security. With the broad selection of compute, memory, and storage configurations available with these new VM series, there is a best fit option for a wide range of workloads. What’s New The new Dalsv6, Davs6, and Easv6 VMs are offered with vCPU counts ranging from 2 to 96 vCPUs. The new general purpose and memory optimized VMs will come in a variety of memory (GiB)-to-vCPU ratios, including the Dalsv6 at 2:1, Dasv6 at 4:1, and Easv6 at 8:1 ratios. The VMs are also available with and without a local disk so that you can choose the option that best fits your workload. Workloads can expect up to 20% CPU performance improvement over the Dasv5 and Easv5 VMs and up to 15% better price/performance. Further expanding our offerings, we are proud to introduce the first Compute-optimized VM series based on AMD processors also in three memory-to-vCPU ratios. The new Falsv6, Fasv6, and Famsv6 VMs offer the fastest x86 CPU performance in Azure and have up to 2x CPU performance improvement over our previous v5 VMs, as shown in the graph below. We are excited to announce that the new Dalsv6, Dasv6, Easv6, and suite of Fasv6 virtual machines are powered by Azure Boost. Azure Boost has been providing benefits to millions of existing Azure VMs in production today, such as enabling exceptional remote storage performance and significant improvements in networking throughput and latency. Our latest Azure Boost infrastructure innovation, in combination with new AMD-based VMs, delivers improvements in performance, security, and reliability. The platform provides sub-second servicing capabilities for the most common infrastructure updates, delivering a 10x reduction in impact. To learn more about Azure Boost, read our blog. To drive the best storage performance for your workloads, the new AMD-based VMs come with the NVMe interface for local and remote disks. Many workloads will benefit from improvements over the previous generation of AMD-based with up to: 80% better remote storage performance 400% faster local storage speeds 25% networking bandwidth improvement 45% higher NVMe SSD capacity per vCPU for Daldsv6, Dadsv6, Eadsv6-series VMs with local disks The 4th Gen AMD EPYC™ processors provide new capabilities for these VMs, including: Always-On Transparent Secure Memory Encryption ensuring that your sensitive information remains secure without compromising performance. AVX-512 to handle compute-intensive tasks such as scientific simulations, financial analytics, AI, and machine learning. Vector Neural Network Instructions enhancing the performance of neural network inference operations, making it easier to deploy and scale AI solutions. Bfloat16 for efficient training and inference of deep learning models, providing a balance between performance and precision. Dasv6, Dadsv6, Easv6, Eadsv6, Fasv6, and Fadsv6-series VMs are SAP Certified. Whether you’re running a simple test infrastructure, mission critical enterprise applications, high-performance computing tasks, or AI workloads, our new VMs are ready to meet your needs. Explore the new capabilities and start leveraging the power of Azure today! General-purpose workloads The new Dasv6-series VMs offer a balanced ratio of memory to vCPU performance and increased scalability, up to 96 vCPUs and 384 GiB of RAM. Whereas the new Dalsv6-series VM series are ideal for workloads that require less RAM per vCPU, with a max of 192 GiB of RAM. The Dalsv6 series are the first 2GiB/vCPU memory offerings in our family of AMD-based VMs. The Dalsv6 series can reduce your costs when running non-memory intensive applications, including web servers, gaming, video encoding, AI/ML, and batch processing. The Dasv6-series VMs work well for many general computing workloads, such as e-commerce systems, web front ends, desktop virtualization solutions, customer relationship management applications, entry-level and mid-range databases, application servers, and more. Series vCPU Memory (GiB) Max Local NVMe Disk (GiB) Max IOPS for Local Disk Max Uncached Disk IOPS for Managed Disks Max Managed Disks Throughput (MBps) Dalsv6 2-96 4-192 N/A N/A 4 - 172K 90 – 4,320 Daldsv6 2-96 4-192 1x110 - 6x880 1.8M 4 - 172K 90 – 4,320 Dasv6 2-96 8-384 N/A N/A 4 - 172K 90 – 4,320 Dadsv6 2-96 8-384 1x110 - 6x880 1.8M 4 - 172K 90 – 4,320 Memory-intensive workloads For more memory demanding workloads, the new Easv6-series VMs offer high memory-to-vCPU ratios with increased scalability up to 96 vCPUs and 672 GiB of RAM. The Easv6-series VMs are ideal for memory-intensive enterprise applications, data warehousing, business intelligence, in-memory analytics, and financial transactions. Series vCPU Memory (GiB) Max Local NVMe Disk (GiB) Max IOPS for Local Disk Max Uncached Disk IOPS for Managed Disks Max Managed Disks Throughput (MBps) Easv6 2-96 16-672 N/A N/A 4 - 172K 90 – 4,320 Eadsv6 2-96 16-672 1x110 - 6x880 1.8M 4 - 172K 90 – 4,320 Compute-intensive workloads For compute-intensive workloads, the new Falsv6, Fasv6 and Famsv6 VM series come without Simultaneous Multithreading (SMT), meaning a vCPU equals one physical core. These VMs will be the best fit for workloads demanding the highest CPU performance, such as scientific simulations, financial modeling and risk analysis, gaming, and video rendering. Series vCPU Memory (GiB) Max Uncached Disk IOPS for Managed Disks Max Managed Disks Throughput (MBps) Max Network Bandwidth (Gbps) Falsv6 2-64 4-128 4 - 115K 90 - 2,880 12.5 - 36 Fasv6 2-64 8-256 4 - 115K 90 - 2,880 12.5 - 36 Famsv6 2-64 16-512 4 - 115K 90 - 2,880 12.5 - 36 Customers are excited about new AMD v6 VMs FlashGrid offers software solutions that help Oracle Database users on Azure achieve maximum database uptime and minimize the risk of outages. The Easv6 series VMs make it easier to support Oracle RAC workloads with heavy transaction processing on Azure using FlashGrid Cluster. The NVMe protocol enhances disk error handling, which is important for failure isolation in high-availability database architectures. The CPU boost frequency of 3.7 GHz and higher network bandwidth per vCPU enable database clusters to handle spikes in client transactions better while keeping a lower count of vCPU to limit licensing costs. The Easv6 VMs have passed our extensive reliability and compatibility testing and are now available for new deployments and upgrades. – Art Danielov, CEO, FlashGrid Inc. Helio is a platform for large-scale computing workloads, optimizing for costs, scale, and emissions. Its main focus is 3D rendering Our architectural and media & entertainment (VFX) 3D rendering workloads have been accelerated by an average of ~42% with the new v6 generation, while maintaining low cost and high scale. In addition, we are seeing significant improvements in disk performance with the new NVMe interface, resulting in much faster render asset load times. -- Kevin Häfeli, CEO / Cofounder Helio AG Silk's Software-Defined Cloud Storage delivers unparalleled price/performance for the most demanding, real-time applications. Silk has tested the new Da/Eav6 VM offering from Azure and we are looking forward to enable our customers to benefit from its new capabilities, allowing higher throughput at lower cost, while providing increased reliability” -- Adik Sokolovski, Chief R&D Officer, Silk ZeniMax Online Studios creates online RPG worlds where you can play and create your own stories. The new VMs we tested provided a significant performance boost in our build tasks. The super-fast storage not only made the workflows smoother and faster, but it also helped highlight other bottlenecks in our design and allowed us to improve our pipeline overall. We are excited for their availability and plan on utilizing these machines to expand our workload in Azure. -- Merrick Moss, Product Owner, ZeniMax Online Studios Getting started The new VMs are now available in the East US, East US 2, Central US, South Central US, West US 3, West Europe, and North Europe regions with more to follow. Check out pricing on the following pages for Windows and Linux. You can learn more about the new VMs in the documentation for Dal-series, Da-series, Ea-series, and Fa-series. We also recommend reading the NVMe overview and FAQ. You can find the Ultra disk and Premium SSD V2 regional availability to pair with the new NVMe based v6 series at their respective links.
Public Preview: Resilient Create and Delete on Virtual Machine Scale Sets
Today we're announcing the public preview of Resilient create and delete, which is a new feature on Virtual Machine Scale Sets (VMSS) that increases the reliability of virtual machine creates and deletes. VMSS initiates automatic recovery from failed creates and deletes by performing retries of those operations on customers’ behalf – ultimately reducing the manual effort required to detect and clean up unused resources. Customers often need to spend significant time understanding, debugging, and fixing failures during create and delete operations, which can lead to frustration and decreased productivity. The resilient create and delete feature will monitor failures during these operations and automatically recover or delete virtual machines, thereby increasing reliability without additional effort from customers. This feature is available across all public Azure regions. Key Benefits Higher reliability in creating and deleting virtual machines in scale sets. Automated recovery of failed operations to significantly reduce manual toil on customers. Reduces Time to Detect (TTD) and Time to Mitigate (TTM) for virtual machine creates and deletes in scale sets. Comprehensive error handling for virtual machine deletes by retrying on all error codes. Reliable initiation of cleaning up unusable capacity. Resilient create Resilient create runs on virtual machines created during a scale-out of a scale set or during the initial scale set creation. It initiates retries for only OS Provisioning Timeout and Virtual Machine Start Timeout errors. Resilient create attempts the create operation 5 times per virtual machine or for a maximum of 30 total minutes for all retries. Resilient delete Resilient delete initiates delete retries for any error, including but not limited to, InternalExecutionError, TransientFailure, or InternalOperationError. Unlike Resilient create that only retries from OS Provisioning Timeout and VM Start Timeout currently, resilient delete doesn't differentiate between error codes. We will retry all failed deletes. It attempts to delete operation up to five times per virtual machine. Setting up Resilient create and delete To enable Resilient create and delete on an existing Virtual Machine Scale Set, navigate to your scale set resource in the Azure portal. Under “Capabilities”, select “Health and repair”, and enable “Resilient VM create (Preview)” and “Resilient VM delete (Preview)”. To enable Resilient create and delete on a new Virtual Machine Scale Set during deployment, navigate to the “Health” tab and go to “Recovery”. Select checkboxes “Resilient VM create (Preview)” and/or “Resilient VM delete (Preview)”. Learn More You can learn more about how Resilient create and delete works and enroll in the preview in the documentation.
Ignite 2024: Bidirectional real-time audio streaming with Azure Communication Services
Today at Microsoft Ignite, we are excited to announce the upcoming preview of bidirectional audio streaming for Azure Communication Services Call Automation SDK, which unlocks new possibilities for developers and businesses. This capability results in seamless, low-latency, real-time communication when integrated with services like Azure Open AI and the real-time voice APIs, significantly enhancing how businesses can build and deploy conversational AI solutions. With the advent of new AI technologies, companies are developing solutions to reduce customer wait times and improve the overall customer experience. To achieve this, many businesses are turning to AI-powered agents. These AI-based agents must be capable of having conversations with customers in a human-like manner while maintaining very low latencies to ensure smooth interactions. This is especially critical in the voice channel, where any delay can significantly impact the fluidity and natural feel of the conversation. With bidirectional streaming, businesses can now elevate their voice solutions to low-latency, human-like, interactive conversational AI agents. Our bidirectional streaming APIs enable developers to stream audio from an ongoing call on Azure Communication Services to their web server in real-time. On the server, powerful language models interpret the caller's query and stream the responses back to the caller. All this is accomplished while maintaining low latency, ensuring the caller feels like they are speaking to a human. One such example of this would be to take the audio streams and processing them through Azure Open AI’s real-time voice API and then streaming the responses back into the call. With the integration of bidirectional streaming into Azure Communication Services Call Automation SDK, developers have new tools to innovate: Leverage conversational AI Solutions: Develop sophisticated customer support virtual agents that can interact with customers in real-time, providing immediate responses and solutions. Personalized customer experiences: By harnessing real-time data, businesses can offer more personalized and dynamic customer interactions in real-time, leading to increased satisfaction and loyalty. Reduce wait times for customers: By using bidirectional audio streams in combination with Large Language Models (LLMs) you can build virtual agents that can be the first point of contact for customers reducing the need for customers waiting for a human agent being available. Integrating with real-time voice-based Large Language Models (LLMs) With the advancements in voice based LLMs, developers want to take advantage of services like bidirectional streaming and send audio directly between the caller and the LLM. Today we’ll show you how you can start audio streaming through Azure Communication Services. Developers can start bidirectional streaming at the time of answering the call by providing the WebSocket URL. //Answer call with bidirectional streaming websocketUri = appBaseUrl.Replace("https", "wss") + "/ws"; var options = new AnswerCallOptions(incomingCallContext, callbackUri) { MediaStreamingOptions = new MediaStreamingOptions( transportUri: new Uri(websocketUri), contentType: MediaStreamingContent.Audio, audioChannelType: MediaStreamingAudioChannel.Mixed, startMediaStreaming: true) { EnableBidirectional = true, AudioFormat = AudioFormat.Pcm24KMono } }; At the same time, you should open your connection with Azure Open AI real-time voice API. Once the WebSocket connection is setup, Azure Communication Services starts streaming audio to your webserver. From there you can relay the audio to Azure Open AI voice and vice versa. Once the LLM reasons over the content provided in the audio it streams audio to your service which you can stream back into the Azure Communication Services call. (More information about how to set this up will be made available after Ignite) //Receiving streaming data from Azure Communication Services over websocket private async Task StartReceivingFromAcsMediaWebSocket() { if (m_webSocket == null) return; try { while (m_webSocket.State == WebSocketState.Open || m_webSocket.State == WebSocketState.Closed) { byte[] receiveBuffer = new byte[2048]; WebSocketReceiveResult receiveResult = await m_webSocket.ReceiveAsync(new ArraySegment<byte>(receiveBuffer), m_cts.Token); if (receiveResult.MessageType == WebSocketMessageType.Close) continue; var data = Encoding.UTF8.GetString(receiveBuffer).TrimEnd('\0'); if(StreamingData.Parse(data) is AudioData audioData) { using var ms = new MemoryStream(audioData.Data); await m_aiServiceHandler.SendAudioToExternalAI(ms); } } } catch (Exception ex) { Console.WriteLine($"Exception -> {ex}"); } } Streaming audio data back into Azure Communication Services //create and serialize streaming data private void ConvertToAcsAudioPacketAndForward( byte[] audioData ) { var audio = new OutStreamingData(MediaKind.AudioData) { AudioData = new AudioData(audioData) }; // Serialize the JSON object to a string string jsonString = System.Text.Json.JsonSerializer.Serialize<OutStreamingData>(audio); // Queue the async operation for later execution try { m_channel.Writer.TryWrite(async () => await m_mediaStreaming.SendMessageAsync(data)); } catch (Exception ex) { Console.WriteLine($"\"Exception received on ReceiveAudioForOutBound {ex}"); } } //Send encoded data over the websocket to Azure Communication Services public async Task SendMessageAsync(string message) { if (m_webSocket?.State == WebSocketState.Open) { byte[] jsonBytes = Encoding.UTF8.GetBytes(message); // Send the PCM audio chunk over WebSocket await m_webSocket.SendAsync(new ArraySegment<byte>(jsonBytes), WebSocketMessageType.Text, endOfMessage: true, CancellationToken.None); } } To reduce developer overhead when integrating with voice-based LLMs, Azure Communication Services supports a new sample rate of 24Khz, eliminating the need for developers to resample audio data and helping preserve audio quality in the process Next steps The SDK and documentation will be available in the next few weeks after this announcement, offering tools and information to integrate bidirectional streaming and utilize voice-based LLMs in your applications. Stay tuned and check our blog for updates!
