Azure IoT Operations 2510 Now Generally Available
Introduction We’re thrilled to announce the general availability of Azure IoT Operations 2510, the latest evolution of the adaptive cloud approach for AI in industrial and large scale commercial IoT. With this release, organizations can unlock new levels of scalability, security, and interoperability, empowering teams to seamlessly connect, manage, and analyze data from edge to cloud. What is Azure IoT Operations? Azure IoT Operations is more than an edge-to-cloud data plane, it’s the foundation for AI in physical environments, enabling intelligent systems to perceive, reason, and act in the real world. Built on Arc-enabled Kubernetes clusters, Azure IoT Operations unifies operational and business data across distributed environments, eliminating silos and delivering repeatability and scalability. By extending familiar Azure management concepts to physical sites, AIO creates an AI-ready infrastructure that supports autonomous, adaptive operations at scale. This approach bridges information technology (IT), operational technology (OT), and data domains, empowering customers to discover, collect, process, and send data using open standards while laying the groundwork for self-optimizing environments where AI agents and human supervisors collaborate seamlessly. We've put together a quick demo video showcasing the key features of this 2510 release. Watch below to discover how Azure IoT Operations' modular and scalable data services empowers IT, OT and developers. What’s New in Azure IoT Operations 2510? Management actions: Powerful management actions put you in control of processes and asset configurations, making operations simpler and smarter. Web Assembly (Wasm) data graphs: Wasm-powered data graphs for advanced edge processing, delivering fast, modular analytics and business logic right where your data lives. New connectors: Expanded connector options now include OPC UA, ONVIF, Media, REST/HTTP, and Server-Sent Events (SSE), opening the door to richer integrations across diverse industrial and IT systems. OpenTelemetry (OTel) endpoints: Data flows now support sending data directly to OpenTelemetry collectors, integrating device and system telemetry into your existing observability infrastructure. Improved observability: Real-time health status for assets gives you unmatched visibility and confidence in your IoT ecosystem. Reusable Connector templates: Streamline connector configuration and deployment across clusters. Device support in Azure Device Registry: Azure Device Registry (ADR) now treats devices as first‑class resources within ADR namespaces, enabling logical isolation and role‑based access control at scale. Automatic device and asset discovery and onboarding: Akri‑powered discovery continuously detects devices and industrial assets on the network, then automatically provisions and onboards them (including creating the right connector instances) so telemetry starts flowing with minimal manual setup. MQTT Data Persistence: Data can now be persisted to disk, ensuring durability across broker restarts. X.509 Auth in MQTT broker: The broker now supports X.509 authentication backed by Azure's Device Registry. Flexible RBAC: Built-in roles and custom role definitions to simplify and secure access management for AIO resources. Customers and partners Chevron, through its Facilities and Operations of the Future initiative, deployed Azure IoT Operations with Azure Arc to manage edge-to-cloud workloads across remote oil and gas sites. With a single management plane, the strategy unifies control over thousands of distributed sensors, cameras, robots, and drones. Real-time monitoring and AI enabled anomaly detection not only to enhance operational efficiency but also significantly improve worker safety by reducing routine inspections and enabling remote issue mitigation. This reuse of a global, AI-ready architecture positions Chevron to deliver more reliable, cleaner energy. [microsoft.com] Husqvarna implemented Azure IoT Operations across its global manufacturing network as part of a comprehensive strategy. This adaptive cloud approach integrates cloud, on-premises, and edge systems, preserves legacy investments, and enables real-time edge analytics. The result: data operationalization is 98% faster, imaging costs were slashed by half, productivity was improved, and downtime was reduced. Additionally, AI-driven capabilities like the Factory Companion powered by Azure AI empower technicians with instant, data-informed troubleshooting, shifting maintenance from reactive to predictive across sites. [microsoft.com] Together, these success stories show how Azure IoT Operations, combined with capabilities like Azure Arc, can empower industrial leaders to advance from siloed operations to unified, intelligent systems that boost efficiency, safety, and innovation. Additionally, this year we are celebrating how our partners are integrating, co-innovating, and scaling real customer outcomes. You can learn more about our partner successes at https://aka.ms/Ignite25/DigitalOperationsBlog. Learn more at our launch event Join us at Microsoft Ignite to dive deeper into the latest innovations in Azure IoT Operations 2510. Our sessions will showcase real-world demos plus expert insights on how new capabilities accelerate industrial transformation. Don’t miss the chance to connect with product engineers, explore solution blueprints, and see how Azure IoT Operations lays the foundation for building and scaling physical AI. Get Started Ready to experience the new capabilities in Azure IoT Operations 2510? Explore the latest documentation and quickstart guides at https://aka.ms/AzureIoTOperations Connect with the Azure IoT Tech Community to share feedback and learn from peers.The Art and Science of Prompting: AI fluency. mayoral delegate edition
Art and science of prompting is your gateway to unlocking citywide transformation. AI skills are now foundational for every city leader. The winners will be those who ask better questions, shape better prompts, and empower their teams to experiment, learn, and scale what works. This session will show you how to move from curiosity to action, and from pilot to policy The deck below is the best prompts I've curated over 2.5 years deeply testing, implementing, teaching, and scaling AI to governments and large companies around the world. These are the basis to the prompting skills you can gain to augment and supercharge your expertise. Slide 10 is my personal favorite -- the easy button -- i use it everyday and so should you. Start with an area you're already an expert in, and go deep with context. Get to your 'Aha moment' then rinse and repeat. Have fun!
Getting Started with AI and MS Copilot - French
Souhaitez-vous découvrir l’intelligence artificielle (IA) et Microsoft Copilot de manière pratique et ludique ? Nous vous invitons à participer à la séance intitulée « Introduction à l’IA et Microsoft Copilot », spécialement conçue pour les membres du corps enseignant qui débutent avec Microsoft Copilot. Cette séance vous permettra d’acquérir les notions fondamentales de l’IA générative, de comprendre comment formuler des requêtes efficaces (invites, ou « prompts ») et d’explorer comment appliquer ces outils en classe. Vous aurez accès à des supports pédagogiques que vous pourrez utiliser en classe et vous aurez l’occasion de mettre vos connaissances en pratique à travers 10 exercices. Rejoignez la réunion iciGetting Started with AI and MS Copilot - French
Souhaitez-vous découvrir l’intelligence artificielle (IA) et Microsoft Copilot de manière pratique et ludique ? Nous vous invitons à participer à la séance intitulée « Introduction à l’IA et Microsoft Copilot », spécialement conçue pour les membres du corps enseignant qui débutent avec Microsoft Copilot. Cette séance vous permettra d’acquérir les notions fondamentales de l’IA générative, de comprendre comment formuler des requêtes efficaces (invites, ou « prompts ») et d’explorer comment appliquer ces outils en classe. Vous aurez accès à des supports pédagogiques que vous pourrez utiliser en classe et vous aurez l’occasion de mettre vos connaissances en pratique à travers 10 exercices. Rejoignez la réunion iciPower Up Your Open WebUI with Azure AI Speech: Quick STT & TTS Integration
Introduction Ever found yourself wishing your web interface could really talk and listen back to you? With a few clicks (and a bit of code), you can turn your plain Open WebUI into a full-on voice assistant. In this post, you’ll see how to spin up an Azure Speech resource, hook it into your frontend, and watch as user speech transforms into text and your app’s responses leap off the screen in a human-like voice. By the end of this guide, you’ll have a voice-enabled web UI that actually converses with users, opening the door to hands-free controls, better accessibility, and a genuinely richer user experience. Ready to make your web app speak? Let’s dive in. Why Azure AI Speech? We use Azure AI Speech service in Open Web UI to enable voice interactions directly within web applications. This allows users to: Speak commands or input instead of typing, making the interface more accessible and user-friendly. Hear responses or information read aloud, which improves usability for people with visual impairments or those who prefer audio. Provide a more natural and hands-free experience especially on devices like smartphones or tablets. In short, integrating Azure AI Speech service into Open Web UI helps make web apps smarter, more interactive, and easier to use by adding speech recognition and voice output features. If you haven’t hosted Open WebUI already, follow my other step-by-step guide to host Ollama WebUI on Azure. Proceed to the next step if you have Open WebUI deployed already. Learn More about OpenWeb UI here. Deploy Azure AI Speech service in Azure. Navigate to the Azure Portal and search for Azure AI Speech on the Azure portal search bar. Create a new Speech Service by filling up the fields in the resource creation page. Click on “Create” to finalize the setup. After the resource has been deployed, click on “View resource” button and you should be redirected to the Azure AI Speech service page. The page should display the API Keys and Endpoints for Azure AI Speech services, which you can use in Open Web UI. Settings things up in Open Web UI Speech to Text settings (STT) Head to the Open Web UI Admin page > Settings > Audio. Paste the API Key obtained from the Azure AI Speech service page into the API key field below. Unless you use different Azure Region, or want to change the default configurations for the STT settings, leave all settings to blank. Text to Speech settings (TTS) Now, let's proceed with configuring the TTS Settings on OpenWeb UI by toggling the TTS Engine to Azure AI Speech option. Again, paste the API Key obtained from Azure AI Speech service page and leave all settings to blank. You can change the TTS Voice from the dropdown selection in the TTS settings as depicted in the image below: Click Save to reflect the change. Expected Result Now, let’s test if everything works well. Open a new chat / temporary chat on Open Web UI and click on the Call / Record button. The STT Engine (Azure AI Speech) should identify your voice and provide a response based on the voice input. To test the TTS feature, click on the Read Aloud (Speaker Icon) under any response from Open Web UI. The TTS Engine should reflect Azure AI Speech service! Conclusion And that’s a wrap! You’ve just given your Open WebUI the gift of capturing user speech, turning it into text, and then talking right back with Azure’s neural voices. Along the way you saw how easy it is to spin up a Speech resource in the Azure portal, wire up real-time transcription in the browser, and pipe responses through the TTS engine. From here, it’s all about experimentation. Try swapping in different neural voices or dialing in new languages. Tweak how you start and stop listening, play with silence detection, or add custom pronunciation tweaks for those tricky product names. Before you know it, your interface will feel less like a web page and more like a conversation partner.Announcing the new Microsoft Learn Plan - Preparing for your organization's AI workloads
We're pleased to announce the new "Preparing for your organization's AI workloads" Microsoft Learn Plan - focused the IT/Ops audience and now available on Microsoft Learn! This set of content was curated by our team and is targeted at helping IT Professionals who want to learn how to support their organization's AI applications and infrastructure. The Learning Plan is composed of 4 milestones, which in its turn are composed of a total of 22 modules: Milestone 1: Getting Started with AI on Microsoft Azure - Learning Path: Introduction to AI in Azure - 12 modules Milestone 2: Introduction to AI Services Infrastructure on Azure - Learning Path: Manage Authentication, Authorization, and RBAC for AI Workloads on Azure - 3 modules - Learning Path: Manage Network Access for AI Workloads - 2 modules Milestone 3: Monitoring AI Services on Azure - Learning Path: Monitor AI Workloads on Azure - 3 modules Milestone 4: Advanced Management of AI Workloads on Azure - Learning Path: AI Workload Governance and DLP - 2 modules This comprehensive plan introduces foundational AI concepts, then guides you through advanced topics. Whether you're an IT administrator, security specialist, or AI practitioner, this plan equips you with the skills to build trusted, secure, and compliant AI solutions at scale. We hope you enjoy learning! Let us know what you think about this content in the comment section below! If you'd like to see more of this type of content, or have any suggestions, let us know as well!AZ-500: Microsoft Azure Security Technologies Study Guide
The AZ-500 certification provides professionals with the skills and knowledge needed to secure Azure infrastructure, services, and data. The exam covers identity and access management, data protection, platform security, and governance in Azure. Learners can prepare for the exam with Microsoft's self-paced curriculum, instructor-led course, and documentation. The certification measures the learner’s knowledge of managing, monitoring, and implementing security for resources in Azure, multi-cloud, and hybrid environments. Azure Firewall, Key Vault, and Azure Active Directory are some of the topics covered in the exam.Getting Started with AI and MS Copilot — French
Souhaitez-vous découvrir l’intelligence artificielle (IA) et Microsoft Copilot de manière pratique et ludique ? Nous vous invitons à participer à la séance intitulée « Introduction à l’IA et Microsoft Copilot », spécialement conçue pour les membres du corps enseignant qui débutent avec Microsoft Copilot. Cette séance vous permettra d’acquérir les notions fondamentales de l’IA générative, de comprendre comment formuler des requêtes efficaces (invites, ou « prompts ») et d’explorer comment appliquer ces outils en classe. Vous aurez accès à des supports pédagogiques que vous pourrez utiliser en classe et vous aurez l’occasion de mettre vos connaissances en pratique à travers 10 exercices. Rejoignez la réunion iciTrain a simple Recommendation Engine using the new Azure AI Studio
The AI Studio Odyssey: Embark on a journey to the heart of personalization with our latest guide, “Train a Simple Recommendation Engine using the new Azure AI Studio.” Unlock the secrets of the all-new Azure AI Studio intuitive tools to craft a recommendation system that feels like magic, yet is grounded in data and user preferences. Ready to enchant your audience? Grab some popcorn and read on!Utilizando un archivo en GitHub Copilot para Visual Studio
Cuando creas un nuevo proyecto desde cero en Visual Studio, algunos archivos se crean. Hay muchas plantillas disponibles, para muchos tipos de aplicaciones, desde aplicaciones simples hasta aplicaciones web complejas, así como aplicaciones móviles, sin servidor y muchas más. Todos estos proyectos constan de varios archivos. Tienes tus archivos de código, que contienen el software que se ejecutará, organizados en clases, frecuentemente cada clase en su propio archivo. Tienes los archivos de configuración, ya sea JSON, XML, YAML u otros. Incluso puedes tener archivos de datos, incrustados en la aplicación cuando está construida. En un video que se publicó, mi compañera Gwyn muestra cómo puedes usar el atajo Hash (#) para hacer referencia a otro archivo. [Este post es una traducción del blog original escrito en inglés por Laurent Bugnion y Gwyn Peña-Sigüenza] El contexto lo es todo Como mencionamos en varias ocasiones, lo que hace que una respuesta de GitHub Copilot sea buena comienza con un buen prompt. Sin embargo, el prompt no es solo pedirle al modelo de lenguaje que haga algo; también es necesario proporcionar contexto. En el mundo de la IA, nos referimos a esto como 'grounding' del modelo con datos, o Generación Aumentada por Recuperación (RAG). A través de su entrenamiento, Copilot tiene acceso a conocimientos generales sobre la plataforma que estás utilizando, así como a conocimientos específicos sobre bibliotecas y frameworks. Sin embargo, lo que falta es tu propio código privado, el código que el resto del mundo no ve. Por ejemplo, puedes informar a GitHub Copilot que otro archivo contiene una serie de métodos que la clase actual puede utilizar. En el ejemplo, Gwyn le indica a GitHub Copilot un archivo JSON que contiene datos para generar una prueba. Esto añade un contexto valioso, permitiendo que Copilot genere el código correcto de manera más rápida. Más información Como siempre, puedes encontrar muchos recursos educativos gratuitos en esta colección de Microsoft Learn. Y, por supuesto, la mejor manera de estar al día es suscribirse al canal de YouTube de Visual Studio, al Visual Studio DevBlog y, por supuesto, a este blog.
