Kategorie: Microsoft Azure

Oracle Database@Azure offers new features, regions, and programs to unlock data and AI innovation

Together, Microsoft and Oracle are delivering the most comprehensive, enterprise‑ready platform for organizations migrating their Oracle solutions to the public cloud—especially those aiming to empower IT professionals and developers to streamline AI adoption and enhance employee productivity.

Oracle Database@Azure was the first offering of its kind in the market and today has the broadest regional availability, new ways to unify your data in Microsoft Fabric, deeper security integrations with Microsoft Defender, and can run most Oracle Database services—Base Database Service, Exadata Database Service on Dedicated Infrastructure, Exadata Database Service on Exascale Infrastructure and Autonomous Database as well as Oracle Database 19c or 23ai—on Azure.

Get started with Oracle Database@Azure

The result? A truly enterprise‑ready platform that offers more choice, increased control, and expanded opportunity to innovate with confidence–and customers are excited about the impact it’s driving in action.

Oracle Database@Azure delivered Exadata-grade performance natively within Azure, enabling us to host our Oracle EBS in the cloud without compromise. We gained native, real-time access to EBS data from Azure and seamless integration with both Oracle and non-Oracle data sources. Paired now with Microsoft Fabric, Power BI, and Copilot studio, our team will be able to accelerate insight delivery to business stakeholders and build agentic workflows faster. It’s a practical path to iterate on new features while keeping governance and security at the forefront.
Mahesh Tyagi, Vice President Finance Engineering, Activision Blizzard 

New Oracle Database@Azure features strengthen its enterprise leadership

Enterprise-grade capabilities are essential for organizations that depend on Oracle databases for mission-critical workloads. That’s why Microsoft continues to advance Oracle Database@Azure, bringing together the scale and resilience of Azure with industry-leading security and AI innovation.

Take a look at our latest announcements. For more details on each of these capabilities, check out our technical blog.

Announcing two new capabilities for real-time data integration and replication with Microsoft Fabric for an AI-ready data estate

Oracle Database mirroring in OneLake, now in public preview, enables continuous zero-ETL synchronization of Oracle data into OneLake, enabling a unified real-time data estate in Microsoft Fabric. Also available today, native Oracle GoldenGate integration offers managed, high-performance, low-latency replication and can be purchased using Microsoft Azure Consumption Commitment (MACC). Once your Oracle data is connected through Oracle Database@Azure, you can use powerful AI innovation tools like Microsoft Copilot Studio, Azure AI Foundry, and Power BI.

Oracle Base Database is generally available

Oracle Database@Azure offers customers the flexibility to run any Oracle Database service on Azure. Oracle Database@Azure now supports all popular Oracle database services—Base Database Service, Exadata Database Service on Dedicated Infrastructure, Exadata Database Service on Exascale Infrastructure and Autonomous Database—and also the choice of using either Oracle Database 19c or 23ai. This provides customers with a comprehensive set of flexible, simple, and cost-effective migration options when moving their Oracle databases to Azure.

Support for Oracle workloads goes beyond Oracle Database services. We’re excited to share that Oracle has introduced support policies for running Oracle E-Business Suite, PeopleSoft, JD Edwards EnterpriseOne, Enterprise Performance Management, and Oracle Retail Applications in Microsoft Azure using Oracle Database@Azure. This enables businesses to harness the power of Microsoft Azure while leveraging Oracle’s industry-leading database technology to achieve greater scalability, performance, and security. We continue to offer full Oracle Maximum Availability (MAA) support—up to platinum tier—available exclusively on Azure, giving customers the highest levels of availability, disaster recovery, and zero-data-loss protection for mission critical workloads.

Microsoft Defender now brings industry-leading threat detection and response to Oracle Database@Azure

Microsoft Defender is a cloud-native security platform that provides unified threat protection, vulnerability management, and automated compliance to safeguard Oracle Database@Azure workloads. Complemented by Microsoft Sentinel’s AI-powered security information and event management (SIEM) for real-time monitoring, and Microsoft Entra ID’s unified identity and access controls, customers get comprehensive enterprise-grade protection designed for today’s complex threat landscape.  

Azure Arc for Oracle Database@Azure

Extend Azure’s management, governance, and security capabilities across environments—whether on-premises, multicloud or edge. From a single control plane, Azure Arc enables you to enforce policies, manage identities, and automate lifecycle operations for all your Azure resources—and now, for your Oracle databases running natively on Azure. 

Azure IoT Operations and Microsoft Fabric now power an integration blueprint with Oracle Fusion Cloud Supply Chain and Manufacturing (SCM)

This integration enables manufacturers to capture live insights from factory equipment and sensors, automate key processes, and drive data‑driven decisions for greater efficiency and responsiveness.

Available in over 28 regions globally

With plans to reach 33 live regions by the end of the year, Oracle Database@Azure empowers organizations to deploy closer to their applications and users across North America, EMEA, and APAC. Stay up to date on the latest regions to go live here.

Introducing Azure Accelerate for Oracle

To help every organization start quickly and confidently—regardless of their size—Microsoft is excited to offer Azure Accelerate benefits to Oracle customers. Azure Accelerate is a program designed to support customers across their cloud and AI journey with expert guidance and investments. Customers can cut through the complexity of their Oracle migrations—and related application migration, modernization, and AI innovation projects—while also minimizing project costs. Azure Accelerate makes it easier than ever to bring your Oracle workloads to Azure by offering:

Access to trusted experts: Tap into the deep expertise of Azure’s specialized partner ecosystem. Additionally, you can take advantage of the Cloud Accelerate Factory benefit provides Microsoft experts at no additional cost.

Microsoft investments: Access Partner funding and Azure credits designed to make your migration to Azure more cost effective and minimize project risk.

Comprehensive coverage: Get help at every stage of the project, starting with an initial assessment through pilots or proof-of-value to full-scale implementation.

With Azure Accelerate, Oracle customers can now migrate more efficiently while integrating AI into their strategy, alongside Azure experts from day one.

Channel partners can now resell Oracle Database@Azure

Microsoft AI Cloud Partners and Oracle Partner Network (OPN) members can now purchase and resell Oracle Database@Azure—right from the Microsoft Marketplace. This new model underscores Microsoft and Oracle’s joint commitment to the partner community while streamlining migration and modernization for customers who prefer to purchase through their trusted partners.

Microsoft’s partner reseller programme helped CGI select Oracle Database@Azure to consolidate cloud services under a single cloud provider, ensuring cost efficiency, elasticity and redundancy required to meet CGI’s client key requirements. For Smart DCC, CGI is working with Oracle and Microsoft to implement the solution through the Microsoft marketplace reseller model, providing a streamlined procurement route on a secure, enterprise-ready platform for mission-critical workloads.
Ro Crawford, VP Consulting Services, CGI

We are also excited to share that Oracle Database@Azure is now included in the Microsoft Most Valuable Professionals (MVP) program under the new technology area, Azure Solutions and Ecosystem. This new technology area spans mission-critical workloads and modernization efforts, including Oracle Database@Azure, Azure VMware Solution (AVS), Nutanix on Azure, and mainframe modernization strategies. Microsoft Most Valuable Professionals program recognizes exceptional community leaders for their technical expertise, leadership, speaking experience, online influence, and commitment to solving real world problems. To learn more about the program, visit this FAQ.

Oracle Database@Azure customer momentum

Customers like Conduent, BV Liantis, SEFE, Astellas Pharmacy, Craneware and Medline have moved their Oracle databases to Oracle Database@Azure to optimize performance and reduce latency while unlocking a future-ready foundation for AI. 

We’re excited to spotlight our customer innovation in our sessions at Oracle AI World. Don’t miss Activision Blizzard on stage for Microsoft’s Spotlight Session on Wednesday, October 15 at 4:45 PM PT. You can find our full session list and featured customers here. 

Get started
Oracle Database@Azure is an Oracle database service running on Oracle Cloud Infrastructure (OCI), colocated in Microsoft data centers

Learn more here

Looking ahead

We’re excited to continue this journey—bringing together the best of Oracle and Microsoft to help customers innovate faster, operate smarter, and lead in the era of intelligent applications.

If you’re attending Oracle AI World 2025, come talk to our experts at the Microsoft booth (#3005) and be sure to check out our sessions.

Learn more about Oracle on Azure | Microsoft Azure.

To get started, contact our sales team.
The post Oracle Database@Azure offers new features, regions, and programs to unlock data and AI innovation appeared first on Microsoft Azure Blog.
Quelle: Azure

Sora 2 now available in Azure AI Foundry

Turning imagination into reality has never been more instantaneous—and powerful—as it is today, with the launch of OpenAI’s Sora 2: Now in public preview in Azure AI Foundry.

Azure AI Foundry is the developer destination built for creators, from startups to global businesses. The platform now offers a curated catalog of generative media models, including OpenAI’s Sora, GPT-image-1 and GPT-image-1-mini, Black Forest Lab’s Flux 1.1 and Kontext Pro, and more. These models empower software development companies and builders to serve creatives with new and unique capabilities—to accelerate storyboarding, drive engagement, and transform the creative process, all without sacrificing the safety, reliability, and integration businesses expect.

Start creating with Sora 2 in Azure AI Foundry

What can you create with Sora 2 in Azure AI Foundry?

Sora 2 in Azure AI Foundry isn’t just another video generation tool; it’s a creative powerhouse, seamlessly integrated into a platform built for innovation, trust, and scale. Unlike standalone solutions, Azure AI Foundry offers a unified platform where developers can access Sora 2 alongside other leading generative models in a secure, scalable, and structured environment to achieve more:

Marketers can rapidly produce stunning, branded campaign assets including animated assets for product launches and personalized content to capture attention and drive engagement.

Retailers can engage customers with interactive and localized campaigns to accelerate time-to-market and transform their customers’ online shopping experience.

Creative directors can transform imaginative ideas into dynamic movie trailers and cinematic experiences to test concepts, while Sora 2’s realistic world simulation, synchronized audio, and creative controls help bring visions to life.

Educators can create immersive lesson plans and interactive media that spark curiosity and deepen understanding.

With Sora 2 in Azure AI Foundry, developers across industries can innovate boldly and confidently. Azure AI Foundry’s unified environment, advanced capabilities, and enterprise-grade security provide the foundation for creativity to flourish and ideas to become reality.

What features and controls are available?

Sora 2 in Azure AI Foundry stands out by combining OpenAI’s most advanced video generation capabilities with the trusted infrastructure and security controls of Microsoft Azure, unlocking new possibilities for every developer with a set of core features:

Realistic video generation powered by advanced world simulation and physics.

Generation based on input text, images, and video.

Synchronized audio and dialogue for immersive storytelling.

Audio available in multiple languages.

Enhanced creative control, including detailed prompt understanding for studio shots, scene details, and camera angles.

Seamless integration into business workflows, backed by Microsoft’s enterprise-grade safety and security.

Microsoft is committed to delivering secure and safe AI solutions for organizations of all sizes. Through Azure AI Foundry and our responsible AI principles, we empower customers with embedded security, safety, and privacy controls.

This foundation extends to Sora 2, where our advanced safety systems and robust controls work together to help developers innovate more confidently in Azure AI Foundry:

Content filters for inputs: Screens text, image, and video inputs for prompts. 

Content filters for outputs: Analyzes video frames and audio; can block content to help comply with organizational policies.

Enterprise-grade security: Azure’s compliance and governance frameworks protect customer data and creative assets. 

Sora 2 Azure AI Foundry pricing and availability

Starting today, Sora 2 is available via API through Standard Global in Azure AI Foundry.

ModelSizePrice per second (in USD)
Sora 2
Portrait: 720×1280 Landscape: 1280×720
$0.10

Please refer to the Azure AI Foundry Models page for future updates in deployment types and availability.

Get started with AI as your creative partner

Sora 2 is designed to empower and inspire developers. By accelerating early production and enabling rapid prototyping, Sora 2 frees up time for more ideation and storytelling. The goal is to bring human creativity to the next level, making it easier for anyone to turn ideas into compelling visual stories.

Ready to create with Sora 2?
Explore the full catalog of generative media models in Azure AI Foundry.

Get started

The post Sora 2 now available in Azure AI Foundry appeared first on Microsoft Azure Blog.
Quelle: Azure

From queries to conversations: Unlock insights about your data using Azure Storage Discovery—now generally available

We are excited to announce the general availability of Azure Storage Discovery, a fully managed service that delivers enterprise-wide visibility into your data estate in Microsoft Azure Blob Storage and Azure Data Lake Storage. Azure Storage Discovery helps you optimize storage costs, comply with security best practices, and drive operational efficiency. With the included Microsoft Copilot in Azure integration, all decision makers and data users can access and uncover valuable data management insights using simple, everyday language—no specialized programming or query skills required. The intuitive experience provides advanced data visualizations and actional intelligence that are most important to you.

 What is Azure Storage Discovery?

Businesses are speeding up digital transformation by storing large amounts of data in Azure Storage for AI, analytics, cloud native apps, HPC, backup, and archive. This data spans multiple subscriptions, regions, and accounts to meet workload needs and compliance rules. The data sprawl makes it challenging to track data growth, spot unexpected data reduction, or optimize costs without clear visibility into data trends and access patterns. Organizations struggle to identify which datasets and business units drive growth and usage the most. Without a global view and streamlined insights across all storage accounts, it’s challenging to ensure data availability, residency, security, and redundancy are consistently aligned with best practices and regulatory compliance requirements.

Azure Storage Discovery makes it simple to gain and analyze insights to manage such large data estates.

Analyze your data estate with Azure Storage Discovery

Azure Storage Discovery lets you easily set up a workspace with storage accounts from any region or subscription you can access. The first insights are available in less than 24 hours, and you can get started by analyzing your data estate.

Unlock intelligent insights using natural language with Copilot in Azure

Use natural language to ask for the storage insights you need to accomplish your storage management goals. Copilot in Azure expresses them using rich data visualizations, like tables and charts.

Interactive reports built into the Azure portal

Azure Storage Discovery generates out-of-box dashboards you can access from the Azure portal, with insights that help you visualize and analyze your data estate. The reports include filters for your storage data estate by region, redundancy, and performance, allowing you to quickly drill down and uncover the insights important to you.

Advanced storage insights

The reports deliver insights, at a glance, across multiple dimensions, helping you manage your data effectively:

Capacity: Insights about resource, object sizes, and counts aggregated by subscriptions, resource groups, and storage accounts with growth trends.

Activity: Visualize transactions, ingress, and egress for insights on how your storage is accessed and utilized.

Security: Highlights critical security configurations of your storage resources with outliers including public network access, shared access key, anonymous access to blobs, and encryption settings.

Configurations: Surfaces configuration patterns across your storage accounts like redundancy, lifecycle management, inventory, and others.

Errors: Highlights failed operations and error codes to help identify patterns of issues that might be impacting workloads.

Kickstart your insights for free, including 15 days of historical data

Getting started is easy with access to 15 days of historical insights within hours of deploying your Azure Storage Discovery workspace. The standard pricing plan offers the most comprehensive set of insights, while the free pricing plan gets you going with the basics.

Analyze long term trends with 18 months of insights

The Azure Storage Discovery workspace with the standard pricing plan, will retain insights for up to 18 months so you can analyze long-term trends and any business or season specific workload patterns.

Azure Storage Discovery is available to you today! You can learn more about Azure Storage Discovery here and even get started in the Azure Portal here.

Use Copilot to solve the most important business problems

During the design of Azure Storage Discovery, we spoke with many customers across various business-critical roles, such as IT managers, data engineers, and CIOs. We realized AI could simplify onboarding by removing the need for infrastructure deployment or coding knowledge. As a result, we included Copilot in Azure Storage Discovery from the start. It offers insights beyond standard reports and dashboards using natural language queries to deliver actionable information through visualizations like trend charts and tables.

To get started, simply navigate to your Azure Storage Discovery workspace resource in the Azure portal, and activate Copilot.

Identify opportunity to optimize costs

Understanding storage size trends is crucial for cost optimization, and analyzing these trends by region and performance type can reveal important patterns about how the data is evolving over time. With Azure Storage Discovery’s 18 months of data retention, you can uncover long-term trends and unexpected changes across your data estate, while Copilot quickly visualizes storage size trends broken down by region.

“How is the storage size trending over the past month by region?”

Finding cost-saving opportunities across many storage accounts can be difficult, but Copilot simplifies this by highlighting accounts with the highest savings potential based on capacity and transactions as shown below.

“Provide a list of storage accounts with default access tier as Hot, that are above 1TiB in size and have the least transactions”

Before taking any action, you can dive even deeper into the insights by evaluating distributions. For example, a distribution of access tiers across blobs.

“Show me a chart of blob count by blob access tier”

Knowing that the majority of objects are still in the Hot tier provides immediate opportunities to reduce costs by enabling Azure Storage Actions to tier down or even delete data that is not accessed frequently. Azure Storage Actions is a fully managed, serverless platform that automates data management tasks—like tiering, retention, and metadata updates—across millions of blobs in Azure Blob Storage and Data Lake Storage.

Assess whether storage configurations align with security best practices

For better storage security, Microsoft recommends using Microsoft Entra ID with managed identities instead of Shared Key authentication. Azure Storage Discovery enables you to quickly see that there are still many storage accounts with shared access keys enabled and drill down into a list of Storage accounts that need optimization.

“Show me a pie chart of my storage accounts with shared access key enabled by region”

Manage your data redundancy requirements

Azure provides several redundancy options to meet data availability, disaster recovery, performance, and cost needs. These choices should be regularly reviewed against risks and benefits for an effective storage strategy. Azure Storage Discovery quickly shows the redundancy configuration for all storage accounts and allows you to analyze the most suitable option for each workload and critical business data.

“Show me a chart of my storage account count by redundancy”

Pricing and availability

A single Azure Storage Discovery workspace can analyze the subscriptions and storage accounts from all supported regions. Learn more about the regions supported by Azure Storage Discovery here. The service offers a free pricing plan with insights related to capacity and configurations retained for up to 15 days and a standard pricing plan that also includes advanced insights related to activity, errors, and security configurations. Insights are retained for up to 18 months, allowing you to analyze trends and business cycles.

Learn more about the pricing plans in the Azure Storage Discovery documentation and access the prices for your region here.

Get started with Azure Storage Discovery

Getting started with Azure Storage Discovery is easy. Simply follow these two steps:

Configure an Azure Storage Discovery workspace and select the set of subscriptions and resource groups containing your storage accounts.

Define the “Scopes” that represent your business groups or workloads.

That’s it! Give it a moment. Once a workspace is configured, Azure Storage Discovery starts aggregating the relevant insights and makes them available to you via intuitive charts. You’ll find them in the Azure portal, on different report pages of your workspace. We’ll even look back in time and provide 15 days of historic data. Your insights are typically available within a few hours.

To get started, visit Azure Storage Discovery in the Azure Marketplace.

You can also deploy via the brand new Storage Center in the Azure portal. Find Azure Storage Discovery in the “Data management” section.

Want to read more before deploying? The planning guide walks you through all the important considerations for a successful Azure Storage Discovery deployment.

We’d love to hear your feedback. What insights are most valuable to you? What would make Azure Storage Discovery more valuable for your business? Let us know at: StorageDiscoveryFeedback@service.microsoft.com.

Get started with Azure Storage Discovery
Azure Storage Discovery integrates with Copilot in Azure, enabling you to unlock insights and accelerate decision-making without utilizing any query language.

Find the overview here

The post From queries to conversations: Unlock insights about your data using Azure Storage Discovery—now generally available appeared first on Microsoft Azure Blog.
Quelle: Azure

Microsoft’s commitment to supporting cloud infrastructure demand in Asia

Microsoft supports cloud infrastructure demand in Asia

As Asia surges ahead in digital transformation, Microsoft is committed to expanding its cloud infrastructure to match the continent’s demand. In 2025, Microsoft launched new Azure datacenter regions in Malaysia and Indonesia, and is set to expand further with new datacenter regions launching in India and Taiwan in 2026. Microsoft is also announcing our intent to deliver a second datacenter region in Malaysia, called Southeast Asia 3. Across Asian markets, the company is investing billions to expand its AI infrastructure footprint—bringing cutting-edge AI, next-generation networking, and scalable storage to the world’s most populus area. These investments will empower enterprises across Asia to scale seamlessly, unlock the full value of their data, and capture new opportunities for growth.

Learn more about Microsoft Cloud Adoption Framework for Azure

Microsoft’s global infrastructure spans over 70 datacenter regions across 33 countries—more than any other cloud provider—designed to meet data residency, compliance, and performance. In Asia, where businesses across financial services, public sector, manufacturing, retail, and start-ups are deeply integrated into the global economy, Microsoft’s strategically distributed datacenters deliver seamless scalability, low-latency connectivity, and regulatory assurance. By keeping critical data and applications close on fault-tolerant, high-capacity networking infrastructure, organizations can operate confidently across local and international markets—delivering fast, reliable services that meet customer expectations and comply with legal requirements.

With a dozen datacenter regions already live across Asia, we are making significant datacenter region investments to expand across the continent. These investments will become some of our most integral datacenters in the region:

East Asia

East Asia, an historically established market in our Japan and Korea geographies, will see continued growth and expansion. In April 2025, Microsoft launched Azure Availability Zones in the Japan West region—enhancing resilience and efficiency as part of a two-year plan to invest in Japan’s AI and cloud infrastructure.

Additionally, Microsoft announced the launch of Microsoft 365 and associated data residency offerings for commercial customers in the Taiwan North cloud region. Azure services are also accessible to select customers in this region, with general availability for all customers expected in 2026.

Southeast Asia nations

Microsoft is also deepening its commitment in Southeast Asia countries through substantial investments, marked by the launch of new cloud regions in Indonesia and Malaysia in May 2025. The recently launched regions are designed with AI-ready hyperscale cloud infrastructure and three availability zones, providing organizations across Southeastern Asia with secure, low-latency access to cloud services.

The recently launched Indonesia Central region is a welcome addition to this area of the world. It offers comprehensive Azure services and local Microsoft 365 availability, unlocking new capabilities to allow customers to innovate. Our continued investments in Indonesia are expected to drive significant expansion, positioning this datacenter region to become one of the largest regions in Asia over the coming years. Today, more than 100 organizations are already using the Microsoft Cloud from Indonesia, to accelerate their transformation, including:

Binus University is leveraging Azure Machine Learning and Azure OpenAI Service to enhance both campus operations and student learning. AI enables accurate student intake forecasting and automates diploma supplement summaries for over 10,000 graduates annually, improving operational efficiency. On the academic side, BINUS is developing AI-powered tools like personalized AI Tutors, generative AI in libraries for tailored book recommendations, and the Beelingua platform for interactive language learning, all aimed at creating a more adaptive, inclusive, and future-ready educational experience.

GoTo Group integrates GitHub Copilot into its engineering workflow, aiming to boost productivity and innovation. Nearly a thousand engineers have adopted the AI-powered coding assistant, which offers real-time suggestions, chat-based help, and simplified explanations of complex code, significantly speeding up the time to innovate.

Customers such as Adaro, BCA, Binus University, Pertamina, Telkom Indonesia, and Manulife have joined the Indonesia Central cloud region, gaining on-premises access to Microsoft’s hyperscale infrastructure.

The Malaysia West datacenter region, our first cloud region in the country, helps empower Malaysia’s digital and AI transformation with access to Azure and Microsoft 365. A diverse group of organizations, enterprises, and startups are already leveraging the Malaysia West region including:

PETRONAS, Malaysia’s global energy and solutions provider, is partnering with Microsoft to leverage hyperscale cloud infrastructure to continue advancing its digital and AI transformation, as well as clean energy transition efforts in Asia.

Other customers using Microsoft’s new cloud region include FinHero, SCICOM Berhad, Senang, SIRIM Berhad, TNG Digital (the operator of TNG eWallet), and Veeam, along with more organizations expected to come onboard as demand for secure, scalable, and locally-hosted cloud services continues to grow across industries.

In Malaysia, Microsoft is expanding its digital infrastructure footprint further with a new datacenter region, Southeast Asia 3, planned in Johor Bahru. When this next-generation region comes online, it will feature Microsoft’s most comprehensive and strategic cloud services, designed to support advanced workloads and evolving customer needs from across the area.  

In addition to Indonesia and Malaysia, Microsoft also announced in 2024, a significant commitment to enable a cloud and AI-powered future for Thailand.

India sub-continent

The India geography already has several live datacenter regions, and this footprint will expand further with the launch of the Hyderabad-based India South Central datacenter region coming in 2026. This is a part of a US $3 billion investment over two years in India cloud and AI infrastructure.

Consider a multi-region approach

Microsoft’s goal is to empower you to build and grow your business with unparalleled performance and availability. One of the best ways to position your organization for growth is to consider how you choose the right Azure regions.

Our infrastructure investments in Asia are driven by the need for greater agility and flexibility in today’s dynamic cloud environment. Organizations can build a more resilient foundation by not locking themselves into a single region, all while optimizing performance. This enables access to Azure services, resources, and capacity across a broader set of geographic areas. A multi-region approach allows businesses to rapidly adapt to changing demands while maintaining high service levels. Our cloud infrastructure supports this agility by distributing services across regions, helping ensure responsiveness and scalability during peak usage. Leveraging a multi-region cloud architecture with any of our Asia-based regions further strengthens application performance, latency, and overall resilience and availability of cloud applications—empowering organizations to stay ahead in a fast-evolving digital landscape.

Opportunities for cost optimization

Pricing is a critical factor when selecting the right Azure regions for your organization. Through our significant investments in Asia, Microsoft is now able to offer newer and more cost-effective Azure regions, catering to both small and large organizations. Our newest regions like Indonesia Central, are designed to provide greater choice and flexibility, enabling businesses to optimize their cloud expenditures while maintaining high performance and availability.

Boost your cloud strategy

Use the Cloud Adoption Framework to achieve your cloud goals with best practices, documentation, and tools for business and technology strategies.

Use the Well Architected Framework to optimize workloads with guidance for building reliable, secure, and performant solutions on Azure.

By choosing to deploy services through any of our Azure regions, customers can leverage the diverse and robust infrastructure that Microsoft is developing across Asia. This approach not only offers resilience and flexibility but also paves the way for innovative solutions that drive economic growth and a more connected future.

Learn more about Cloud Adoption Framework

The post Microsoft’s commitment to supporting cloud infrastructure demand in Asia appeared first on Microsoft Azure Blog.
Quelle: Azure

Microsoft Azure delivers the first large scale cluster with NVIDIA GB300 NVL72 for OpenAI workloads

Microsoft delivers the first at-scale production cluster with more than 4,600 NVIDIA GB300 NVL72, featuring NVIDIA Blackwell Ultra GPUs connected through the next-generation NVIDIA InfiniBand network. This cluster is the first of many, as we scale to hundreds of thousands of Blackwell Ultra GPUs deployed across Microsoft’s AI datacenters globally, reflecting our continued commitment to redefining AI infrastructure and collaboration with NVIDIA. The massive scale clusters with Blackwell Ultra GPUs will enable model training in weeks instead of months, delivering high throughput for inference workloads. We are also unlocking bigger, more powerful models, and will be the first to support training models with hundreds of trillions of parameters.

This was made possible through collaboration across hardware, systems, supply chain, facilities, and multiple other disciplines, as well as with NVIDIA.

Power groundbreaking AI innovation with Azure AI Infrastructure

Microsoft Azure’s launch of the NVIDIA GB300 NVL72 supercluster is an exciting step in the advancement of frontier AI. This co-engineered system delivers the world’s first at-scale GB300 production cluster, providing the supercomputing engine needed for OpenAI to serve multitrillion-parameter models. This sets the definitive new standard for accelerated computing.
Ian Buck, Vice President of Hyperscale and High-performance Computing at NVIDIA

From NVIDIA GB200 to GB300: A new standard in AI performance

Earlier this year, Azure introduced ND GB200 v6 virtual machines (VMs), accelerated by NVIDIA’s Blackwell architecture. These quickly became the backbone of some of the most demanding AI workloads in the industry, including for organizations like OpenAI and Microsoft who already use massive clusters of GB200 NVL2 on Azure to train and deploy frontier models.

Now, with ND GB300 v6 VMs, Azure is raising the bar again. These VMs are optimized for reasoning models, agentic AI systems, and multimodal generative AI. Built on a rack-scale system, each rack has 18 VMs with a total of 72 GPUs:

72 NVIDIA Blackwell Ultra GPUs (with 36 NVIDIA Grace CPUs).

800 gigabits per second (Gbp/s) per GPU cross-rack scale-out bandwidth via next-generation NVIDIA Quantum-X800 InfiniBand (2x GB200 NVL72).

130 terabytes (TB) per second of NVIDIA NVLink bandwidth within rack.

37TB of fast memory.

Up to 1,440 petaflops (PFLOPS) of FP4 Tensor Core performance.

Building for AI supercomputing at scale

Building infrastructure for frontier AI requires us to reimagine every layer of the stack—computing, memory, networking, datacenters, cooling, and power—as a unified system. The ND GB300 v6 VMs are a clear representation of this transformation, from years of collaboration across silicon, systems, and software.

At the rack level, NVLink and NVSwitch reduce memory and bandwidth constraints, enabling up to 130TB per second of intra-rack data-transfer connecting 37TB total of fast memory. Each rack becomes a tightly coupled unit, delivering higher inference throughput at reduced latencies on larger models and longer context windows, empowering agentic and multimodal AI systems to be more responsive and scalable than ever.

To scale beyond the rack, Azure deploys a full fat-tree, non-blocking architecture using NVIDIA Quantum-X800 Gbp/s InfiniBand, the fastest networking fabric available today. This ensures that customers can scale up training of ultra-large models efficiently to tens of thousands of GPUs with minimal communication overhead, thus delivering better end-to-end training throughput. Reduced synchronization overhead also translates to maximum utilization of GPUs, which helps researchers iterate faster and at lower costs despite the compute-hungry nature of AI training workloads. Azure’s co-engineered stack, including custom protocols, collective libraries, and in-network computing, ensures the network is highly reliable and fully utilized by the applications. Features like NVIDIA SHARP accelerate collective operations and double effective bandwidth by performing math in the switch, making large-scale training and inference more efficient and reliable.

Azure’s advanced cooling systems use standalone heat exchanger units and facility cooling to minimize water usage while maintaining thermal stability for dense, high-performance clusters like GB300 NVL72. We also continue to develop and deploy new power distribution models capable of supporting the high energy density and dynamic load balancing required by the ND GB300 v6 VM class of GPU clusters.

Further, our reengineered software stacks for storage, orchestration, and scheduling are optimized to fully use computing, networking, storage, and datacenter infrastructure at supercomputing scale, delivering unprecedented levels of performance at high efficiency to our customers.

Looking ahead

Microsoft has invested in AI infrastructure for years, to allow for fast enablement and transition into the newest technology. It is also why Azure is uniquely positioned to deliver GB300 NVL72 infrastructure at production scale at a rapid pace, to meet the demands of frontier AI today.

As Azure continues to ramp up GB300 worldwide deployments, customers can expect to train and deploy new models in a fraction of the time compared to previous generations. The ND GB300 v6 VMs v6 are poised to become the new standard for AI infrastructure, and Azure is proud to lead the way, supporting customers to advance frontier AI development.

Stay tuned for more updates and performance benchmarks as Azure expands production deployment of NVIDIA GB300 NVL72 globally.

Read more from NVIDIA here.
The post Microsoft Azure delivers the first large scale cluster with NVIDIA GB300 NVL72 for OpenAI workloads appeared first on Microsoft Azure Blog.
Quelle: Azure

Unleash your creativity at scale: Azure AI Foundry’s multimodal revolution

Imagine a platform where every developer—whether you’re building for a startup or a global enterprise—can unlock the full spectrum of AI: text, images, audio, and video. This OpenAI DevDay, Azure AI Foundry is making that vision real. With today’s launch of OpenAI GPT-image-1-mini, GPT-realtime-mini, and GPT-audio-mini, plus major safety upgrades to GPT-5, you now have the ultimate toolkit to create, experiment, and scale multimodal solutions—faster and more affordably than ever before. We are excited to share that the models announced today by OpenAI will be rolling out now in Azure AI Foundry, with most customers being able to get started on October 7, 2025.

Try Azure AI Foundry today

Today’s announcement joins major innovations we announced last week with the launch of the Microsoft Agent Framework (now in preview), multi-agent workflows in Foundry Agent Service in private preview, unified observability, Voice Live API general availability, and the new Responsible AI capabilities. Microsoft Agent Framework (GitHub) is a commercial-grade, open-source SDK, and runtime designed to simplify the orchestration of multi-agent systems. It unifies the business-ready foundations of Semantic Kernel with the multi-agent capabilities of AutoGen, giving developers the tools to build intelligent, scalable agentic solutions with speed and confidence.

By expanding Azure AI Foundry with the latest OpenAI models and advancing our agentic AI framework, we empower customers with unparalleled choice, flexibility, and business capabilities, enabling developers to build intelligent agent systems that address complex business needs and drive innovation at scale.

Meet the new models: Built for developers, ready for anything

GPT-image-1-mini: Compact power for visual creativity

GPT-image-1-mini is purpose-built for organizations and developers who need rapid, resource-efficient image generation at scale. Its compact architecture enables high-quality text-to-image and image-to-image creation while consuming fewer computational resources, allowing teams to deploy multimodal AI even in constrained settings. Its robust architecture built on Image-1 model optimizes consistency and ease of adoption for organizations already leveraging multimodal AI in Azure AI Foundry.

What makes it special?

Flexible image generation: Deploy high-quality text-to-image and image-to-image features without breaking your budget.

Lightning-fast inference: Generate images in real time, seamlessly integrated with existing Azure AI Foundry workflows.

Use cases:

Generating educational materials for classrooms and online learning.

Designing storybooks and visual narratives.

Producing game assets for rapid prototyping and development.

Accelerating UI design workflows for apps and websites.

Table 1: GPT-image-1-mini pricing and deployment in Azure AI Foundry (per 1m tokens)*

GPT-realtime-mini and GPT-audio-mini: Efficient and affordable voice solution

The two new mini models are designed for organizations and developers who need fast, cost-effective multimodal AI without sacrificing quality. These models are lightweight and highly optimized, delivering real-time voice interaction and audio generation with minimal resource requirements. Their streamlined architecture enables rapid inference and low latency, making them ideal for scenarios where speed and responsiveness are critical—such as voice-based chatbots, real-time translation, and dynamic audio content creation. By consuming fewer computational resources, these models help businesses and developer teams reduce operational costs while scaling multimodal capabilities across a wide range of applications.

What makes them special?

Real-time responsiveness: Power chatbots, assistants, and translation tools with near-zero latency.

Resource-light: Run advanced voice and audio models on minimal infrastructure.

Affordable scaling: Lower your operational costs while expanding multimodal capabilities.

Use cases:

Voice-based chatbots for customer service and support.

Real-time translation for global communication.

Dynamic audio content creation for media and entertainment.

Interactive voice assistants for enterprise and consumer applications.

GPT‑realtime‑mini in Azure AI Foundry enables our customer to build voice solutions with lower latency, better instruction adherence, and cost efficiency—capabilities our customers value, driving shorter handle times, smoother dialogues, and faster time‑to‑value.
Andy O’Dower, VP of Product, Twilio

Table 2: GPT-realtime-mini and GPT-audio-mini pricing and deployment in Azure AI Foundry (per 1m tokens)*

GPT-5-chat-latest: Raising the bar for safety and wellbeing

The latest GPT-5-chat-latest update in Azure AI Foundry introduces a more robust set of safety guardrails, designed to better protect users during sensitive conversations. With enhanced detection and response capabilities, GPT-5-chat-latest is now equipped to more effectively recognize and manage dialogue that could lead to mental or emotional distress. These improvements reflect our ongoing commitment to responsible AI, ensuring that every interaction is not only intelligent and helpful, but also safe and supportive for users in challenging moments.

Table 3: GPT-5-chat-latest pricing and deployment in Azure AI Foundry (per 1m tokens)*

GPT-5-pro: The pinnacle of reasoning and analytics

GPT-5-pro represents the pinnacle of advanced reasoning and analytics within the Azure AI Foundry ecosystem, delivering research-grade intelligence. When deployed through Foundry, GPT-5-pro’s tournament-style architecture leverages multiple reasoning pathways to ensure maximum accuracy and reliability, making it ideal for complex analytics, code generation, and decision-making workflows. With Azure AI Foundry, organizations unlock the full potential of GPT-5-pro, driving smarter decisions and accelerating innovation across their most critical business processes, securely and reliably.

Table 4: GPT-5-pro pricing and deployment in Azure AI Foundry (per 1m tokens)*

The developer’s edge: Build, experiment, and ship—faster

With these new models, Azure AI Foundry isn’t just keeping up—it’s setting the pace. Developers can now move beyond text, tapping into image and audio generation, editing, and understanding. The result? Richer, smarter workflows that drive innovation in every industry—from education and gaming to enterprise automation.

Sneak peek: Sora 2—Next-level video and audio generation

And there’s more on the horizon. Sora 2 in Azure AI Foundry is coming soon, bringing advanced video and audio generation in a single API. Imagine physics-driven animation, synchronized dialogue, and cameo features—all available to developers through Azure AI Foundry. Stay tuned for the next wave of immersive, generative experiences.

Are you ready to create the next wave of immersive, multimodal experiences? Azure AI Foundry is your platform for every possibility.

*Pricing is accurate as of October 2025.
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Introducing Microsoft Agent Framework

Today we’re announcing new capabilities in Azure AI Foundry that make it easier for developers to build, observe, and govern multi-agent systems, while helping organizations close the trust gap in AI.

As agentic AI adoption accelerates—eight in ten enterprises now use some form of agent-based AI, according to PwC1—the complexity of managing these systems is increasing. Developers face fragmented tooling, and organizations struggle to ensure agents behave responsibly. Our latest updates to Azure AI Foundry address these challenges head-on. 

Introducing Microsoft Agent Framework (public preview) 

The Microsoft Agent Framework, now in public preview, is the open-source SDK and runtime that simplifies the orchestration of multi-agent systems. It converges AutoGen, a former Microsoft Research project, and the enterprise-ready foundations of Semantic Kernel into a unified, commercial-grade framework—bringing cutting-edge research to developers.

Get started with the Microsoft Agent Framework

With Microsoft Agent Framework, developers can: 

Experiment locally and then deploy to Azure AI Foundry with observability, durability, and compliance built in. 

Integrate any API via OpenAPI, collaborate across runtimes with Agent2Agent (A2A), and connect to tools dynamically using Model Context Protocol (MCP). 

Use the latest multi-agent patterns like Magentic One and orchestrate agents into Workflows. 

Reduce context-switching across tools and platforms. 

Build multi-agent systems connecting Azure AI Foundry, Microsoft 365 Copilot, and other agent platforms.

This framework is designed to help developers stay in flow. According to an industry study2, 50% of developers lose more than 10 hours per week due to inefficiencies like fragmented tools, highlighting the need for solutions that reduce complexity and improve the developer experience.

One organization using Microsoft Agent Framework to reduce friction is KPMG. KPMG’s transformation began with KPMG Clara, its cloud-based smart audit platform used on every KPMG audit worldwide.

KPMG Clara AI is tightly aligned with the next-generation, open-source Microsoft Agent Framework, built on the convergence of Semantic Kernel and AutoGen.

This means KPMG Clara AI can connect specialized agents to enterprise data and tools, while benefiting from built-in safeguards and an open, extensible developer ecosystem. The framework’s open-source connectors allow agents in KPMG Clara AI to interoperate not only with Azure AI Foundry, but also with external systems and language models, making it possible to scale multi-agent collaboration across a global, regulated enterprise.

Foundry Agent Service and Microsoft Agent Framework connect our agents to data and each other, and the governance and observability in Azure AI Foundry provide what KPMG firms need to be successful in a regulated industry.
— Sebastian Stöckle, Global Head of Audit Innovation and AI at KPMG International

We invite developers to join us in shaping the future of agentic AI by contributing code and feedback to Microsoft Agent Framework. 

Multi-agent workflows (private preview) 

Building on Microsoft Agent Framework, we’re extending these capabilities directly into the cloud with multi-agent workflows in Foundry Agent Service. This new feature enables developers to orchestrate sophisticated, multi-step business processes using a structured, stateful workflow layer. 

With multi-agent workflows, teams can: 

Coordinate multiple agents across long-running tasks with persistent state and context sharing. 

Automate complex enterprise scenarios such as customer onboarding, financial transaction processing, and supply chain automation. 

Leverage built-in error handling, retries, and recovery to improve reliability at scale. 

Workflows can be authored and debugged visually through the VS Code Extension or Azure AI Foundry, then deployed, tested, and managed in Foundry alongside existing solutions. 

Several customers are currently experimenting with this capability, and we look forward to expanding to more customers in the coming weeks.

Multi-agent observability across popular frameworks with OpenTelemetry contributions 

We’re also announcing enhancements to multi-agent observability, with contributions to OpenTelemetry that help standardize tracing and telemetry for agentic systems.

This gives teams deeper visibility into agent workflows, tool call invocations, and collaboration—critical for debugging, optimization, and compliance. We made the above enhancements to OpenTelemetry in collaboration with Outshift, Cisco’s incubation engine. 

With the above enhancements, Azure AI Foundry now provides unified observability for agents built with multiple frameworks, including Microsoft Agent Framework and others like LangChain, LangGraph, and OpenAI Agents SDK.

Voice Live API in Azure AI Foundry now generally available 

Mutli-agent workflows are increasingly initiated through voice inputs and culminate in voice outputs. We’re excited to announce the general availability of Voice Live API, which empowers developers and enterprises to build scalable, production-ready voice AI agents. Voice Live API is a unified, real-time speech-to-speech interface that integrates speech-to-text (STT), generative AI models, text-to-speech (TTS), avatar, and conversational enhancement features into a single, low-latency pipeline. 

Organizations such as Capgemini, healow, Astra Tech, and Agora are leveraging Voice Live API to build customer service agents, educational tutors, HR assistants, and multilingual agents. Voice Live API is transforming how developers build voice AI agents by providing an integrated, scalable, and efficient solution. 

Responsible AI capabilities public preview 

Building on advancements in agent observability and framework integration, it’s equally important to ensure that AI systems operate responsibly and securely—especially as they become more deeply embedded in critical enterprise workflows. 

According to McKinsey’s 2025 Global AI Trust Survey3, the number one barrier to AI adoption is lack of governance and risk-management tools. That’s why we’re putting the following responsible AI features in public preview in the coming weeks:

Task adherence: Help agents stay aligned with assigned tasks. 

Prompt shields with spotlighting: Protect against prompt injection and spotlight risky behavior. 

PII detection: Identify and manage sensitive data. 

These capabilities are built into Azure AI Foundry, helping organizations build with confidence and comply with internal and external standards. 

Customer momentum 

Azure AI Foundry solutions are helping over 70,000 organizations worldwide—from digital natives to enterprise companies—transform AI innovation into practical results. For example: 

Commerzbank: Commerzbank is piloting Microsoft Agent Framework to power avatar-driven customer support, enabling more natural, accessible, and compliant customer interactions.

The new Microsoft Agent Framework simplifies coding, reduces efforts and fully supports MCP for agentic solutions. We are really looking forward to the productive usage of container-based Azure AI Foundry agents, which significantly reduces workload in IT operations.
— Gerald Ertl, Managing Director/Head of Digital Banking Solutions, Commerzbank AG

Citrix: Citrix is exploring how they can use agentic AI within virtual desktop infrastructure (VDI) environments to improve enterprise productivity and efficiency.

Citrix has always embraced flexible ways of working as the leader in secure work. As we move into a world where agentic AI works side-by-side with us, we’re excited to enable that also within workspaces that our customers already use every day. Microsoft’s Agent Framework brings a modern, developer-first approach to building agents. With support for key APIs and languages, and native adoption of emerging protocols for tool calling and observability, it enables intuitive development of agents on Azure AI Foundry without compromising developer control. We are eager to leverage the framework to deliver on our vision – enterprise-scale, production-ready AI agents for our customers.
— George Tsolis, Distinguished Engineer, Citrix

TCS: Tata Consultancy Services is actively building a multi-agent practice on the Microsoft Agent Framework, with several initiatives underway that showcase their strategic investment and technical depth, including agentic solutions for finance, IT operations, and retail.

Adopting Microsoft Agent Framework is not just a technological advancement, but a bold step towards reimagining industry value chains. By harnessing Agentic AI and Frontier models, we enable our teams to build flexible, scalable, enterprise-grade solutions that transform workflows and deliver value across platforms. True leadership is about empowering innovation, embracing change, and fostering an environment where agility and collaboration drive excellence. 
— Girish Phadke, Head, Microsoft Azure Practice, TCS

Sitecore: Sitecore is developing a solution that enables marketers to interact seamlessly with the platform by automating tasks across the entire content supply chain—from creating and managing web experiences to handling digital assets—using intelligent agents.

By partnering with Microsoft to leverage its new Microsoft Agent Framework, Sitecore can bring together the best of both worlds: the flexibility to power fully non-deterministic agentic orchestrations and the reliability to run more deterministic, repeatable agents. At the same time, we benefit from Microsoft’s enterprise-grade observability and telemetry, ensuring that these orchestrations are not only powerful but also secure, measurable, and production-ready.
— Mo Cherif, VP of AI, Sitecore

Elastic: Elasticsearch supports a native connector to Microsoft Agent Framework, enabling developers to seamlessly integrate enterprise data into intelligent agents and workflows.

Elasticsearch is the context engineering platform and vector database of choice for organizations to store and search their most valuable operational and business data. With the new Microsoft Agent Framework connector, developers can now bring the most relevant organizational context directly into intelligent agents and multi-agent workflows. This makes it easier than ever to build production-ready AI solutions that combine the reasoning power of agents with the speed and scale of Elasticsearch.
— Steve Kearns, General Manager Search Solutions, Elastic

A trusted agent factory for developers 

Azure AI Foundry is more than a platform—it’s a trusted agent factory for developers and enterprises. Whether you’re a CIO looking to scale AI responsibly, a security architect focused on governance, or a developer building the next generation of intelligent agents, Azure AI Foundry provides the tools, frameworks, and trust you need. 

Microsoft stands out in the AI landscape with its commitment to open standards, interoperability, and responsible AI. The Microsoft Agent Framework, now in public preview, is a unified, enterprise-grade framework that integrates cutting-edge research and allows developers to seamlessly orchestrate multi-agent systems with built-in observability, durability, and compliance.

Unlike other solutions, our framework supports integration with any API via OpenAPI, collaboration across runtimes with Agent2Agent (A2A), and dynamic tool connections using MCP. This ensures developers can reduce context-switching and stay in flow, accelerating innovation.

The open-source nature of the framework invites developers to contribute and shape the future of agentic AI, making it a truly collaborative and forward-thinking platform. With Microsoft, organizations can trust that their AI systems will be powerful, efficient, responsible, and secure, addressing the top barriers to AI adoption identified in McKinsey’s 2025 Global AI Trust Survey.

Learn more about Azure AI Foundry

1 PwC’s AI Agent Survey.

2 AI adoption is rising, but friction persists.

3 Insights on responsible AI from the Global AI Trust Maturity Survey.
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Grok 4 is now available in Azure AI Foundry: Unlock frontier intelligence and business-ready capabilities

Today’s enterprises are entering a new phase of AI adoption—one where trust, flexibility, and production readiness aren’t optional; they’re foundational. Microsoft has collaborated closely with xAI to bring Grok 4, their most advanced model, to Azure AI Foundry—delivering powerful reasoning within a platform designed for business-ready safety and control.

Check out the Azure AI Foundry Grok 4 model card

Grok 4 undeniably has exceptional performance. With a 128K-token context window, native tool use, and integrated web search, it pushes the boundaries of what’s possible in contextual reasoning and dynamic response generation. But performance alone isn’t enough. AI at the frontier must also be accountable. Over the last month, xAI and Microsoft have worked closely to enhance responsible design. The team has evaluated from a responsible AI perspective, putting Grok 4 through a suite of safety tests and compliance checks. Azure AI Content Safety is on by default, adding another layer of protection for enterprise use. Please see the Foundry model card for more information about model safety.

In this blog, we’ll explore what makes Grok 4 stand out, how it compares to other frontier models, and how developers can access it via Azure AI Foundry.

Grok 4: Enhanced reasoning, expanded context, and real-time insights

Grok models were trained on xAI’s Colossus supercomputer, utilizing a massive compute infrastructure that xAI claims delivers a 10 times leap in training scale compared to Grok 3. Grok 4’s architecture marks a significant shift from its predecessors, emphasizing reinforcement learning (RL) and multi-agent systems. According to xAI, the model prioritizes reasoning over traditional pre-training, with a heavy focus on RL to refine its problem-solving capabilities.

Key architectural highlights include:

First-principles reasoning: “think mode”

One of Grok 4’s headline features is its first-principles reasoning ability. Essentially, the model tries to “think” like a scientist or detective, breaking problems down step by step. Instead of just blurting out an answer, Grok 4 can work through the logic internally and refine its response. It has strong proficiency in math (solving competition-level problems), science, and humanities questions. Early users have noted it excels at logic puzzles and nuanced reasoning better than some incumbent models, often finding correct answers where others get confused. Put simply, Grok 4 doesn’t just recall information—it actively reasons through problems. This focus on logical consistency makes it especially attractive if your use case requires step-by-step answers (think of research analysis, tutoring, or complex troubleshooting scenarios).

Example prompt: Explain how you would generate electricity on Mars if you had no existing infrastructure. Start from first principles: what are the fundamental resources, constraints, and physical laws you would use?

Extended context window

Perhaps one of Grok 4’s most impressive technical feats is its handling of extremely large contexts. The model is built to process and remember massive amounts of text in one go. In practical terms, this means Grok 4 can ingest extensive documents, lengthy research papers, or even a large codebase, and then reason about them without needing to truncate or forget earlier parts. For use cases like:

Document analysis: You could feed in hundreds of pages of a document and ask Grok to summarize, find inconsistencies, or answer specific questions. Grok 4 is far less likely to miss the details simply because it ran out of context window, compared to other models.

Research and academia: Load an entire academic journal issue or a very long historical text and have Grok analyze it or answer questions across the whole text. It could, for example, take in all of Shakespeare’s plays and answer a question that requires connecting info from multiple plays.

Code repositories: Developers could input an entire code repository or multiple files (up to millions of characters of code) and ask Grok 4 to find where a certain function is defined, or to detect bugs across the codebase. This is huge for understanding large legacy projects.

xAI has claimed that this is not just “memory” but “smart memory.” Grok can intelligently compress or prioritize information in very long inputs, remembering the crucial pieces more strongly. For the end user or developer, the takeaway is: Grok 4 can handle very large input texts in one shot. This reduces the need to chop up documents or code and manage context fragments manually. You can throw a ton of information at it and it can keep the whole thing “in mind” as it responds.

Example prompt: Read this Shakespeare play and find my password (password is buried in the long context text).

Data-aware responses and real-time insights

Another strength of Grok 4 is how it can integrate external data sources and trending information into its answers—effectively acting as a data analyst or real-time researcher when needed. It understands that sometimes the best answer needs to come from outside its training data, and it has mechanisms to retrieve and incorporate that external data. It turns the chatbot into more of an autonomous research assistant. You ask a question, it might go read a few things online, and come back with an answer that’s enriched by real data. Of course, caution is needed—live data can sometimes be incorrect, or the model might pick up on biased sources; one should verify critical outputs.

Example prompt: Check the latest news on global AI regulations (past 48 hours). 

Summarize the top 3 developments.

Highlight which regions or governments are driving the changes.

Explain what impact these updates could have on companies deploying foundation models.

Provide the sources you referenced.

Stacking up Grok 4: How it performs against top models

Grok 4 showcases impressive capabilities on high-complexity tasks. These benchmarks underscore Grok 4’s leading-edge capabilities in high-level reasoning, STEM disciplines, complex problem-solving, and industry-specific tasks. These benchmark numbers are calculated using our own internal Azure AI Foundry benchmarking service, which we use to compare models across a set of industry standard benchmarks.

Family of Grok models 

 In addition to Grok 4, Azure AI Foundry also has 3 additional Grok models already available.

Grok 4 Fast Reasoning is optimized for tasks requiring logical inference, problem-solving, and complex decision-making, making it ideal for analytical applications.

Grok 4 Fast Non-Reasoning focuses on speed and efficiency for straightforward tasks like summarization or classification, without deep logical processing.

Grok Code Fast 1 is tailored specifically for code generation and debugging, excelling in programming-related tasks across multiple languages.

While all three models prioritize speed, their core strengths differ: reasoning for logic-heavy tasks, non-reasoning for lightweight operations, and code for developer workflows. 

Pricing including Azure AI Content Safety: 

Model Deployment Type Price $/1M tokens Grok 4 Global Standard Input- $5.5 Output- $27.5 

Get started with Grok 4 in Azure AI Foundry

Lead with insight, build with trust. Grok 4 unlocks frontier‑level reasoning and real‑time intelligence, but it is not a deploy and forget model. Pair Azure’s guardrails with your own domain checks, monitor outputs against evolving standards, and iterate responsibly—while we continue to harden the model and disclose new safety scores. Please see the Azure AI Foundry Grok 4 model card for more information about model safety.

Head over to ai.azure.com, search for “Grok,” and start exploring what these powerful models can do.

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Explore the Grok 4 model in Azure AI Foundry.

Try it now

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Agent Factory: Designing the open agentic web stack

This blog is a wrap-up post in a blog series called Agent Factory which shares best practices, design patterns, and tools to help guide you through adopting and building agentic AI.

The rise of AI agents—autonomous software entities acting on behalf of users and organizations—marks a transformative moment for enterprise technology. But as we’ve explored throughout this blog series, building effective agents is about more than just code. It requires a repeatable blueprint, spanning use case design, developer tooling, observability, integrations, and governance. 

Throughout this series, we’ve walked through the journey of building enterprise-grade agents: from early use cases and design patterns to the tools and developer workflows needed to move from prototype to production, to the importance of observability, interoperability, and open standards, and finally the governance and security principles required to deploy agents responsibly. 

Now, as we conclude the series, we zoom out to the bigger picture: the agentic web stack. Much like HTTP and TCP/IP standardized the internet, this stack provides the common services and protocols needed to make multi-agent ecosystems secure, scalable, and interoperable across organizational boundaries. 

Learn more with Azure AI Foundry

Blueprint: 8 essential components and services

A robust agentic web stack is not one technology but a composition of services that together provide the foundation for open, secure, and enterprise-grade multi-agent systems. Here’s what it takes—and how Azure AI Foundry is making it real. 

1. Communication protocol service

Agents need a shared “language” to exchange messages, requests, and structured data. Without it, collaboration breaks down into isolated silos. Standards like Model Context Protocol (MCP) and Agent-to-Agent (A2A) provide this foundation, ensuring agents can negotiate, coordinate, and cooperate—regardless of who built them or where they’re hosted. In Azure AI Foundry, A2A support enables not only intra-organization workflows but also cross-boundary collaboration, where supply chain partners or business ecosystems can securely exchange actions through a common protocol.

2. Discovery registry service

Just as the web needed directories and search engines, agents need a way to be found and reused. The Catalog serves as the listing of assets—a curated collection of agents, tools, and applications that can be discovered and composed into new solutions. The Registry, by contrast, tracks the deployed instances of those assets—the live agentic app instances running across providers, with their endpoints, health, and status. Together, the Catalog and Registry bridge the gap between what’s available and what’s active, enabling developers to publish once, discover broadly, and reliably orchestrate workflows against running systems.

3. Identity and trust management service

Trust is the lifeblood of the agentic web. Every agent must carry a verifiable identity, enforced through standards like OIDC (OpenID Connect) and JWT (JSON Web Token), and tied into enterprise systems like Microsoft Entra ID. In Azure AI Foundry, identity is not an afterthought—it’s the control plane. This enables fine-grained role-based access, ensures that only authorized actors participate in workflows, and provides auditable accountability for every action an agent takes. Combined with encrypted channels, this identity-first model enforces a zero-trust security posture across the agentic stack.

4. Tool invocation and integration service

No agent can succeed in isolation; value comes when agents can connect with data, APIs, and enterprise systems. The Model Context Protocol (MCP) provides a vendor-neutral standard for exposing tools in a way that any compliant agent can invoke. In Azure AI Foundry, MCP integration is deeply embedded, so developers can register enterprise APIs once and instantly make them available to multiple agents—whether they’re built on Microsoft’s agent frameworks like Semantic Kernel and AutoGen, LangGraph, or third-party SDKs. This eliminates bespoke integrations and allows enterprises to compose workflows from best-in-class components.

5. Orchestration service

Single agents can handle discrete tasks, but the real breakthroughs come from multi-agent orchestration: teams of agents collaborating across multi-step, distributed processes. Azure AI Foundry delivers this through a unified framework that brings together Semantic Kernel and AutoGen—and extends it with multi-agent workflow orchestration inside Azure AI Foundry Agent Service. These workflows manage dependencies, allocate resources, and resolve conflicts, enabling enterprise-scale use cases such as financial transaction processing or IT incident response.

6. Telemetry and observability service

As we covered in Part 3, observability is non-negotiable for reliable agents. Azure AI Foundry extends OpenTelemetry with agent-aware instrumentation—tracing conversations, capturing performance data, and surfacing anomalies in real time. This makes agent behavior explainable and debuggable, while also serving governance needs: every decision and action is logged, auditable, and tied back to identity. For enterprises, this is the bedrock of trust, compliance, and continuous improvement.

7. Memory service

Agents without memory are limited to stateless interactions; agents with memory become adaptive, contextual, and human-like in their continuity. Azure AI Foundry supports both short-term session memory and long-term enterprise knowledge integration. Imagine a customer support agent that recalls prior interactions across channels, or a supply chain agent that tracks historical disruptions to improve future decisions. With memory, agents evolve from transactional helpers into strategic partners that learn and adapt over time.

8. Evaluation and governance service

Finally, no stack is complete without governance. This includes continuous evaluation, policy enforcement, ethical safeguards, and regulatory compliance. In Azure AI Foundry, governance hooks are built into orchestration, observability, and identity services—enabling enterprises to block unsafe actions, enforce approvals for sensitive workflows, and generate compliance-ready audit trails. This ensures organizations don’t just innovate fast, but innovate responsibly.

Strategic use cases and business value

The agentic web stack is not theoretical; it unlocks concrete enterprise value.

End-to-end business process automation: Imagine a procure-to-pay workflow where one agent negotiates with suppliers, another verifies compliance, a third triggers payment, and a fourth updates ERP records. With Azure AI Foundry’s orchestration and discovery registry, these agents collaborate seamlessly, cutting manual intervention and cycle times from weeks to hours.

Cross-organization supply chain synchronization: In global supply chains, delays often come from mismatched systems and data. With A2A and discovery services, a logistics agent from one company can securely interoperate with a customs agent from another—both governed by identity and observability. The result: faster border clearance, lower costs, and higher resilience. 

Knowledge worker augmentation: Agents built with Azure AI Foundry can take on repetitive but high-value tasks—scheduling, research, first-draft writing—while humans focus on creativity and judgment. The memory integration ensures continuity: a legal research agent remembers prior cases analyzed, while a marketing agent recalls brand guidelines across campaigns.

Complex IT operations: When outages occur, every second counts. Multi-agent workflows in Azure AI Foundry can detect anomalies, route alerts, execute diagnostics, and propose mitigations across distributed environments. Observability ensures root causes are transparent, while governance enforces that corrective actions comply with policy.

Memory-driven customer journeys: A customer support agent that recalls a prior complaint, a personalization agent that adapts recommendations, a compliance agent that enforces rules—working together, these create adaptive, context-rich interactions. The outcome is not just efficiency but stronger relationships and trust.

Preparing for the agentic era

For organizations, the path forward is as much about strategy and culture as it is about technology: 

Start with open standards: Adopt MCP and A2A from the outset, even in pilots, to avoid future rework and ensure interoperability. 

Invest in foundations: Identity, observability, and memory are not optional; they are the pillars that differentiate ad hoc automations from enterprise-grade systems. 

Operationalize governance: Define policies now and embed them into workflows through Azure AI Foundry’s governance services, so oversight scales with adoption. 

Engage the ecosystem: Participate in open-source and standards communities, influence their direction, and ensure your organization’s voice is heard. 

Prepare your workforce: Train employees not just to use agents, but to collaborate with them, supervise them, and improve them over time. 

Leaders who act on these imperatives will not only adopt agentic AI but shape its trajectory in their industries.

Shaping the future together at Ignite 2025 

The Agent Factory series has laid out the foundations: design patterns, developer tools, observability practices, interoperability standards, and governance principles. The agentic web stack brings these threads together into a cohesive vision: an open, secure, and interoperable ecosystem where agents can scale across organizational boundaries. 

Azure AI Foundry is your platform to make this vision real—unifying frameworks, standards, and enterprise capabilities so organizations can accelerate value while staying in control. 

At Ignite 2025, we’ll showcase the next wave of innovations—from multi-agent orchestration to deeper integrations with enterprise apps, data, and security systems. Join us to see how Azure AI Foundry is not only enabling enterprises to adopt agentic AI but also shaping the agent-driven future of business. 

Did you miss these posts in the series?

The new era of agentic AI—common use cases and design patterns

Building your first AI agent with the tools to deliver real-world outcomes

Top 5 agent observability best practices for reliable AI

From prototype to production—developer tools and rapid agent development

Connecting agents, apps, and data with new open standards like MCP and A2A

Creating a blueprint for safe and secure AI agents

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Build AI agents that automate tasks and enhance user experiences.

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