As application architectures evolve, and as AI becomes a default part of the software stack, PostgreSQL continues to adapt. This adaptability is a key reason Microsoft has been investing deeply in PostgreSQL: 345 commits contributed to the latest PostgreSQL release, a team of PostgreSQL committers and contributors working directly on the upstream project, and a growing portfolio of managed services, developer tools, and community programs built around Postgres on Azure. Here’s what’s driving that investment, and what it means for the people building on Postgres today.

Figure 1: This infographic highlights the many ways Microsoft contributes to and supports the PostgreSQL ecosystem

Discover Azure HorizonDB

Why PostgreSQL, and why now

Across industries, PostgreSQL is increasingly the default choice for new workloads and modernization projects. That shift is driven by three clear trends.

PostgreSQL is trusted with real production systems

PostgreSQL earned its reputation by solving hard problems in production environments: transactional correctness, concurrency control, extensibility, and operational resilience. These characteristics weren’t designed for isolated benchmarks; they emerged through years of running mission critical systems under real pressure.

Microsoft runs PostgreSQL at global scale and sees these same patterns firsthand. Many upstream contributions, such as recent work in PostgreSQL 18 on asynchronous I/O, vacuum behavior, and query planning, are informed directly by production bottlenecks encountered at scale.

This feedback loop works both ways. Improvements made upstream benefit the entire PostgreSQL ecosystem, while lessons learned from large‑scale deployments continue to inform future development.

Databases are becoming part of the AI stack

Databases are no longer isolated storage layers. In modern systems, they increasingly sit inside feedback loops that involve reasoning, ranking, and decision‑making.

Developers building AI‑enabled applications are asking new questions:

How close can vector data live to transactional data?

How can similarity search respect SQL predicates?

How can inference, ranking, and structured data work together without excessive glue code?

PostgreSQL’s extensibility makes it a natural foundation for these patterns. That’s why Azure Database for PostgreSQL and Azure HorizonDB focus on integrating AI‑related capabilities, such as vector search and model invocation, directly into familiar PostgreSQL workflows.

Different workloads, different paths to scale

As applications scale, not every workload benefits from the same architectural approach.

Some teams want a fully open, single‑node PostgreSQL experience with minimal abstraction. Others need elastic scale, multi‑zone replication, and fast failover but don’t want to push complexity into the application layer.

This diversity is why Microsoft supports multiple PostgreSQL deployment models on Azure:

Azure Database for PostgreSQL for open‑source‑aligned workloads and lift‑and‑shift scenarios.

Azure HorizonDB for cloud‑native systems that require scale‑out compute, shared storage, and low‑latency global resilience.

These aren’t forks. They are different engineering responses to different workload realities.

Get started with Azure Database for PostgreSQL

Upstream collaboration and developer tooling

Microsoft’s investment in PostgreSQL goes beyond product announcements for Azure’s managed services to include shipped code from in-house contributors, upstream collaboration, and production reliability. As our learnings expand, we’ve used these insights to enrich the open-source Postgres engine for the broader community.

Upstream contributions that benefit everyone

Postgres committers and developers at Microsoft actively contribute to the PostgreSQL open source project, working alongside the global community on core improvements. Recent version updates include contributions across:

Asynchronous I/O foundations.

Performance improvements in vacuum and memory management.

Planner and execution enhancements for large datasets.

These changes land upstream first, ensuring that improvements are broadly available not tied to any single cloud or service. A transparent overview of our Postgres work is published annually.

Architectural motivations behind Azure HorizonDB

Azure HorizonDB was built to address a specific class of PostgreSQL workloads that are constrained by single node scaling but not well served by application level sharding. For example, high-throughput, low-latency systems that require horizontal scale without adding application complexity.

Key architectural goals shaped Azure HorizonDB:

Independent scaling of compute and storage.

Failover and recovery operations decoupled from data size.

Multi‑zone replication enabled by default.

The result is a PostgreSQL‑compatible service with a shared‑storage, scale‑out design supporting sub‑millisecond multi‑zone commits and growth to thousands of cores, without requiring application rewrites.

Azure HorizonDB extends PostgreSQL’s reach while maintaining compatibility expectations that developers rely on.

Improving the developer experience where work actually happens

PostgreSQL has long been a developer‑centric database. Tooling investments on Azure reflect that mindset.

With more than 500,000 installs, the Visual Studio Code extension for PostgreSQL brings provisioning, schema exploration, performance diagnostics, and migration workflows directly into the IDE developers already use. Integrated GitHub Copilot assistance helps with SQL authoring, tuning, and even complex migrations, such as Oracle to PostgreSQL, which is one of the most challenging real world scenarios teams face.

The extension helps to remove unnecessary friction while keeping PostgreSQL familiar.

Investing in the PostgreSQL ecosystem

PostgreSQL’s progress has always depended on its community. That’s why Microsoft’s investment extends beyond products and services.

Microsoft sponsors and helps organize PostgreSQL conferences and user groups worldwide including PGConf.dev, PGConf EU, PGConf India, and many others. POSETTE: An Event for Postgres is a free and virtual Postgres event organized by the Postgres team at Microsoft and in partnership with AMD. It covers a wide range of topics including internals, ecosystem tools, real world debugging stories, and production architectures. This year’s 5th annual event, hosted 16-19 of June, brings together contributors, users, and engineers from across the Postgres community to share what works in practice.

Explore the schedule for POSETTE 2026

Talking Postgres, a monthly podcast that our team produces, features conversations with people who work with Postgres, from longtime contributors to production engineers solving hard problems at scale.

And the Microsoft Blog for PostgreSQL provides regular deep dives on product updates, migration guidance, and real-world Postgres usage patterns on Azure.

Looking ahead

PostgreSQL is approaching its fourth decade and it’s still accelerating. What began as a research project at UC Berkeley, is now a widely used database for modern applications, from developer experiments to mission-critical production environments.

As the community celebrates this moment, Microsoft’s focus remains consistent:

Strengthening PostgreSQL core through upstream collaboration.

Extending PostgreSQL responsibly for AI‑driven and cloud‑native workloads.

Preserving developer trust through open standards and transparency.

These priorities shape ongoing investments in Azure Database for PostgreSQL, Azure HorizonDB, developer tooling, and community engagement. Updates across these areas are now shared regularly through the Microsoft for PostgreSQL LinkedIn page.

A clear takeaway

PostgreSQL’s success has always been rooted in engineering discipline and community trust. Sustaining that success requires meaningful, long‑term investment, not just in services, but in the project itself and the people behind it.

Microsoft’s commitment to PostgreSQL reflects that belief: contributing upstream, building thoughtfully, and supporting an ecosystem that continues to move the database forward.

Unlock AI‑Ready Performance with Azure Database for PostgreSQL
Build intelligent, high‑performance apps with a fully managed PostgreSQL service that scales effortlessly.

Try today!

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This year, the key theme from Cosmos Conf was clear: AI is not just another workload. It is fundamentally reshaping how applications—and data platforms—are built.

In the opening keynote, VP of Azure Cosmos DB Kirill Gavrylyuk described three key shifts driving this transformation, and we saw them play out across every customer story at the event.

Discover how Azure Cosmos DB powers AI app development

The three AI shifts reshaping application architecture with Azure Cosmos DB

AI is making flexible, semi-structured data foundational

AI applications don’t operate on rigid schemas. They operate on prompts, memory, and context, all of which are inherently semi-structured and evolving over time.

This fundamentally changes how databases must behave.

Data platforms are no longer just systems of record—they are becoming systems of reasoning, where flexibility is critical to how applications learn, adapt, and generate outcomes.

AI is dramatically accelerating the pace of development

AI, and especially coding agents, are changing how software is built.

Developers are:

Iterating faster

Shipping more frequently

Scaling from zero to massive usage instantly

As Kirill highlighted, developers can no longer be constrained by strict schemas. Flexibility isn’t just a convenience—it’s what enables teams to move at AI speed. Databases need to meet the demand with serverless form factor, instant and limitless scalability, advanced integrated caching, and provide agent-friendly interfaces.

Semantic search is becoming a first-class query operator

The third shift is just as important:

AI applications require:

Vector search

Full-text search

Hybrid search

Semantic ranking

These are no longer “add-ons.” They are core to how modern applications function.

Across Cosmos DB Conf, we saw a clear pattern: teams are building applications where retrieval, reasoning, and real-time context are tightly integrated.

OpenAI: Flexibility at planet scale

These shifts are most visible in what organizations like OpenAI are building.

Speaking at Cosmos Conf, Jon Lee of OpenAI addressed how they are operating at massive scale—processing trillions of transactions and petabytes of data—reinforcing that what matters most is not just scale, but the ability to evolve quickly.

Watch how OpenAI approaches database design at scale

As Jon shared, modern systems must be able to:

Scale instantly from zero to massive usage.

Support schema-less design for rapid onboarding.

Enable thousands of developers to iterate simultaneously.

“The most important thing… is being able to scale from zero to millions of QPS, being able to scale from zero bytes to petabytes,” explained Jon, adding that speed and flexibility go together.

We have thousands of developers that are actively building products… it’s really important to make it easy to onboard to databases really fast.

This is exactly the world Kirill described: AI systems demand flexible data models that evolve as fast as the applications themselves.

This highlights how Azure Cosmos DB supports dynamically evolving, large-scale AI workloads.

Vercel: The rise of serverless, AI-native applications

If OpenAI shows what’s possible at scale, Vercel shows how the shape of applications is changing.

As Guillermo Rauch, CEO of Vercel, explained, AI is dramatically expanding who can build software—from millions of developers to potentially billions of creators, many of whom are using agents to generate applications on demand. Kirill underscored this point in his keynote when he stated that more than half of Azure Cosmos DB customers are already using coding agents in their development workflows.

Watch how Vercel approaches building AI‑powered applications

According to Guillermo, this is driving a structural shift toward:

Serverless architectures

Ephemeral applications

Instant scaling from zero to viral

Data platforms must keep up. To support this pace, platforms need to provide:

Built-in best practices (data modeling, partitioning, and optimization).

Intelligent guidance (agent skills and automation).

Real-time feedback on performance and cost.

Speaking on why he turned to Azure Cosmos DB, Guillermo said, “I wanted a system that gave me an economical thinking where the developer writes a query and they understand its cost.”

Developers need immediate feedback on the cost of their decisions, making efficiency a built-in design principle, not an afterthought.

This reflects a broader shift toward AI-native apps built on globally distributed, serverless data platforms like Azure Cosmos DB.

Walmart: Reliability and performance at scale

While AI is transforming how applications are built, one thing hasn’t changed: Performance and reliability remain mission-critical.

As Kirill emphasized, AI does not remove the need for reliability, security, and performance.

In fact, it raises the bar. This was reinforced in sessions like Walmart’s, where Technical Fellow Sid Anand explained that large-scale applications must:

Deliver low-latency experiences globally.

Remain available through regional failures.

Maintain consistent performance at massive scale.

Watch how Walmart approaches global e‑commerce at scale

“We want people to be able to add to their cart and view cart no matter what is happening in a given cloud region…and we need all of these interactions to be low latency because any type of latency friction will cause a drop-off,” said Sid.

From gigabytes to petabytes, from hundreds to trillions of transactions, modern systems must operate seamlessly under unpredictable demand.

These requirements align with how Azure Cosmos DB is designed for global distribution and low latency at scale.

Cost efficiency becomes a core design principle

A final takeaway from Cosmos Conf: as systems grow more complex, cost becomes just as important as scale.

Across the keynote and sessions, we saw a clear shift:

Developers need cost visibility in real time.

Architects need to design for efficiency upfront.

Teams want to consolidate platforms and reduce complexity.

This is where innovations like Azure DocumentDB come into focus.

As highlighted in the keynote, Azure DocumentDB offers over 40% lower cost vs. alternatives, and enables high performance with simplified architecture. It also supports open-source, multi-cloud portability scenarios. The result is a broader choice for builders:

Azure Cosmos DB → for global scale, serverless, five-nines reliability.

Azure DocumentDB → for cost efficiency, flexibility, open ecosystem.

Design and architecture examples that developers can start building now

Beyond the keynote, there were a number of demo-driven sessions at Cosmos Conf across app architectures, repeatable patterns, and best practices for building and scaling AI-enabled solutions.

For example, Farah Abdou, a lead machine engineer at startup SmartServe, shared how her team rebuilt their architecture using Azure Cosmos DB as a unified “agent memory fabric.” By combining vector search for semantic caching, change feed for event-driven coordination, and optimistic concurrency for conflict prevention, they were able to reduce costs, enable sub-100ms agent handoffs, and eliminate state conflicts.

Another topic we get asked about a lot is how users protect and govern their AI applications. Pamela Fox, a Microsoft Principal Cloud Advocate, walked through how to build secure, multi-user AI systems using the Model Context Protocol (MCP). By authenticating users with Entra ID and storing per-user data in Azure Cosmos DB, she enabled role-based access with Microsoft Graph, and practical development workflows using tools like VS Code and GitHub Copilot.

From these hands-on patterns to large-scale production systems, the lesson was consistent: teams are designing for scale, efficiency, and real-world usage from day one.

Key takeaways 

AI applications require flexible, schema-agnostic data models. 

Serverless and instant scalability are becoming default expectations. 

Semantic and vector search are now core to application design. 

Cost visibility and efficiency must be designed upfront. 

Building for what’s next

We’re entering a new era of application development. Apps are becoming AI-native, globally distributed, and are continuously evolving.

And success will depend on how well organizations align to these shifts.

The most forward-thinking teams we heard from at Cosmos Conf are already doing this by:

Designing for flexibility.

Building for speed, not just scale.

Treating cost and performance as key concerns.

Leveraging AI not just in apps, but in how apps are built.

This isn’t just a technology shift.

It’s a shift in how we think about building software.

Explore Cosmos DB Conf on demand

If you missed Cosmos Conf 2026, you can explore all sessions on demand and hear directly from the teams building these systems in production today.

The patterns shared this year are more than best practices, they’re a blueprint for what comes next.

Start building AI apps with Azure Cosmos DB
Design scalable, AI-native applications with a globally distributed database built for speed, flexibility, and real-time insights.

Explore Azure Cosmos DB

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Explore Microsoft and Red Hat’s platform modernization

Red Hat Ecosystem Innovation Award for Platform Modernization

Microsoft was recognized as the Platform Modernization Partner of the Year for the 2026 Red Hat Ecosystem Innovation Award as well as the North American Hybrid Cloud Everywhere honorable mention. These awards highlight partners whose collaboration with Red Hat delivers measurable customer outcomes through open, enterprise-grade platforms.

As AI moves from pilot projects to production systems, the challenge shifts from building models to operating them with consistent identity, governance, and security through integration with Microsoft Azure services.

At the center of this recognition is Banco Bradesco, one of the largest financial institutions in Latin America. Operating at massive scale with strict regulatory and security requirements, Banco Bradesco has moved beyond AI experimentation to production by building on Azure Red Hat OpenShift.

Azure Red Hat OpenShift serves as the secure-focused, scalable foundation for Banco Bradesco’s enterprise AI platform, unifying governance across more than 200 AI initiatives through integration with Azure identity, security, and policy capabilities. This is production AI on a jointly supported, enterprise-ready platform, not a proof of concept.

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Beyond large-scale financial institutions like Banco Bradesco, Topicus demonstrates how this approach applies across regional lenders and regulated markets. Its Akkuro lending platform runs on Azure Red Hat OpenShift, providing a consistent, enterprise Kubernetes foundation for document-driven credit decisioning in regulated environments.

By deploying in Switzerland North, Topicus keeps financial data in-country to meet sovereignty requirements and maintains a repeatable deployment model across regions. Built on a fully managed service jointly operated by Microsoft and Red Hat, Akkuro allows lenders to scale document intelligence workflows and maintain compliance and operational control.

Customers are increasingly seeking a single platform to run applications and AI, with a consistent application environment integrated with Azure AI and governance services.

Platform advancements across modernization, security, and AI

Azure Red Hat OpenShift provides a consistent, enterprise-ready foundation for running applications and AI at scale. The latest advancements focus on four priority areas:

Modernization

Security

AI innovation

Global expansion

Customers don’t just need features—they need to trust the platform running their most critical workloads. That’s what Microsoft and Red Hat delivers through Azure Red Hat OpenShift: a jointly engineered, enterprise-ready foundation.
—Aaron Isom, Technical Cloud Strategist, Red Hat

Migrate and modernization with Red Hat OpenShift Virtualization

For many enterprises, the immediate priority is migrating off legacy virtualization platforms without disrupting existing workloads. Enterprises are evaluating options to move off legacy virtualization platforms while maintaining flexibility in how and when to modernize. OpenShift Virtualization on Azure Red Hat OpenShift allows virtual machines and containers to run side-by-side on a single managed platform.

This provides a practical path to migrate existing workloads without rearchitecting and transition those workloads to Kubernetes over time. Integrated RHEL entitlements and Azure Hybrid Benefit eligibility further simplify licensing during modernization.

Securing workloads on Azure Red Hat OpenShift

As sensitive applications and data move to the cloud, enterprises need to trust that their most sensitive workloads can run securely across regions while meeting strict regulatory and sovereignty requirements. Azure Red Hat OpenShift applies a Zero Trust approach with built-in identity and confidential computing capabilities to enable that trust.

Confidential Containers on Azure Red Hat OpenShift protect sensitive data in use through hardware‑backed isolation, enabling secure processing of regulated workloads without exposing plaintext data to the underlying infrastructure.

Managed Identities and Workload Identities on Azure Red Hat OpenShift is generally available, standardizing credential management across both platform operations and application workloads.

At the platform layer, Azure Red Hat OpenShift operators use scoped, user assigned managed identities aligned with Azure role-based access control (Azure RBAC). At the application layer, workload identity provides secure access to Azure services through OpenID Connect (OIDC) federation, eliminating the need for long-lived secrets embedded in code or configuration.

As environments scale, managing credentials manually introduces operational overhead and security risk. Adopting identity-based access reduces credential sprawl, improves security posture, and aligns with Zero Trust principles across distributed applications.

These capabilities reduce credential risk, strengthen security posture, and support compliance requirements in regulated industries.

AI innovation on Azure Red Hat OpenShift

Azure Red Hat OpenShift provides a consistent platform for running AI applications across hybrid and multi-cloud environments, with Azure delivering the AI, identity, and governance services needed to operationalize them.

Customers can run AI capabilities directly on Azure Red Hat OpenShift, using Red Hat OpenShift AI, or integrate with Azure AI services and Microsoft Foundry to accelerate development and scale.

Expanded NVIDIA GPU support enables large-scale inference and data-intensive workloads to run on a fully managed Red Hat OpenShift platform backed by Azure infrastructure.

Expanded regional availability

Where workloads run is as important as how they run. Data residency, sovereignty, and latency requirements often shape platform decisions, particularly in regulated industries.

Azure Red Hat OpenShift continues to expand globally, including recent availability in Mexico Central, New Zealand North, Malaysia West, and Indonesia Central and Austria East.

Modern applications and AI capabilities run closer to users and data, meeting local compliance requirements, and maintaining consistency across regions.

The bigger picture

Across virtualization, security, identity, AI infrastructure, and global expansion, these advancements show how enterprises are standardizing on a single platform for applications and AI at production scale. As AI becomes part of core business operations, consistency in governance, identity, and operational control is becoming a requirement for enterprise platforms.

For customers like Banco Bradesco, Azure Red Hat OpenShift powers production AI platforms that meet the demands of scale, security, and operational reliability.

We are bringing AI powered‑ banking to millions of Brazilians, so performance at scale is nonnegotiable. The developed solution gives us the speed and resilience to power AI-powered banking at scale. It is a reliable foundation.
—Rafael Romualdo Wandresen, Senior Bridge Manager, Banco Bradesco

Join Microsoft at Red Hat Summit 2026

See you at Red Hat Summit 2026. Stop by to connect with Microsoft and Red Hat and see how Azure Red Hat OpenShift supports VMware modernization and production AI workloads on a single platform, and how to get started on Azure.

Azure Red Hat OpenShift at Red Hat Summit 2026

Explore how customers modernize with Azure Red Hat OpenShift

Explore how customers adopt AI on Azure Red Hat OpenShift

Watch the Banco Bradesco customer story

See how Topicus has adopted Microsoft Foundry on Azure Red Hat OpenShift

Announcing the winners of the 2026 Red Hat Ecosystem Innovation Awards

Learn more about Azure Red Hat OpenShift

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AI is reshaping how enterprises operate, make decisions, and innovate at scaleFrontier innovation for ERP systemsYour agentic intelligencePutting enterprise AI into productionAdvancing a new era of AI collaborationPowering AI with a unified data foundationMicrosoft and SAP expand partnership to deliver trusted sovereign cloud solutionsExpanding platform availability and ecosystem innovationCloud Acceleration Factory expansion: Driving AI innovation for SAPExpanding the Global RISE with SAP Acceleration Program on Microsoft AzureCustomer innovation in actionA global partner ecosystem driving scalePowering the future of SAP with Microsoft CloudDiscover what SAP and Microsoft Cloud have to offer

AI is reshaping how enterprises operate, make decisions, and innovate at scale

Together, Microsoft and SAP are helping enterprises transform operations, decision-making, and innovation at scale on Azure.

At SAP Sapphire 2026, Microsoft and SAP continue to build on a deep, decades-long partnership—one that is increasingly centered on a shared vision for how enterprises innovate in the age of AI. We’re excited to unveil how Microsoft’s Frontier Transformation helps customers realize SAP’s autonomous enterprise journey.

See how SAP on Azure drives business value for these customers

Frontier innovation for ERP systems

Microsoft Azure is the foundation of Frontier Transformation. To succeed, it must be built on a global, trusted, AI-first commercial cloud. Modern AI at scale requires a different kind of platform—one designed for agents, intelligence platforms, and continuous learning with AI embedded where people already work—augmenting decisions and actions in real time. That is how AI moves from experimentation to everyday impact.

What differentiates these experiences is intelligence and context. Agents that understand enterprise data, business processes, and organizational semantics improving relevance, accuracy, and decision quality over time. We call this Microsoft IQ.

Your agentic intelligence

Microsoft IQ is a shared intelligence layer built to power enterprise AI. It brings together three dimensions of intelligence: how people work, how the business operates, and how knowledge is unlocked and activated. From collaboration and workflows, to business data and systems of record, to policies and institutional knowledge—these signals are connected through a common platform, enabling AI to operate with full context across the organization.

This creates a new model for the enterprise:

Employees are supported by AI that understands their work in context.

Business operations are powered by real-time, connected data.

Knowledge is continuously surfaced, reasoned over, and applied through intelligent agents.

The result is an enterprise that moves faster, adapts more quickly, and drives better decisions with AI.

This is where the joint innovation between Microsoft and SAP becomes uniquely powerful. By combining SAP’s deep business process expertise with Microsoft’s intelligence layer, customers can extend this Frontier model into core business operations. SAP’s enterprise applications and data—spanning across SAP Business AI Platform and Joule—connect smoothly with Microsoft Teams, Microsoft Fabric, Microsoft Copilot, and a new generation of AI agents.

Putting enterprise AI into production

A central theme at SAP Sapphire 2026 is making AI real—moving from experimentation to production-ready, business-driven outcomes.

Save the bAIkery AI experience

Microsoft’s AI Immersion Experience showcases this shift in action. Through interactive scenarios like “Save the bAIkery,” attendees step into a dynamic business environment where every decision matters. Powered by Azure OpenAI, SAP Joule, SAP Cloud ERP, Microsoft Copilot Studio, and Power BI. This experience demonstrates how insights are generated to drive business outcomes across SAP systems—bringing together generative AI, analytics, and business processes in a seamless flow.

What makes this experience compelling is not just the technology—it’s the shift it represents. AI is no longer a layer on top of enterprise systems. It is becoming embedded into the core of how businesses operate, enabling faster decisions, greater agility, and entirely new ways of working.

Interactive: Explore how Microsoft and SAP AI capabilities can work together to connect business context, productivity tools and enterprise workflows.

Together, this enables end-to-end AI transformation:

Business data flows into a unified data foundation.

Intelligence is applied through SAP Joule and Copilot and agent-driven experiences.

Actions are executed across systems through tightly integrated workflows, in a governed, secure, and observable way.

The result is not just better integration—but a fundamentally new way of operating. Creating intelligent, interconnected systems where data, AI, and business processes continuously learn, adapt, and improve. This is the path to becoming a Frontier enterprise—where AI delivers measurable impact across the business, not as isolated gains, but as a continuous engine of innovation.

Advancing a new era of AI collaboration

One of the most exciting areas of innovation between Microsoft and SAP is the continued evolution of AI innovation across systems.

Over the past year, integration between SAP Joule and Copilot has taken important steps forward, enabling users to access business data and take action across SAP and Microsoft 365 environments.

At Sapphire, that vision continues to evolve and we are excited to announce agent-to-agent (A2A) integration between Microsoft 365 Copilot and Joule—delivering connected AI experiences using agent‑to‑agent capabilities, enabling Joule to work seamlessly across the Microsoft 365 productivity suite. This announcement opens up a world in which AI systems don’t just assist users—they begin to coordinate with each other across workflows.

Business collaboration happens in Microsoft 365 (for example, Teams chats about supply chain, finance, sales, or external emails with customers and suppliers) A2A enables Joule and Copilot to execute agentic flows with the collective intelligence of Microsoft Work IQ and SAP Knowledge Graph to truly deliver contextually aware enterprise AI.

This emerging model allows SAP and Microsoft AI capabilities to work together more seamlessly, enabling scenarios where business tasks can be orchestrated end-to-end across applications. Internally, this direction focuses on enabling more secure, governed, and scalable workflows across SAP landscapes while using the broader Microsoft ecosystem of applications and partner solutions.

For example, customers can prepare for performance reviews by starting directly in Microsoft 365 Copilot within Word, leveraging SAP-delivered Joule skills for systems like SAP S/4HANA or SAP SuccessFactors, and seamlessly scheduling a one-on-one meeting with their manager—all within the same interface.

It’s a meaningful step toward a future where AI becomes an active participant in how work gets done.

Powering AI with a unified data foundation

AI is only as powerful as the data behind it—and for many organizations, that data is still fragmented across systems, limiting its full potential.

At Ignite 2025, Microsoft and SAP took a major step forward in addressing this challenge. With the announcement of SAP Business Data Cloud Connect for Microsoft Fabric, we committed to a simplified method of accessing semantically rich data products from SAP through bi-directional, zero-copy delta sharing with Microsoft Fabric. Coming in the latter half of 2026, delta sharing will enable enterprises to gain instant access to trusted, business-ready insights for advanced analytics—bringing together SAP and non-SAP data into a single, unified foundation for AI.

Through bi-directional, zero-copy sharing between the SAP Business Data Cloud solution and Microsoft Fabric, customers can realize a fundamentally different data experience: one where data is no longer siloed, insights are no longer delayed, and AI is no longer constrained—enabling organizations to move faster, act with confidence, and turn intelligence into impact across every part of the business.

To lay the foundation for this delta-sharing Microsoft and SAP already deployed SAP BDC in eight Azure Datacenters. We will also add Japan by the end of May and Germany in June. With three additional deployments planned by the end of 2026, that will bring a total of 13 Azure regions available to support SAP BDC for customer analytics.

Microsoft and SAP expand partnership to deliver trusted sovereign cloud solutions

Sovereignty has become a decisive factor for organizations operating in regulated industries and the public sector—where data control, compliance, and operational assurance are critical. SAP and Microsoft are expanding their partnership to help customers meet growing sovereign cloud requirements as they modernize SAP landscapes.

Building on sovereign offerings such as SAP NS2, Delos Cloud, and BLEU, SAP and Microsoft continue to deepen their collaboration to deliver trusted sovereign cloud solutions for customers worldwide. Together, SAP and Microsoft are expanding support for RISE with SAP on SAP Sovereign Cloud running on Azure, giving customers greater choice in how and where they run mission‑critical SAP workloads, without compromising data residency, security, or governance.

Learn more about this announcement

Customers benefit from Microsoft’s and SAP’s sovereign cloud and service capabilities, supporting strong data residency, security, and governance.

The offering is available for customers today in these regions, with continuous worldwide expansion:

Australia

New Zealand

Canada

India

Europe

The United Kingdom

Together, SAP and Microsoft are empowering customers to innovate while maintaining the highest standards of sovereignty and trust.

Expanding platform availability and ecosystem innovation

Microsoft and SAP continue to expand global availability and ecosystem integration:

SAP Business Technology Platform (BTP) is available on Azure, the leading hyperscaler for SAP BTP, with 12 Azure regions live, so customers can meet data residency, and compliance needs while improving performance and scaling innovation closer to their users.

Azure Marketplace provides a streamlined path to discover and procure SAP BTP, SAP LeanIX solutions, and SAP Business Suite, helping customers standardize purchasing, accelerate deployments, and simplify governance through consolidated billing and procurement workflows (available in the US Azure Marketplace).

Joint innovations are enabling deeper integration with Microsoft 365, Teams, and Azure AI—unlocking productivity gains and new business scenarios.

These advancements reinforce Azure as a leading cloud platform for SAP workloads—supporting both migration and innovation at scale.

Cloud Acceleration Factory expansion: Driving AI innovation for SAP

We are expanding Cloud Acceleration Factory to help SAP customers and partners move beyond migration and unlock immediate AI value. By enabling integration between Microsoft 365 Copilot and SAP Joule within RISE and GROW environments, organizations can seamlessly connect data, workflows, and productivity tools from day one, accelerating real business outcomes with AI.

Through Azure Accelerate, customers can quickly operationalize AI with the first three agent-based use cases, built and deployed using Copilot Studio or Foundry. These prebuilt agents automate key business processes and establish a foundation for scaling intelligent operations across the enterprise.

This expansion is further strengthened by Microsoft Sentinel for SAP, providing integrated security and monitoring across SAP landscapes. Together, these innovations enable customers and partners to securely adopt AI and immediately take advantage of SAP and Microsoft’s joint AI innovation, accelerating time to value and increasing measurable business impact on Azure.

Expanding the Global RISE with SAP Acceleration Program on Microsoft Azure

Microsoft and SAP are excited to announce the expansion of the global RISE with SAP Acceleration program on Microsoft Azure, a joint initiative between Microsoft and SAP designed to deliver technical expertise, support, and innovation for RISE with SAP on Microsoft Azure customers.

In 2026, we will more than double the number of customers allowed into the program, marking an important milestone in our mission to provide RISE with SAP on Azure customers extraordinary support and expertise throughout their experience. Thousands of enterprise customers are already transforming their businesses with RISE on Azure, including Nestle, Migros, and Samsung.

First publicly announced in January 2025, this program brings together the best technical teams from SAP and Microsoft to enable a more seamless, high-touch migration and onboarding experience for the customer with no additional cost for an accelerated path to business transformation and faster cloud innovation.

Customer innovation in action

From manufacturing to logistics to energy, organizations are building more intelligent, resilient enterprises on Microsoft Cloud—where insights are embedded into workflows and decisions are driven in real time.

For example, Riddell, leading designer and manufacturer of protective sports equipment and helmets, modernized its operations on Azure to gain deeper visibility across its business and accelerate decision-making. In the logistics sector, Maersk transformed its global SAP estate on Azure to improve scalability and operational efficiency, creating a stronger foundation for innovation across its supply chain. And in the energy industry, MAIRE is enhancing its security posture with Microsoft Sentinel—gaining greater visibility and protection across its SAP and enterprise environments.

At SAP Sapphire 2026, you will also hear directly from Cargill, showcasing how it has modernized its SAP environment on Azure while preparing for an AI-powered future—bringing together SAP data, Copilot, and a secure, governed cloud platform to enable new business scenarios.

Together, with Microsoft and SAP, customers are moving beyond transformation to continuous, AI-powered innovation, using data and AI intelligence with embedded security as core drivers of growth and competitive advantage.

A global partner ecosystem driving scale

Partners play a critical role in helping customers navigate their SAP journey—from migration to modernization to AI transformation. Together, we are enabling industry-specific solutions, accelerating deployment timelines, and ensuring customers can realize value faster.

This ecosystem approach allows organizations to not only adopt new technologies, but also to operationalize them effectively—turning innovation into tangible business impact.

Supported by Microsoft’s cloud, data and AI platforms, EY teams built the EY.ai Agentic Acceleration Engine, which allowed them to analyze SAP business processes, identify over 175 high‑value agentic use cases, and rapidly translate them into interactive prototypes and solution designs that produce tangible impact, including agent teams supporting SAP‑based financial close activities, and intelligent supply chain and inventory management platforms where AI agents transact directly across SAP Finance, Logistics, Inventory and Sales modules. Together, EY teams and Microsoft are demonstrating how agentic AI can extend SAP from a system of record into a system of autonomous action—delivering measurable operational value today while creating a scalable blueprint for future enterprise transformation.
Unlock SAP value with EY, Microsoft and agentic AI

Modernizing large SAP environments often involves a difficult trade-off between speed, risk, and business continuity. For Microsoft, maintaining uninterrupted operations while transitioning to SAP S/4HANA was essential. Together with SNP, the company used a selective data migration approach to complete the transformation over a single weekend.
Massive scale with zero disruption: How Microsoft modernized to S/4HANA in record time with SNP

Powering the future of SAP with Microsoft Cloud

As enterprises look ahead, the opportunity is no longer just to transform SAP systems—it is to reimagine how business runs end-to-end.

Microsoft Cloud is uniquely positioned to enable this next phase. By combining a globally trusted cloud platform with a unified data foundation, advanced AI capabilities, and a seamless productivity layer, Microsoft provides customers with the full stack needed to move from ERP-centric operations to intelligent, AI-powered enterprises.

Our partnership with SAP is foundational to this vision. Together, we are driving innovation across cloud, data, and AI—creating a platform where insights, decisions, and actions are continuously connected.

This is what sets Microsoft apart in the SAP ecosystem. It’s not just about where customers run their SAP workloads—it’s about how they unlock new value across their entire business, using data and AI to drive outcomes, accelerate innovation, and stay competitive in a rapidly evolving world.

Together with SAP, we are shaping a future where enterprise systems are no longer static—but adaptive, intelligent, and built for continuous innovation.

Discover what SAP and Microsoft Cloud have to offer

Visit us at SAP Sapphire 2026 this week at booth #302 in Orlando, Florida and at #9.203 in Hall 9 in Madrid, Spain. Register for the Microsoft sessions.

Read our product blog for additional details on the announcements.

Read more about how customers are unlocking AI innovation and business transformation with SAP and Microsoft Cloud.

SAP on the Microsoft Cloud
Discover why Microsoft Cloud is the leading cloud platform for SAP workloads.

Learn more

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These innovations are powered by Microsoft Azure—the platform underpinning both Microsoft 365 Copilot and Microsoft Foundry. Azure enables organizations to build, deploy, and scale AI solutions with performance, security, and trust. Across industries, customers are turning to Azure to run critical workloads and advance their AI strategies, driving a new wave of innovation across Europe. 

Get started with Azure geography

Meeting Europe’s cloud and AI demand

To support customers running everything from core business systems to advanced analytics and AI-powered applications, we are significantly investing in datacenter regions across Europe.

This fiscal year, we’ve expanded into new regions and continue to build across key markets. We’re scaling capacity across both new and existing regions so customers can grow with confidence including:

Austria

Belgium

Two regions in Denmark

Greece

Finland

Microsoft’s global infrastructure spans more than 80 datacenter regions in 34 countries, giving customers greater choice for storing data at rest and meeting data residency, compliance, and performance requirements.

These investments deliver more than capacity; they provide trusted, sovereign solutions designed for transparency, operational control, and alignment with local regulations.

Comprehensive sovereign solutions without compromise

We’re expanding rapidly with a clear focus: helping customers scale as demand grows. We’re investing where customers are building and scaling critical workloads, and we’ll continue to grow our regional footprint with secure, resilient cloud and AI services—including sovereign solutions that help provide the control and deployment flexibility many organizations require.

These investments go beyond expanding capacity, they deliver trusted sovereign infrastructure that supports innovation with transparency, operational control, and alignment with local regulations.

Between Azure datacenter regions across the European Union, the European Union Data Boundary, and Microsoft Sovereign Cloud, customers gain control over where data is stored and processed — without giving up access to advanced cloud and AI capabilities.

Discover Microsoft Sovereign Cloud

Northern Europe: Scaling AI and cloud innovation in the Nordics

Across the Scandinavian countries in Northern Europe, demand from industry, the public sector, and enterprises is rising quickly, driven by advanced digital and AI workloads.

In Sweden we’re pairing that growing demand with a more sustainable approach to how Azure datacenters are designed and powered from:

Free-air cooling.

Rainwater harvesting.

Renewable diesel backup power.

A partnership with Vattenfall to use every day renewable-energy matching.

Organizations like Legora and inriver are using Azure and Azure OpenAI to innovate with AI-powered solutions and enhance digital experiences, while Sandvik is revolutionizing manufacturing with Microsoft AI solutions.

That same focus on proximity, resilience, and trust is shaping cloud adoption across Denmark. In the recently launched Denmark East datacenter region, organizations can run workloads closer to users while meeting data residency and protection needs, while strengthening their digital resilience.

As demand grows across the Nordics, we’re continuing to invest in cloud and AI infrastructure throughout the region, supporting the next wave of innovation from customers like Sanoma in Finland and the City of Stavanger in Norway.

Southern Europe: Accelerating digital transformation with local Azure regions

Southern Europe is seeing its own rapid growth in cloud adoption as organizations modernize IT estates, expand digital services, and bring AI workloads closer to users. In countries such as Spain and Italy, Azure infrastructure supports cloud and AI workloads with low latency while meeting national and European Union-level regulatory requirements.

The Spain Central datacenter region in Madrid helps organizations like LaLiga build and scale digital services. LaLiga delivers seamless fan experiences and AI-powered insights using Azure Arc, showcasing how organizations are using local infrastructure to power innovation at scale.

At the same time, companies such as Telefónica are advancing AI and machine learning capabilities on Azure, while Amadeus is using Azure Databricks to enhance data-driven decision-making, and Factorial is running its platform on Azure Kubernetes Service to scale efficiently and support rapid growth.

Similarly, the Italy North datacenter region in Milan expands access to trusted cloud and AI infrastructure, helping organizations meet in-country data requirements while modernizing critical systems and accelerating innovation.

Microsoft is working with telecom infrastructure operator FiberCop to bring cloud and AI capabilities closer to organizations across Italy by integrating Microsoft technologies with FiberCop’s nationwide network and edge infrastructure. This helps deliver ultra low-latency performance for scenarios such as industrial automation, healthcare systems, and smart city solutions while expanding deployment options for customers building secure cloud and AI services in Italy.

Further south, in Greece, Microsoft is expanding access to trusted cloud and AI infrastructure—supporting both public sector transformation and enterprise innovation. Azure enables organizations to deploy locally, meet regulatory requirements, and accelerate their digital modernization.

Across financial services, leading institutions including the National Bank of Greece are using Azure to strengthen resilience, enhance customer experiences, and drive data- and AI-powered operations. In energy and critical infrastructure, organizations such as HELLENiQ Energy are using Azure to modernize systems, optimize performance, and support the transition to more sustainable, intelligent operations. Together, these efforts reflect a broader momentum across Greece—where cloud and AI are becoming foundational to economic growth, public service delivery, and long-term competitiveness.

Western Europe: Investing in cloud capacity and AI skills

Across Western Europe, Microsoft continues to invest in infrastructure to support growing demand in markets such as the United Kingdom and Belgium. The United Kingdom remains a major cloud market in Europe, with accelerating demand across the public sector, financial services, healthcare, and enterprise workloads.

Microsoft is investing $30 billion in AI infrastructure and ongoing operations across the United Kingdom from 2025 through 2028, including $15 billion in capital expenditures to expand cloud and AI capacity and grow the datacenter footprint.

Customers such as Manchester City Council are using Microsoft 365 Copilot to enhance productivity and streamline citizen services, while Space Intelligence is delivering data-driven insights for environmental sustainability and ITF is modernizing its operations on Azure to improve efficiency and scalability.

Building on the momentum established in the United Kingdom, Microsoft is also advancing digital growth and innovation in Belgium. Our Belgium Central region continues to expand since the recent launch supporting local organizations while also contributing to digital skills and economic growth.

Microsoft’s commitment in Belgium extends beyond infrastructure: AI skills are essential to unlock Belgium’s digital transformation. That’s why Microsoft recently partnered with the Flemish government to introduce Microsoft Copilot to 10,000 civil servants one of the largest public Copilot projects in Europe.

Central Europe: Enabling compliance and advance analytics with Azure

Microsoft’s focus on expanding regional capabilities continues further into Central Europe. In Germany, Azure infrastructure enables local deployment while staying connected to the broader Microsoft Cloud for resilience and operational flexibility.

The Germany West Central region provides high availability and regional performance supporting organizations such as BMW Group, which is driving innovation across automotive with Azure, while TK Elevator is modernizing digital services and improving operational efficiency on Azure.

Basalt AG is using Microsoft Fabric to unlock data-driven insights and enhance analytics capabilities while maintaining strong governance with regional requirements. As demand for analytics and AI grows, regional cloud capacity helps organizations in Germany scale without sacrificing security or compliance.

Beyond these large industrial workloads, customers like ElringKlinger are modernizing SAP workloads on Azure while keeping sensitive manufacturing data governed and compliant with regional sovereignty requirements.

In Austria, Azure infrastructure enables organizations to store and process data locally, supporting regulatory compliance and innovation across industries.

Microsoft is training 200,000 people in Austria in digital skills as part of its broader commitment to the country’s digital future. Programs like Red Bull Basement highlight how these skills translate into real-world innovation—bringing together the next generation of builders to develop new ideas using Microsoft AI technologies, including Azure OpenAI.

Similar advances are now taking shape in Poland, where cloud-powered innovation is transforming education and healthcare. In Poland, organizations are accelerating digital transformation to address real-world challenges. Photon Education is reimagining classrooms, enabling teachers to deliver more engaging and inclusive learning experiences. Meanwhile, CancerCenter.AI is transforming cancer diagnostics and reducing diagnosis times with an Azure-powered platform, showcasing how innovation in Poland is shaping a more connected future.

Building resilient multi‑region cloud architectures

Europe is deeply integrated into the global economy, with businesses operating across borders and serving customers worldwide. Microsoft’s expanding regional footprint enables customers to build multi‑region cloud architectures, deploying applications across more than one Azure region for greater flexibility and control. By deploying across regions, organizations can improve availability, reduce the impact of localized disruptions, and deliver more consistent performance across Europe, while aligning with data residency, regulatory, and operational requirements without being limited to a single region.

A multi‑region approach allows organizations to scale dynamically, improve availability for business‑critical workloads, and reduce the impact of localized disruptions. It also brings applications and data closer to users for better performance, while supporting compliance with data residency and European Union wide regulatory requirements across Europe. With guidance from the Microsoft Cloud Adoption Framework and Azure Well-Architected Framework, customers can design multi-region environments.

Scaling Azure to meet Europe’s growing AI demand

Demand for cloud and AI is accelerating globally and we’re seeing it in customer adoption and the scale of workloads moving to Azure. That’s why we continue to invest in regional capacity across Europe, grounded in real growth and a clear view of what’s ahead. As we expand both new and existing Azure regions, we aim to support customers in building scale, performance, and governance, with infrastructure designed to be available where and when they need it. Together, these investments reflect a long-term commitment to building the infrastructure needed to support Europe’s next wave of innovation.

Learn more

Develop a multi-region architecture for your applications: Modern Azure Resilience with Mark Russinovich.

Take a virtual tour of a Microsoft datacenter.

Discover a sovereign cloud without compromise.

Explore our regions around the globe

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Defense in depth as a systemSecure by design: Engineering security into the platformHardware and host-level trustVirtual machine-layer trustSecure by default: Protection enabled without frictionSecure defaults across networkingEncryption and data protection by defaultCompute protection defaultsSecure in operation: Continuous protection at runtimeMonitoring, detection, and signal correlationIdentity-centric control and least privilegeBringing defense in depth and SFI together Security as an ongoing platform commitment

This blog post is the third part of a blog series called Azure IaaS which will share best practices and guidance to help you build a trusted infrastructure platform—from performance, resiliency, and security to scalability and cost efficiency.

​Security for cloud infrastructure is no longer defined by a single control, product, or boundary. Modern threats target identity, software supply chains, control planes, networks, and data simultaneously. Addressing this reality requires two things to work together: a layered defense-in-depth architecture and security principles that are enforced consistently across the platform.

In Azure Infrastructure as a Service (IaaS), security is built around these two reinforcing ideas. First, Azure implements defense in depth, applying multiple, independent layers of protection across compute, networking, storage, and operations so that no single control stands alone. Second, those protections are guided by Microsoft’s  Secure Future Initiative (SFI) principles: secure by design, secure by default, and secure in operation. Together, they define how Azure IaaS is engineered, configured, and operated at scale.

Explore Azure IaaS solutions

Defense in depth as a system

Defense in depth is not a checklist of features—it is a system-level security architecture. Each layer is designed with the assumption that another layer may fail, and that compromise at one point should not lead to platform-wide impact.

In Azure IaaS, defense in depth spans the full infrastructure stack:

Hardware and host integrity

Virtualized compute isolation

Network segmentation and traffic control

Data protection for storage

Continuous monitoring and response

These layers are intentionally independent. Hardware root-of-trust mechanisms validate host integrity before workloads ever start. Virtual machines (VM) run with strong isolation boundaries enforced by the hypervisor. Network controls limit lateral movement and restrict exposure. Storage services encrypt and protect data even if credentials are compromised. And telemetry and monitoring systems operate continuously, detecting and responding to anomalous behavior across the platform.

This layered approach ensures that Azure IaaS security does not rely on perimeter assumptions or a single “control plane defense,” but instead applies multiple mutually reinforcing controls that work together.

Build a stronger cloud infrastructure with Azure IaaS

Secure by design: Engineering security into the platform

“Secure by design” means security is architected into the platform from the beginning, not added after deployment. In Azure IaaS, this starts at the lowest layers of the stack.

Hardware and host-level trust

Azure servers are built with hardware roots of trust, measured boot, and secure firmware validation. Technologies such as Trusted Platform Modules (TPMs) and secure boot validate that host firmware, boot loaders, and operating systems have not been tampered with before the system joins the Azure fleet. These mechanisms reduce exposure to firmware-level and boot-chain attacks that traditional software-only defenses cannot address.

Azure also offloads critical infrastructure functions—such as storage, networking, and management operations—into dedicated, hardened components like Azure Boost, reducing the attack surface of the host operating system and improving isolation between customer workloads and platform services.

Virtual machine-layer trust

At the virtual machine layer, Azure enforces strong virtualization boundaries using a hardened hypervisor. Features like Trusted Launch for Azure VM combine secure boot, virtual TPMs, and integrity monitoring to protect VMs against low-level attacks such as bootkits and kernel rootkits.

For highly sensitive workloads,  Azure confidential computing extends defense in depth by using trusted execution environments (TEEs) backed by hardware-based memory encryption (such as AMD SEV‑SNP or Intel TDX). These technologies help ensure that data remains protected even while in use and inaccessible to the host or hypervisor.

Security here is not a bolt-on—it is a design property of how Azure compute infrastructure is built and operated.

Secure by default: Protection enabled without friction

Secure-by-default controls reduce risk by making the safest option the standard configuration, without requiring customers to assemble security from scratch.

Learn how to keep critical applications running with built-in resiliency at scale with Azure IaaS

Secure defaults across networking

In Azure IaaS, networking defaults are aligned with least-privilege and Zero Trust principles. Virtual networks are isolated by default. Inbound traffic to VM is blocked unless explicitly allowed. Network security groups (NSGs) enforce stateful filtering, while Azure Firewall provides centralized policy enforcement and traffic inspection when deployed.

Private connectivity options such as Azure Private Link and private endpoints allow services to be accessed without exposing them to the public internet. DDoS protection is automatically applied at the platform edge, helping protect workloads from volumetric attacks without additional configuration.

These defaults limit exposure by design, narrowing the attack surface before workload-specific rules are added.

Encryption and data protection by default

Azure IaaS storage services encrypt data at rest by default, using platform-managed keys, with options to use customer-managed keys via Azure Key Vault or Managed HSM. Disk encryption protects operating system and data disks for VM, and secure snapshots protect point-in-time copies of data.

Encryption in transit is enforced across Azure backbone networks, ensuring traffic between services within the platform is protected without requiring per-workload configuration.

Secure-by-default encryption ensures that data protections are always on, not optional.

Compute protection defaults

Signed and measured Azure host boot, secure host operating system (OS) hardening, host‑level monitoring and patching by Microsoft, and hypervisor-enforced isolation between tenants are all enabled by default and cannot be disabled by Azure tenants.

Trusted Launch is enabled by default for newly created Azure Gen2 VMs and VM scale sets, when using supported OS images, VM sizes, and deployment methods. Supported deployments methods include deployment via the Azure Portal, ARM templates, Bicep, Terraform, and Azure SDKs.

Secure in operation: Continuous protection at runtime

Security does not stop at deployment. The secure in operation principle focuses on maintaining protection continuously as threats evolve.

Monitoring, detection, and signal correlation

Azure integrates telemetry from compute, network, and storage layers into centralized monitoring systems such as Azure Monitor and Microsoft Defender for Cloud. These systems continuously analyze behavior to identify misconfigurations, detect threats, and surface actionable security recommendations.

For IaaS workloads, Defender for Cloud helps identify exposed management ports, missing disk encryption, and insecure network configurations, while also correlating threat signals across the environment.

Identity-centric control and least privilege

Operational security depends heavily on identity. Azure IaaS integrates with Microsoft Entra ID to enforce identity-based access controls, reduce standing privileges, and apply conditional access policies. Features like Just-In-Time (JIT) VM access limit administrative exposure by only opening management ports when needed and only for approved identities.

By minimizing persistent access and rotating privileges dynamically, Azure reduces the impact of credential compromise.

Bringing defense in depth and SFI together

Defense in depth provides the technical structure of Azure IaaS security. Secure by design, secure by default, and secure in operation provide the engineering and operational discipline that governs how those controls are built, deployed, and maintained.

Together, they ensure that Azure IaaS security is:

Layered: No single control is assumed to be sufficient.

Intrinsic: Security is part of the platform architecture, not an add-on.

Consistent: Defaults and policies reduce configuration drift.

Adaptive: Continuous monitoring and operational controls evolve with the threat landscape.

This combination allows Azure to protect IaaS workloads across compute, network, and storage while maintaining compatibility with diverse operating systems, workload types, and deployment models.

 Security as an ongoing platform commitment

Azure IaaS security is not defined by a static set of features. It is the result of ongoing engineering investment, guided by clear principles, and reinforced through layered technical controls.

Defense in depth ensures that failures are contained. Secure-by-design architecture reduces attack surfaces from the start. Secure-by-default configurations minimize exposure without adding friction. And secure-in-operation practices ensure the platform continues to adapt as threats evolve.

Together, these principles define how Azure IaaS delivers infrastructure security that is systematic, scalable, and aligned with modern threat realities.

To go deeper, explore the Azure IaaS Resource Center for tutorials, best practices, and guidance across compute, storage, and networking to help you design and operate resilient infrastructure with greater confidence.

Did you miss these posts in the Azure IaaS series?

Explore new resources for building a stronger, more efficient infrastructure

Keep critical applications running with built-in resiliency at scale

Create a resilient infrastructure with Azure
Visit the Azure IaaS Resource Center to start building a stronger, more efficient infrastructure today.

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Organizations operating national infrastructure, regulated workloads or mission-critical services are navigating a fundamental shift in how cloud infrastructure must be deployed and managed. As digital sovereignty postures evolve and regulatory requirements tighten across regions, infrastructure strategies are increasingly shaped by the need to maintain jurisdictional control over data, operations and dependencies. At the same time, AI and data-intensive applications are moving closer to where data is generated, requiring infrastructure that can scale to support larger deployment footprints while maintaining operational control, compliance and data residency requirements within sovereign environments.

Azure Local is the foundation for Microsoft’s Sovereign Private Cloud, allowing organizations to run cloud-consistent infrastructure on hardware they own and operate within their sovereign boundary. It supports deployments across connected, intermittently connected or fully disconnected environments. With Azure Local disconnected operations, customers retain the ability to apply policy enforcement, role-based access control, auditing and compliance configuration locally, allowing them control over how infrastructure is configured, secured and updated regardless of public cloud connectivity.

Scaling Sovereign Private CloudSovereign Private Cloud deployments must scale to support not only larger workloads, but also the operational requirements of national infrastructure and regulated industries. Azure Local allows organizations to grow deployments from hundreds up to thousands of servers within a single sovereign boundary, allowing infrastructure to expand alongside demand without requiring architectural redesign.

As deployment footprints grow, resiliency becomes essential to maintaining continuous operations for mission critical services. Expanded fault domains and infrastructure pools help prevent hardware failures from resulting in service outages, ensuring critical workloads remain operational across environments with varying levels of cloud connectivity.

At these larger scale points, organizations can run data-intensive AI inference and analytics workloads entirely within their own environment. With support for high-performance graphics processing unit (GPU) infrastructure, sensitive models and operational data remain within customer-controlled infrastructure, while access management, auditing and compliance controls are maintained within the sovereign deployment.

Built for challenging workloadsIncreased deployment scale unlocks new workload placement opportunities, from large sovereign private cloud deployments to distributed AI workloads, allowing organizations to run more data intensive and latency sensitive applications entirely within their sovereign boundary.

AT&T, one of the world’s largest telecommunications operators, is deploying Azure Local to run mission-critical infrastructure on hardware they own in their environment. The goal: full operational control while running at the scale the business demands.

“Azure Local provides the infrastructure foundation we need to run critical operations at scale, while ensuring control and governance across our environment. The consistency of the Azure operating model, delivered on our own infrastructure, is key as we continue to modernize while delivering reliable services to our customers.”

— Sherry McCaughan, Vice President – Mobility Core Services, AT&T

Kadaster, the Netherlands’ official land registry and mapping agency, is running Azure Local to keep sovereign control over some of the country’s most sensitive public data.

“As a government agency responsible for some of the Netherlands’ most sensitive data, we need infrastructure that gives us full control over where our data lives and how it’s governed. Azure Local has been a consistent foundation for that — and as our workloads grow in scale and complexity, the platform has grown with us.”

— Maarten van der Tol, General Manager, Kadaster

FiberCop, Italy’s most advanced and extensive digital network operator is deploying Azure Local across its edge locations to bring sovereign cloud and AI services to organizations throughout the country. Fabio Veronese, Chief Information & Technology Officer commented:

“FiberCop is better positioned than any other player on the Italian market to drive innovation and deliver cloud as well as AI services at national scale. Azure Local supports our mission to drive Italy’s digital future and brings Microsoft’s cloud capabilities to edge workloads across the country while keeping data sovereignty and compliance where they matter most.”

The infrastructure behind Sovereign Private CloudAzure Local is available today with validated compute and enterprise storage platforms from partners including DataON, Dell Technologies, Everpure, Hitachi Vantara, HPE, Lenovo and NetApp, allowing organizations to integrate existing Storage Area Networks (SAN) and preserve prior investments while allowing compute and storage resources to scale independently within their sovereign environment.

At the silicon level, Intel®  Xeon® 6 processors provide the compute foundation for the platform. Built for the density and performance demands of modern enterprise workloads, Xeon 6 also brings built-in AI acceleration with Intel® AMX, meaning organizations running inference or generative AI workloads within their sovereign environment do not need to introduce separate, specialized infrastructure to do so.

Together, Azure Local, validated compute and enterprise storage platforms, accelerated computing platforms and underlying silicon can provide a datacenter-scale stack that supports sovereign infrastructure deployments while helping ensure data, models and execution remain within customer-controlled environments.

Sovereign infrastructure built for your requirementsAzure Local was built to meet customers where their requirements are whether that means strict data residency, disconnected operations, regulated workloads or AI running close to where data is generated. As these requirements evolve across regulated industries and governments worldwide, Sovereign Private Cloud deployments can expand from a single node at the edge to large enterprise-scale datacenter environments, running on hardware organizations own and operate, with consistent lifecycle management through Azure.

Resources:

Learn more about Azure LocalExplore Microsoft’s Sovereign CloudRead the Tech Community blogVisit the Azure Local solution catalogDouglas Phillips leads global engineering efforts for Microsoft’s specialized, sovereign and private clouds. He is responsible for Microsoft’s global strategy, products and operations that bring Microsoft’s industry-leading solutions, including Azure, our adaptive cloud portfolio and Microsoft 365 collaboration suite, to customers with additional sovereignty, security, edge and compliance requirements.
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Azure Integrated HSM is a tamper‑resistant, Microsoft‑built hardware security module integrated into every new Azure server, extending existing key management services by bringing hardware enforced protection directly to where workloads execute. Rather than relying solely on centralized services, this approach makes hardware-backed security a native property of the compute platform itself.

Azure Integrated HSM is engineered to meet FIPS 140‑3 Level 3, the gold standard for hardware security modules used by governments and regulated industries worldwide. Level 3 requires strong tamper resistance, hardware-enforced isolation, and protection against physical and logical key extraction. By building these assurances directly into the platform, Azure makes the highest levels of compliance a default property of the cloud, rather than a specialized configuration or premium add‑on.

Learn more about Azure Security

Reinforcing transparency through trust with open-sourced designs

Our approach to hardware security is grounded in a simple belief: transparency builds trust, and industry collaboration strengthens security. Openness strengthens trust by allowing customers, partners, and regulators to validate design choices and security boundaries.

This week, at the Open Compute Project (OCP) EMEA Summit, we announced plans to open the Azure Integrated HSM hardware to the broader open hardware ecosystem. Through OCP, we plan to release the Azure Integrated HSM firmware, driver, and software stack as open source, and launch an OCP workgroup to guide ongoing development—spanning architectural design, protocol specifications, firmware, and hardware. The Azure Integrated HSM firmware is now available through the Azure Integrated HSM GitHub repository, alongside independent validation artifacts such as the OCP SAFE audit report.

This openness is particularly important for regulated industries and sovereign cloud scenarios, where independent validation of security controls is required. By making key components available for external review, Azure Integrated HSM enables customers, partners, and regulators to assess implementation details directly rather than relying solely on vendor assertions.

This approach strengthens confidence in the platform and helps establish a more transparent and verifiable foundation for cloud security, while reducing reliance on proprietary vendor specific protocols. At a time when cryptographic trust underpins everything from AI inference to national digital infrastructure, open sourcing the HSM is a practical step toward interoperability, auditability, and customer confidence.

A tiered approach to key management

This design complements services like Azure Key Vault and Azure Managed HSM, which continue to provide centralized key lifecycle management, governance, and policy enforcement. Azure Integrated HSM adds a new layer; one that brings cryptographic protection down to the individual server, so that keys are protected not just when they are stored but while they are actively being used by workloads. The Azure Integrated HSM also supports industry standards such as TDISP, enabling secure binding between the HSM and confidential computing environments.

In the coming weeks, Azure Integrated HSM will be available in Azure V7 virtual machines to all customers globally.

Setting a new standard for server-local key protection at scale

With Azure Integrated HSM, encryption keys are generated, stored, and used entirely within hardened hardware. Keys are designed to never appear in host memory, guest memory, or software processes even during active cryptographic operations. By keeping keys within the hardware boundary at all times, Azure Integrated HSM eliminates entire classes of key and credential exfiltration attacks that target memory or software layers.

The result is true customer control enforced by silicon, not policy. Security is no longer dependent on operational discipline or complex isolation assumptions; it is enforced by hardware.

Traditional cloud security models rely on centralized HSM services accessed over the network. While effective, these models introduce shared blast radius, scalability challenges, and performance constraints as workloads grow.

By anchoring cryptographic protection directly to the server, security scales naturally with compute. There are no shared bottlenecks, no added network hops, and no need to trade performance for protection. As Azure scales, security scales with it.

With hardware roots of trust, measured boot, and attestation, Azure Integrated HSM makes trust verifiable rather than contractual. Customers and regulators can cryptographically validate that approved hardware, firmware, and configurations are in place. This can be further verified by the open-source firmware. Trust is no longer something you accept; it is something you can prove.

Together, these capabilities establish a new baseline for cloud security, one in which hardware-enforced, verifiable trust is the default for modern workloads, from core infrastructure services to the next generation of AI. When combined with confidential computing, open silicon roots of trust, Azure Boost, and datacenter-level secure control modules, the Azure Integrated HSM helps establish a vertically integrated chain of trust, from silicon to software.

We invite customers, partners, and the broader open-source community to contribute to the architecture and help shape future standards. Together, we can build secure, sovereign, and open cloud infrastructure for the challenges ahead.

For additional information, read the announcement blog and learn more about Azure Security.

Azure Security
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The post Enforcing trust and transparency: Open-sourcing the Azure Integrated HSM appeared first on Microsoft Azure Blog.
Quelle: Azure

Der Beitrag Enforcing trust and transparency: Open-sourcing the Azure Integrated HSM erschien zuerst auf Cloud Computing Köln.

Built on a proven foundation extending into AIOne platform to scale APIs and AIGovernance by design for AI at scaleTurning AI innovation into business impactExpanding the platform for what’s next

As AI moves into production, how systems interact is fundamentally changing. Organizations must now manage not just APIs, but how AI systems operate across the enterprise.

We’re proud to share that Microsoft has been named Leader in the IDC MarketScape: Worldwide API Management 2026 Vendor Assessment (#US52034025, March 2026). We believe this recognition reflects our focus on helping organizations securely scale APIs and AI together with the control, visibility, and reliability required for production.

Read why Microsoft was named a Leader in the IDC MarketScape: Worldwide API Management 2026 Vendor Assessment

Built on a proven foundation extending into AI

For more than a decade, Azure API Management has served as a trusted control plane for API governance, security, and observability at a global scale, supporting over 38,000 customers, nearly 3 million APIs, and more than 3 trillion API requests each month. That foundation is now extending to a new class of workloads.

As organizations bring AI into production, they must govern a growing mix of API traffic and AI-driven interactions, each with new governance needs, cost dynamics, and reliability requirements. What was once about connecting systems and exposing APIs is now an operational challenge at scale. Organizations must continuously manage how models, tools, and agents behave in production controlling cost, enforcing policies, and ensuring reliability across multi-provider AI traffic.

AI gateway capabilities in API Management build on this foundation, extending API Management’s proven API governance to AI workloads. Today, more than 2,000 enterprise customers are already using these capabilities to safely operationalize AI.

One platform to scale APIs and AI

To meet this shift, organizations need a simpler model, one platform that brings consistency across both APIs and AI.

Azure API Management provides a single, Azure-native platform to govern everything from traditional APIs to AI models, tools, and agents, built on a foundation proven at enterprise scale. This allows organizations to move faster with AI without losing control, visibility, or consistency as they scale. By standardizing how systems connect and interact, teams can reduce fragmentation, simplify operations, and create a trusted foundation for innovation across the business.

Learn more about Azure API Management

This approach is already delivering results on a global scale. Heineken uses Azure API Management as the backbone of its global API platform, enabling teams to build and scale digital experiences faster while maintaining a consistent, centrally governed foundation. In just five months, Heineken built and deployed a worldwide API platform now handling 50 million API calls per month, achieving 100% uptime since go-live, and reducing cost per API call by up to 75% through standardized governance and security at scale.

Governance by design for AI at scale

As AI adoption grows, the challenge shifts from building models to operating them reliably in production. Organizations need a consistent way to control how AI systems operate in production.

Azure API Management provides that governance layer, allowing organizations to define how AI systems access models, tools, and agents, while enforcing security policies, monitoring usage, and maintaining control over cost and behavior across environments. This ensures every interaction is secure, observable, and aligned with business and compliance requirements.

This approach is already proving essential in real-world deployments. Banco Bradesco uses Azure API Management to securely manage AI services and APIs across channels, applying centralized governance and end-to-end visibility. By standardizing how APIs and AI services are exposed and consumed, the bank ensures consistent security policies, improves monitoring across interactions, and supports high-scale digital banking experiences with strong data protection.

With Microsoft Azure API Management, we securely manage AI services and APIs across all channels. It’s the backbone of our architecture scaling with demand while maintaining strict governance and data protection.
 —Phelipi Dal’Olio, Bridge Manager, Banco Bradesco

Turning AI innovation into business impact

With governance in place, organizations can move beyond experimentation and focus on delivering real business value with AI.

Telefónica Brasil is using Azure OpenAI to enhance customer interactions across digital channels. This improves service experiences, accelerates response times, and enables more personalized engagement at scale.

At the same time, Access Group embedded AI directly into its product portfolio. Using Azure API Management as the foundation of its AI gateway, Access launched over 50 AI-powered products in a single year and scaled to 2.2 million users. The company also achieved ISO 42001 certification for responsible AI, demonstrating how governance can accelerate innovation.

Air India deployed a generative AI assistant at scale. It now handles up to 40,000 customer queries per day, has resolved over 13 million conversations, and operates with a 97% success rate. This allows the airline to scale customer support without increasing agent volume while saving millions annually.

Azure API Management supports this shift by providing a consistent way to expose, secure, and manage the APIs that power these AI-driven experiences, helping organizations move from isolated innovation to production-ready, enterprise-scale impact.

Expanding the platform for what’s next

As organizations adopt new interaction patterns across APIs and AI systems, the platform continues to evolve. Azure API Management is expanding to support emerging scenarios, including governed agent interactions, exposing APIs as reusable tools for AI systems, and enabling centralized discovery and policy enforcement across environments. This ensures organizations can adopt new capabilities without introducing fragmentation or losing control.

As organizations continue to invest in AI, the ability to govern how systems and AI interact at scale will become a defining capability. API management is evolving from connecting systems to enabling controlled, trusted interaction across the enterprise.

We’re honored to be named a Leader in the 2026 IDC MarketScape for Worldwide API Management Vendor Assessment, and we remain committed to helping organizations scale APIs and AI with confidence.

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The post Microsoft named a Leader in the IDC MarketScape: Worldwide API Management 2026 Vendor Assessment appeared first on Microsoft Azure Blog.
Quelle: Azure

Der Beitrag Microsoft named a Leader in the IDC MarketScape: Worldwide API Management 2026 Vendor Assessment erschien zuerst auf Cloud Computing Köln.

GPT-5.5 continues a clear progression in the GPT-5 series. GPT-5 brought unified reasoning and speed into a single system. GPT-5.4 brought stronger multi-step reasoning and early agentic capabilities for enterprise use. GPT-5.5 advances this arc with deeper long-context reasoning, more reliable agentic execution, improved computer-use accuracy, and greater token efficiency—designed for sustained, high-stakes professional workflows.

Powerful models alone aren’t enough to operationalize agentic AI at scale. Microsoft Foundry provides the platform layer that turns frontier models into usable, governable systems that enable enterprises to apply security policy and management at the platform level. Foundry is a unified, interoperable environment to build, optimize, and deploy AI applications and agents with confidence. Customers benefit from broad model choice, open and flexible agent frameworks, native integration with enterprise systems and productivity tools, and enterprise-grade security, compliance, and governance. When new models like GPT-5.5 become available, Foundry makes it easy to evaluate, productionize, and scale them without friction.

Explore models in Microsoft Foundry

What’s new in GPT-5.5

GPT-5.5 is built for professional scenarios where precision, reliability, and persistence matter. GPT-5.5 Pro, a premium variant, extends reasoning depth and task complexity for the most demanding enterprise workloads.

Improved agentic coding and computer-use: Executes multi-step engineering tasks end-to-end—holding context across large systems, diagnosing the root cause of ambiguous failures at the architectural level, and reasoning through what else in the codebase a fix will affect before making a move. It anticipates downstream testing and review requirements without needing to be told, and navigates software interfaces with improved precision and more reliable recovery when execution takes an unexpected turn.

Autonomous execution and research depth: Goes beyond code to handle the full span of professional work—producing polished deliverables like documents, spreadsheets, and presentations. For research-intensive workflows, GPT-5.5 operates as an active collaborator across the entire arc from question to output: refining drafts across multiple passes, stress-testing analytical reasoning, proposing approaches, and synthesizing across documents, data, and code to drive work forward rather than just answering it.

Complex reasoning and long-context analysis: Handles extensive documents, codebases, and multi-session histories without losing the thread.

Token efficiency built for scale: GPT-5.5 reaches higher-quality outputs with fewer tokens and fewer retries—lowering cost and latency for production deployments at scale.

GPT-5.5 is particularly well suited for domains where the cost of imprecision is high—such as software engineering, DevOps, legal, health sciences, and professional services. With GPT-5.5 in Microsoft Foundry, customers can pair OpenAI’s latest frontier model with enterprise-grade infrastructure to put agentic AI into production.

Microsoft Foundry: The operating system for GPT-5.5 agents at scale

Access to a frontier model is just the starting point. What we see from customers is that the hard part isn’t building an agent: it’s running thousands of them in production, with real isolation, identity, and governance. That’s where Foundry Agent Service comes in.

A revolution is unfolding in the market. Now, a developer can reliably reason through a business problem with a coding agent—human’s interact with a model doing heavy thinking, research, asking questions — and the output is a production agent: a declarative workflow suitable for a specific task, and connected to your business systems.

These declarative agents can be defined in YAML or written in a harness like Microsoft Agent Framework, GitHub Copilot SDK, or virtually any library. With hosted agents in Foundry Agent Service, LangGraph, Claude Agent SDK, and OpenAI Agents SDKs all work the same way. Engineers can run a single command to land agents in an isolated sandbox with a persistent filesystem, a distinct Microsoft Entra identity, and scale-to-zero pricing. Enterprise ready agents, at scale, powered by GPT-5.5.

Learn more about Foundry Agent Service and Microsoft Agent Framework.

Pricing

ModelInput ($/M tokens)Cached Input ($/M tokens)Output ($/M tokens)GPT-5.5$5.00$0.50$30.00GPT-5.5 Pro$30.00$3.00$180.00

Get started with Microsoft Foundry

Stop experimenting and start building your next production AI workloads with GPT-5.5 in Microsoft Foundry.
The post OpenAI’s GPT-5.5 in Microsoft Foundry: Frontier intelligence on an enterprise ready platform appeared first on Microsoft Azure Blog.
Quelle: Azure

Der Beitrag OpenAI’s GPT-5.5 in Microsoft Foundry: Frontier intelligence on an enterprise ready platform erschien zuerst auf Cloud Computing Köln.