Microsoft Azure Blog

At Microsoft, our vision is to build a Frontier Firm: one where people and technology work together, combining human expertise, context, and judgment with technology that can extend intelligence throughout everyday work. The potential is significant: helping people create, solve complex problems, and make progress on some of society’s most consequential challenges. But realizing that potential requires frontier infrastructure.

At this year’s OCP Global Summit, Microsoft announced Project Tessera, the evolution of the Azure Integrated Hardware Security Module (HSM), into a fully open-source initiative developed in collaboration with Marvell®, Oracle, and Open Compute Project (OCP). Project Tessera advances our broader commitment to open, industrywide standards for platform security.

From its inception, Azure Maia has been built around a single architectural philosophy: optimize the entire system for LLM inference so that every watt and every dollar delivers more intelligence. Now in its third generation, Maia 300 is the fullest expression of that philosophy. Maia 300 is built as a complete system, with software, silicon, physical rack infrastructure, networking, and datacenters co-designed to operate as a single platform to meet the demands of cloud-scale agentic inference.

AI infrastructure is a system, and every part of that system is connected. Decisions made in silicon and systems design influence how infrastructure is sourced, deployed, and operated across the fleet. And what we learn once that hardware is running can inform what we build next. This feedback matters because the system never stands still. Demand shifts, component constraints emerge, new capacity comes online, and hardware requirements evolve across the fleet.

We’re proud to share that Microsoft has been named a Leader in the 2026 Gartner® Magic Quadrant™ for Global Industrial AIoT Platforms. We believe this recognition reflects our vision for the future of industrial operations: moving toward intelligent systems that continuously learn, adapt, and improve business outcomes. As industrial organizations modernize, they need a foundation that connects operations across cloud and edge environments.

Every new generation of cloud infrastructure creates two jobs. We must deploy more capable systems quickly, and we must manage the hardware they replace responsibly. Even though these jobs happen behind the scenes, the results matter to Microsoft Azure customers. Newer systems deliver more compute capacity from the space and power available in a datacenter.

One of the defining strengths of the Fabric and SQL communities is how openly people share what they are building and learning. This week, nearly 5,000 data professionals are coming together in Barcelona to do exactly that. Across more than 130 sessions, more than 10 tutorials, community meetups, and roundtable discussions, attendees will exchange practical insights and real-world experiences that others can apply in their own organizations.

Azure continuously advances through new infrastructure generations, platform capabilities, services, and innovations that lead the industry in performance, security, reliability, and efficiency. Our Virtual Machine (VM) Lifecycle policy guides how we manage these transitions, giving Azure customers transparency, predictability, and guidance to plan for and execute technology changes with confidence.

The best model for your business will keep changing. Adopting it should move your business forward, not send your team back to rebuild the architecture around it. As models advance, organizations need the freedom to choose the right model for each workload, and an agent foundation that can evolve with those choices. Microsoft Foundry provides that model—and harness—agnostic foundation for building and running agents.

This first article in our resilience series draws on a conversation with Mark Russinovich about how resilience is changing in the AI era and what it takes to continuously validate it at scale. What surprises me most about resilience failures is how ordinary the drift is. A workload is deployed across availability zones, but a health probe still points to a single dependency. A database supports failover, but the application’s connection string is pinned to one region. Nothing looks broken.