We’re proud to share that Microsoft has been recognized as a Leader in the 2026 Gartner® Magic Quadrant™ for Distributed Hybrid Infrastructure for the fourth consecutive year. Microsoft is positioned highest for Ability to Execute. We believe this recognition reflects the strength of Microsoft’s unified approach to distributed infrastructure. With Azure Local and Azure Arc,…
I am pleased to share that Microsoft has been named a Leader in the 2026 Gartner® Magic Quadrant™ for Container Management, positioned furthest to the right on Completeness of Vision. We believe this recognition reflects our ability to help customers modernize existing applications and embrace AI workloads without adding operational complexity. Furthermore, this recognition comes…
This blog post is the fourth and final installment of The Economics of Agent Optimization, which shares the strategies, capabilities, and proof points that can help you optimize agent costs and run AI as a managed investment system on Microsoft Foundry. The first post set out the three decisions that systems rest on, the second…
Why infrastructure resiliency is essential for modern applications and AI workloads Organizations today face constant pressure to modernize; business-critical applications are being transformed, AI workloads are becoming foundational to business operations, and infrastructure environments continue to grow in complexity. Yet modernization only succeeds when organizations have confidence that their applications, data, and infrastructure can withstand…
Takeaway: Zone resiliency isn’t a single number you apply to a whole workload. The useful question isn’t “how many zones?” but “how many zones does each component need to survive the loss of one?” Decide zone patterns component by component, use service-managed zone redundancy wherever it fits, and reserve three-zone designs for the components that…
For research and development (R&D) organizations, the promise of agentic AI is not a better one-time answer. It is a new way to explore complex scientific and engineering problems: pursuing multiple hypotheses, validating them against evidence, learning from what does not work, and adapting their approach as new information becomes available. This unique nature of…