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Summary The recognition for Microsoft over the past couple of weeks comes down to models, infrastructure, data, applications, and developer tools working as one system when AI moves into production. Enterprise AI is moving into production, and our customers are becoming multi-model. Organizations will use frontier models where capability matters, and smaller, specialized, and open-weight…
When a physical security operator begins a shift supporting Microsoft’s global datacenter operations, they depend on a collection of applications and systems that help monitor access activity, review video feeds, investigate alerts, and coordinate physical security operations across a complex global environment. Those tools must be available, responsive, and reliable from the moment a shift…
Summary This post is for technical decision makers evaluating where to run production PostgreSQL workloads. It compares two valid operating models—self-managed PostgreSQL and a managed database service—through business and operational outcomes: control, engineering capacity, resilience, security, cost predictability, risk tolerance, and access to specialist expertise. The right choice depends on which responsibilities the organization needs…
In this article What customers consistently value Turning customer feedback into innovation Thank you to our customers and community Every day, customers trust Microsoft Databases to power their most critical applications, business processes, and AI-powered experiences. Continuous customer feedback provides valuable insights into how these technologies perform in production and where we should continue investing.…
Takeaway: Azure Chaos Studio helps organizations validate application resilience by simulating outages, failovers, network disruptions, and infrastructure failures before they impact production. You don’t know with certainty that your application is resilient until that resilience is tested. Better to learn it isn’t by deliberately breaking it in a test environment and watching how it reacts,…
Poor database performance is never just a database problem. In enterprise teams, it shows up as missed service-level agreements (SLAs), delayed releases, frustrated development teams, and rising operational risk. The performance problem compounds further in business impact, often resulting in frustrated customers, retention and conversion risk, and lost revenue. I have seen this repeatedly while…