At Build, Microsoft described how Azure is supporting large AI workloads today, with an inference accelerator, high-bandwidth connections, and tools for efficiency and reliability.
Microsoft delivers a one-stop shop for big data applications with its latest updates to its data platform.
Microsoft’s Power Platform AI tooling gets a major update and a new role in process automation.
Microsoft is not simply making a big bet on AI in Windows, but betting that natural language and semantic computing are the future of Windows.
Microsoft has added new skills to its LLM-powered Copilot in Azure and opened up access to everyone.
Microsoft’s Concise API Design Language has a new name and a larger role to play in building REST, OpenAPI, gRPC, and other services.
New tools for filtering malicious prompts, detecting ungrounded outputs, and evaluating the safety of models will make generative AI safer to use.
A new managed signing service on Azure offers low-cost, low-touch code signing with integration into GitHub Actions.
An open-source collection of low-level tools helps you troubleshoot cloud-native applications by delivering key data from the heart of the Linux kernel.
Microsoft has rolled its Git Virtual File System and Scalar optimizations into a fork of Git designed to support enormous repos and large distributed teams.
It’s time to update your older cross-platform .NET applications. Should you use MAUI or something else?
New techniques make graph databases a powerful tool for grounding large language models in private data.
The open-source Retina brings observability to container networks in Kubernetes using eBPF.
Microsoft continues to evolve its Azure Kubernetes Service. Kubernetes co-creator Brendan Burns tells us where it’s going next.
The open-source cloud-native runtime security tool is now a graduated CNCF project. Is it time to use it in your Kubernetes applications?
It’s time to move away from passwords. Microsoft has tools to help you get started.
Microsoft has quietly added a cloud-hosted secure tunnel to Visual Studio and VS Code, making it easier to test APIs, web services, and mobile back ends.
A first preview release of the next .NET sets the scene for a year of platform development focused on cloud-native and AI-powered applications.
LinkedIn needed a better way to test and tune machine learning models, so it wrote its own tool that plugs into Visual Studio Code.
Microsoft Graph provides one unified API to search all content in SharePoint, OneDrive, Outlook, and other Microsoft 365 services. That changes how we build SharePoint applications.
The cloud and automation go hand in hand. Use Azure Automation and runbooks to deploy and manage Azure infrastructure and platform services.
Amazon simplifies writing Lambda functions in C# with features like Lambda Annotations, which uses C# source generators to generate code from a REST API path. Support for .NET 8 is coming soon.
Microsoft Research is experimenting with the development of tailored AIs that minimize resource usage.
Microsoft is laying the groundwork for a hardware-accelerated Azure cloud with its own custom AI silicon, Arm server processors, virtualization offload, and more.
How do we measure developer productivity, and how do we use that to improve products and the workplace?
Available in an early preview, Microsoft’s AI development environment for the desktop lets you build small language models that run on PCs and mobile devices.
Hardware-backed confidential computing in Microsoft Azure now includes protected environments for VMs, containers, and GPUs, without the need to write specialized code.
From GPU support to reference implementations, the latest updates to Azure Container Apps combine Microsoft’s commitment to developer productivity with its latest AI development tools.
Microsoft’s low-code and copilot-driven AI builder makes it easy to train chatbots on internal data, and ‘boost’ them with GPT and external data sources when appropriate.
Microsoft’s cloud-based AI development environment, now in public preview, takes a more streamlined approach to building AI-powered applications.
Leaner container images, simpler code syntax, and a welcome surprise—.NET Aspire, an opinionated stack for building cloud-native applications with .NET.
A new open-source tool from The Browser Company sets us on the road to bringing Swift apps from iOS and macOS to Windows.
A new release of Uno in advance of .NET 8 adds support for MVUX and C#-based markup.
Build, manage, and deploy Kubernetes applications using infrastructure-as-code techniques, with separation of concerns and dependency graphs.
Microsoft’s cloud-hosted data lake and lakehouse platform gains new data science tools and opens up Power BI datasets to Python, R, and SparkSQL.
Microsoft’s new C# Dev Kit extension for Visual Studio Code turns the programmer’s editor into a complete development environment for .NET.
Microsoft’s free cloud migration tools simplify the process of bringing applications and services out of your data center and into the cloud.
Updates to Windows Subsystem for Linux and Windows Subsystem for Android make cross-platform development on Windows easy.
Azure Notification Hubs can deliver notifications to any device from any platform anywhere, without your having to manage all aspects of the messaging stack.
Often the hardest part of contributing to an open source project is learning where to start. Microsoft has a cure for that.
Adaptive Card-based Loop components are live and portable chunks of functionality that you can embed in Outlook, Teams, business apps, and your own code. Here’s how to get started.
Microsoft’s Azure Space platform and Azure Orbital Space SDK are taking edge computing to the final frontier, starting with satellite image processing, geospatial, and communications applications.
With Microsoft’s yearly .NET release just around the corner, it’s time to start thinking about the changes you will need to make to your code.
Microsoft’s Cognitive Search API now offers vector search as a service, ready for use with large language models in Azure OpenAI and beyond.
Microsoft Azure’s new, unified data platform aims to be your one-stop shop for analytics and machine learning at scale.
Large language models mean not having to use complicated regular expression handlers to turn text into data. Using TypeChat, you can ensure that that data is type-safe JSON.