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.
Process mining is now part of Microsoft’s process automation suite, giving you the KPIs and visualizations you need to identify bottlenecks in both manual workflows and software processes.
Configuration as code is coming to Microsoft’s Azure-hosted workstations, allowing us to use WinGet, YAML files, and PowerShell DSC to deliver ready-to-run toolchains to developers.
Bundled with Windows 11, Power Automate for Windows lets you wrap low-code workflows around your desktop applications. A new SDK supports custom actions.
Microsoft’s open-source, hardware-aware optimization tool for ONNX models is an essential part of its AI application development tool chain.
The addition of MQTT protocol support paves the way to bringing SCADA control systems and other industrial IoT deployments to Azure. Here’s how to get started.
Microsoft has introduced a spectrum of new tools to make it easier to customize and focus the output of GPT-based AI models. Cosmos DB plays an important role.
Microsoft’s open-source KubeAI Application Nucleus is a low-touch, Kubernetes-based system for building and running machine learning applications for edge devices.
How much will Kubernetes cost to run? That question has become much easier to answer for Azure Kubernetes Service, thanks to OpenCost integration.
Microsoft’s Semantic Kernel SDK makes it easier to manage complex prompts and get focused results from large language models like GPT.
Add REST and GraphQL APIs to any database with a handy .NET CLI tool.
Microsoft is working to bring open source machine learning models into Azure applications and services.
Microsoft’s open source tool helps you write code to work with generative AI, ensuring results give correct information and stay on topic.
Old languages never die, they just get ported to a new runtime. Here’s a look at a new open source project for .NET that can help modernize Cobol.
Microsoft’s Azure-hosted OpenAI language models are now generally available, and it’s surprisingly simple to use them in your code.
GitHub Pages lets you manage content exactly the same way you manage code, pushing from content development branches to main to publish new content. It’s a great way to ensure that code and documentation are delivered side by side.
Inside one of the technologies that powers Azure Kubernetes Service’s WebAssembly support, and promises to make applications portable across clouds and other hosts.
With Cadl, you can write a 500-line OpenAPI definition in 50 lines of code. It’s a logical way for architects and developers to construct and constrain APIs.
WebAssembly is ideal for cloud-native apps. A shift from Krustlets to runwasi should simplify managing Wasm nodes in Azure Kubernetes Service.
Microsoft’s Azure incubation team is experimenting with blockchain technologies. Can the company make them ready for the enterprise?
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