One Migration Experience, More Flexibility

Modernizing SQL Server estates is rarely a single-step journey. Organizations often operate across on-premises, hybrid, and cloud environments while balancing application dependencies, operational requirements, and modernization goals. SQL Server migration enabled by Azure Arc simplifies this process by bringing migration activities into a single experience in the Azure portal.

With the July 2026 release, we are announcing General Availability of SQL Server on Azure Virtual Machines as a migration target in Azure Arc, allowing customers to have a greater flexibility to choose Azure destination that best aligns with to your needs without introducing additional tools or migration processes.

Whether migrating to the fully managed Azure SQL Managed Instance service or to SQL Server running on Azure VMs, the experience remains consistent and familiar.

Unified Migration Workflow

A key benefit of SQL Server migration enabled by Azure Arc is that the entire migration lifecycle is managed from a single tool in Azure portal.

After a SQL Server instance is enabled by Azure Arc, customers can:

• Assess migration readiness
• Select a migration target
• Configure migration settings
• Monitor migration progress
• Validate results
• Perform final cutover

All of these activities are performed directly from the Azure portal using a guided workflow designed to simplify migration planning and execution.

The prerequisite remains unchanged: source SQL Server instances must be enabled by Azure Arc before migration can begin. The result is a flexible, scalable, and consistent migration experience that supports hybrid realities, reduces operational overhead, and helps customers modernize SQL Server estates at their own pace.

Consistent Experience Across Azure SQL Targets

Migration to SQL Server on Azure Virtual Machines follows the same operational model already available for Azure SQL Managed Instance migration scenarios.

Customers use the same migration dashboard, monitoring experience, and guided workflow regardless of the destination. This consistency reduces learning curves, simplifies operational processes, and enables teams to select the most appropriate Azure SQL platform without changing migration methodology.

 

Online Migration Using Backup and Log Shipping

Migration to SQL Server on Azure Virtual Machines uses backup and restore with log shipping to support online migration scenarios while minimizing downtime.

The process begins with a full database backup that is restored to the target SQL Server instance running on an Azure Virtual Machine. Transaction log backups that are uploaded continuously by your workflows to Azure Blob Storage are continuously applied to the target database, keeping it closely synchronized with the source environment.

Azure Blob Storage serves as the intermediary staging location between source and target systems. To support efficient data movement and restore operations, both the Azure Blob Storage account and the target SQL Server on Azure Virtual Machines must reside in the same Azure region.

Within the Azure Arc migration experience, customers select the Azure Blob Storage container that stores the backup files. Azure Arc automatically restores the full backup and continuously applies transaction log backups as they become available. Customers are responsible for configuring and maintaining the continuous upload of transaction log backups to Azure Blob Storage.

Customer-Controlled Cutover

When the customer is ready to complete migration, upon customer initiated cutover, Azure Arc performs the final synchronization by applying the last uploaded backup and bringing the target database online.

This approach gives organizations full control over the migration timeline and cutover window, allowing downtime to be planned according to business requirements while reducing operational complexity.

Learn More

To learn more about SQL Server migration enabled by Azure Arc, see: Migration Overview

For information about migrating to SQL Server in Azure VM, see: Migrate to SQL Server in Azure VM

In June, we introduced the next generation of Surface Pro and Surface Laptop, built to deliver performance and flexibility for a new class of AI-powered workflows. You can read the full announcement here.

Today, we’re extending that momentum with commercial availability of Surface Pro for Business 13-inch and Surface Laptop for Business 13.8 and 15-inch powered by Snapdragon X2 Series processors, bringing these capabilities to organizations modernizing endpoints for AI, mobility, and security. 

A closer look at Snapdragon X2 Series: performance and efficiency at scale

The Snapdragon® X2 Series processors - designed for environments where workloads span both device and cloud.

At the center of this release is the Snapdragon X2 Series processors, designed for environments where workloads span both device and cloud. With an integrated Qualcomm^® Hexagon^™ NPU capable of up to a remarkable 80 TOPS, Surface Pro and Surface Laptop support leading on-device AI experiences that can help reduce latency, support privacy-sensitive scenarios, and decrease reliance on constant cloud connectivity. By enabling AI workloads to run where it makes the most sense, organizations gain flexibility to optimize performance, connectivity, and resource utilization as AI adoption expands.

From enterprises to small businesses, customers will benefit from the improved graphics, expanded memory, and modern AI, all with the impressive all-day battery life¹ people have come to expect from Snapdragon-powered Surface devices.

Sustained, efficient performance across power states

Snapdragon X2 Series processors are designed to enable responsive, consistent high performance whether your device is at your desk or unplugged. On Surface Laptop, that means doing up to 25% more productivity tasks on a single charge² and up to 29% more productivity tasks on Surface Pro.³ When you compare this generation of Surface Laptop to Surface Laptop 5, we’re seeing up to 160% more productivity tasks.⁴ This all translates to meaningful improvements in experience and getting work done.

AI acceleration built into the platform

The Qualcomm^® Hexagon^™ NPU with 80 TOPS delivers a significant improvement in performance with up to 85% faster local AI inferencing on Surface Laptop⁵ and up to 80% faster on Surface Pro.⁶ This powerful new microprocessor enables AI workloads, from real-time video enhancements to local, sustained inference, to efficiently run on-device and provides a solid foundation for organizations to integrate local AI models into their line of business applications. In combination with powerful development tools like GitHub Copilot CLI, it’s easier than ever to quickly build proof of concepts of where AI can enhance an existing business process. Be sure to check out this blog as an example.

Planning for hybrid AI, where inferencing traverses both cloud-based and on-device models, will be a critical part of many organizations’ AI adoption strategies. AI-ready devices like Surface Pro and Surface Laptop powered by Snapdragon X2 Series help customers shift toward "unmetered intelligence," enabling AI workloads to run natively on devices by leveraging the combined processing power of CPUs, GPUs, and NPUs for performance, energy efficiency, and cost optimization. This approach gives customers flexibility over where data is processed and creates new opportunities to move AI inferencing closer to the edge. While cloud-based AI services remain an important part of the AI stack, running AI locally on devices can help organizations scale AI experiences predictably as adoption grows.

As highlighted in Satya Nadella’s Build 2026 keynote, the next wave of AI innovation will be defined by the seamless integration of cloud and edge intelligence. Be sure to follow us on LinkedIn and in future blogs where we’ll explore how hybrid AI architectures, local AI capabilities, and Copilot+ PCs are reshaping enterprise computing, and why the shift toward unmetered intelligence is becoming a foundational element of long-term AI strategy.

Graphics and compute improvements for modern workloads

Snapdragon X2 Series delivers massive generation-over-generation improvements, including up to 58% more graphics performance on Surface Laptop⁷ and 53% more graphics performance on Surface Pro⁸ compared to prior Snapdragon based models. Graphics performance is becoming increasingly important as organizations adopt AI-enhanced applications, enabling more responsive visual experiences while helping unlock new workloads that blend productivity, creativity, and local AI.

Configurations with up to 64GB memory are designed to support heavy multitasking and AI-assisted workflows across a range of applications.

Continued progress in Windows on Snapdragon compatibility

Application compatibility continues to be one of the strongest areas of progress for Windows on Snapdragon. Windows provides broad support for many of the applications organizations rely on today, while an increasing number of experiences are being optimized natively for Arm-based devices. For IT decision makers evaluating deployment readiness, resources such as WorksOnWoA.com provide a community-driven view of application compatibility across Windows on Arm devices, making it easier to validate business-critical software and plan migrations with confidence. Together, ongoing ecosystem investments and growing software support continue to strengthen the case for PCs powered by Snapdragon in commercial environments.

Combined with the hardware and software experiences built into Surface, Snapdragon X2 Series helps deliver a platform designed for modern work, where productivity, security, and AI increasingly intersect.

Visual privacy built into the display

Users increasingly work in public and shared spaces where protecting sensitive information on screen can be a real challenge.

Integrated privacy screen engineered directly into the display system of select Surface Laptop 13.8-inch configurations

That’s why we engineered a privacy screen directly into the display system of select Surface Laptop 13.8-inch configurations.

It eliminates the need for external accessories while preserving device design. Rather than relying only on brightness reduction, it uses a luminance control approach that reduces off-axis visibility while maintaining clarity for the user.

• One-touch activation via keyboard or software
• Persistent behavior across sleep and restart states
• Designed to operate alongside Windows brightness and HDR features
• IT administrators can manage the privacy screen using policy settings

You can read in detail about our approach to the integrated privacy screen here: Surface integrated privacy screen overview | Microsoft Learn.

 

Precision with advanced haptics for touchpad and pen

Haptic touchpad with adaptive touch mode and tactile feedback designed to make scrolling and gestures feel more responsive and intuitive.

This generation introduces refined haptic feedback across supported models, designed to make interactions feel more responsive and controlled.

Surface Laptop features a customizable haptic touchpad with adaptive touch mode and tactile feedback designed to make scrolling and gestures feel more responsive and intuitive.

On Surface Pro, haptics extend into the pen experience, providing tactile feedback during writing, drawing, and interaction in supported applications to create a more natural connection between pen and screen. Further detail on our approach to advanced haptics as well as third-party applications taking advantage of the capabilities can be found in this blog.

AI-enhanced camera systems for modern collaboration

Surface Pro and Surface Laptop feature an integrated imaging pipeline that combines camera hardware, firmware, and on-device AI to support consistent video quality across a variety of collaboration scenarios and environments.

The Snapdragon X2 uses its 80 TOPS Qualcomm^® Hexagon^™ NPU to accelerate processing to enhance video in real time, helping improve clarity, lighting, and color while maintaining low latency and efficient performance.

AI-enhanced video, built into the system

Surface integrates camera enhancements at the system level, enabling consistent experiences across supported collaboration tools:

Surface Laptop has the #1 rated laptop camera by DXOMark[9]

• AI Noise Reduction (AINR) is designed to reduce visible noise while preserving detail, particularly in low-light scenarios.
  AI Noise Reduction and certain camera features require supported applications and Windows 11. Results may vary based on lighting conditions, scene composition, and configuration.
• Dynamic tuning, including HDR and exposure adjustments, help improve performance in bright, dim, and mixed lighting.
  HDR functionality requires HDR content and enabling HDR in device settings. Results may vary based on content and environment.
• The platform is designed to adapt to complex lighting while maintaining natural-looking results across a variety of skin tones.

 

 

Surface also uses a coordinated imaging pipeline to support features such as Windows Studio Effects while maintaining system responsiveness:

• Front-end processing prepares a stable baseline image
• AI-driven enhancements via Windows Studio Effects refine the image using on-device models

Recognized camera performance

Third-party validation from DXOMark reflects this achievement, ranking Surface Laptop as the #1 laptop camera⁹ and Surface Pro’s front-facing camera as #2.¹⁰ Stay tuned for an upcoming deep dive on our camera innovations.

New Designed for Surface accessories support diverse needs

The Designed for Surface ecosystem helps organizations further extend the flexibility of Surface devices across a variety of industries and work environments.

Surface Pro 13-inch shown with the Kensington BlackBelt EQ Case, an accessory designed to help protect devices across a variety of work environments

For Surface Laptop, solutions such as STM’s Dux Cases for Surface Laptop, 13-inch and the UAG Essential Armor Case for Surface Laptop, 13.8-inch, provide additional protection options designed to complement mobile workstyles.

For Surface Pro, a broad portfolio of protective cases is available to support diverse needs across industries and environments, from manufacturing and frontline deployments to education and hybrid work scenarios.

When it’s time to connect to displays and other accessories, the Kensington USB4 Portable Docking Station and ViewSonic monitors offer a convenient way to expand a workspace, supporting multiple external displays, pass-through power delivery, and a range of connectivity options.

Together, these accessories complement the Surface for Business portfolio and provide organizations with more ways to support modern work. To explore the full catalog of 250+ Designed for Surface accessories, visit DesignedforSurface.com.

Available for commercial customers starting today

Surface Pro for Business 13-inch and Surface Laptop for Business 13.8-inch and 15-inch powered by Snapdragon X2 Series processors are available for commercial customers starting today in select markets.

They represent the next step in the Surface portfolio, bringing together:

• AI-ready silicon
• Enterprise-grade security and privacy
• Hardware and software designed together to support modern work

Check with your Surface commercial authorized reseller or head to the Microsoft Store to buy direct. When shopping at Microsoft.com, customers can take advantage of fast, free shipping, free 60-day returns, and flexible payment options.¹¹

 

 

As organizations continue to evolve endpoint strategies for AI-powered work, Surface is focused on building devices where advanced capabilities are designed to feel integrated and ready for real-world use from day one, helping customers unlock new opportunities powered by AI across both the cloud and the edge.

Additional Resources

Read: Introducing the next Surface Pro and Surface Laptop, built for performance and flexibility | Microsoft Devices Blog

Visit the Microsoft Store:

• Surface Pro for Business 13-inch (12th edition) (Snapdragon)
• Surface Laptop for Business, 13.8 and 15-inch (8th edition) (Snapdragon)

Watch our new Surface for Business video series:

• Designed for Brilliance
• Engineered for Security
• Trusted for Transformation

Learn more about our solutions at Surface.com/business.

 

 

__________________________________________________________________________________________________________________________________________

References

Posted by Amman Asfaw, Product Manager, Android Studio

Android Studio Quail 2 is now stable and ready for you to use in production, bringing a shift to your IDE with concurrent agentic workflows, natively integrated memory leak profiling, and context-aware crash remediation. Whether you are performing a sweeping architectural overhaul, tracing a memory leak, or resolving a critical production crash, Android Studio keeps you anchored in your workspace by reducing manual friction.

Here’s a deep dive into what’s new:

Multi-tasking with parallel chats

In Android Studio Quail 2, we've been hard at work redesigning Agent Mode from the ground up. This new architecture provides better performance, offers more flexibility for decomposing complex tasks, and improves the suite of internal tools the agent uses to do its work.

In addition to these behind-the-scenes improvements, these changes also allow you to converse across multiple agent chats simultaneously. Waiting for the Android Studio agent to finish a task before you can ask another question or initiate a separate task in Agent Mode is a bottleneck of the past. You can multi-task seamlessly: kick off a UI refactor in one tab, fix a ProGuard rule in a second, and generate documentation in a third.

You can also change which models the agent uses from chat to chat based on the requests you have. Take a look at Android Bench for an analysis of how LLMs perform Android development tasks.

• How to use: Click the "+" icon to start a new parallel conversation, and use the History icon to navigate between active tasks. Alternatively, select File > New > New Agent Tab to open a conversation in a dedicated tab.
• Note: Worktree support is currently unavailable. Exercise caution when running concurrent chats that modify the same project files, which can potentially lead to editor conflicts.

Run multiple agent tasks in parallel with different models of your choice.

Use the History icon to navigate between active tasks.

Memory leak detection with LeakCanary

Memory leaks in Android occur when your code holds onto an object's reference long after its life cycle has ended. This prevents the Garbage Collector from reclaiming that memory, eventually leading to sluggish performance or OutOfMemoryError.

Hunting down memory leaks can be a tedious, manual task. Starting with Android Studio Quail 2, the popular open-source leak detector LeakCanary is natively integrated directly into the Profiler as a dedicated, first-class task.

This integration transforms your debugging performance by lifting and shifting the heap analysis off your resource-constrained testing phone, and onto your powerful development computer. By running the analysis on your computer, leak tracing is up to five times faster and jank-free, leaving your test app running smoothly on the device.

Once a leak is detected during a profiling session:

• The Profiler renders an interactive, color-coded leak trace, grouping occurrences and estimating lost memory.
• You can click Go to declaration on any leaking object in the trace to instantly jump to that exact line of code in your editor.
• You can click Fix with Agent to have the Gemini agent ingest the trace, explain the root cause of the retained reference, and write the exact code change (such as unbinding a listener or clearing a static reference) to plug the leak.

App Quality Insights agent integration

Tracking down the root cause of an app crash can require manually synthesizing stack traces, device data, and source code. However Android Studio’s App Quality Insights (AQI) is now fully integrated with Agent Mode to do the heavy lifting for you.

When you click on a crash in the AQI panel, you immediately get a concise, high-level summary of the issue. If you need to dig deeper, simply click See more. This opens a dedicated chat where the agent uses your selected model and pulls in local source code and the full stack trace to deliver a comprehensive explanation of the failure.

With the new agent integration, you move directly from issue identification to resolution. By clicking Fix with AI, the agent will analyze the issue, propose a step-by-step fix plan, and—upon your approval—apply the necessary code changes directly to your project and verify the resulting fix

The Fix with AI button triggering the agent to analyze the issue, then propose the fix

Quality & stability improvements

Beyond new features, we’ve continued our focus on quality by addressing numerous bugs and incorporating the latest stability and performance improvements from the IntelliJ platform, making this a significant enhancement for your daily development.

Get Started

Ready to dive in and accelerate your development? Download Android Studio Quail 2 and start exploring these new features today! As always, your feedback is crucial to us. Check known issues, report bugs, and be part of our vibrant community on LinkedIn, Medium, YouTube, or X. 

The Microsoft Teams platform mission is to build the best collaborative platform in the world. We want to make it easy for developers to build agents that participate seamlessly in chats, channels, and meetings, helping teams turn ideas into action in real time. By bringing agents directly into the places where collaboration happens, we can help ensure work is completed in the moment rather than getting lost in a stream of conversation. Everything we build is designed to help developers create collaborative experiences that empower people and agents to work together more effectively.

Today we’re launching Building Agents for Teams, a new monthly blog series here on the Microsoft 365 developer blog dedicated to sharing what we’re building, why we’re building it, and how developers can build on it. Expect a mix of deep technical guidance, product updates, customer and partner stories, and perspectives on the future of collaboration.

If you build agents, or you want to, this blog series is for you.

The agent opportunity in Teams

Most agents today are confined to standalone apps and tabs, forcing work into a series of disconnected 1:1 interactions. People must seek out the right agent, enter its environment, and adapt to its way of working instead of having agents participate naturally in existing workflows. That friction may be tolerable for intensive tasks like research or coding, but it quickly adds up across the countless small moments of work that happen every day—checking status, finding data, granting approvals, and bringing the right people together.

In Teams, an agent behaves like another person you collaborate with. You @mention it, add it to a channel, give it a task in plain language so it answers in the thread, and you bring it into a meeting when you need it. There’s no manual or training cost, because people already know how to work with each other, and your agent works the same way.

That means agent adoption happens the moment your users log in for the day. The hard part of distribution – getting your agent in front of real people in the flow of real work – is already solved.

That’s the opportunity for developers: broad user reach and zero learning curve. You can build something useful and put it where work is already happening.

Why should you build an agent now?

A year ago, you could demo an agent, but today you can ship one that completes real tasks. LLMs have made major leaps forward, the latency isn’t a blocker, and the cost keeps falling.

Model Context Protocol gives agents a common way to reach tools, skills and markdown format memories and functionality, and agent-to-agent communication gives them a way to work together. These aren’t Microsoft-centric ideas, they’re standards for how the whole industry connects agents, and the Teams platform speaks them natively.

We are at a unique junction where the technology, standards, and demand are aligned at the same time, making this the perfect time to build collaborative agents.

The value of collaborative agents

Teams is the right home for agents because agents belong where people already collaborate, inside the threads and meetings where the team lives, rather than in a sidebar you have to remember to open. To enable seamless collaboration, we support two kinds of interactions:

• Private interactions are one-to-one, a person and an agent solving a problem together. This is the familiar shape, and we make it excellent: fast, contextual, and private to that person. You can privately interact with an agent in Teams 1:1 chats or with targeted messages grounded in the confines of a group chat, channel, or meeting.
• Public interactions are where it gets interesting. Picture an agent in a group chat, in a channel where the whole team can see it work, or in a meeting where it contributes while everyone watches. Here the agent isn’t a private tool, it’s a participant. Designing for both is harder than designing for one, but the potential value increases exponentially. The agents that matter most will be the ones your whole team can work with, the way you work with each other. We’re building the platform so you can make those agents without reinventing the hard parts yourself.

Build an agent with the Teams SDK

The Teams SDK is your one-stop-shop for building your collaborative agent. Authentication, event routing, and the Teams-specific details are done for you. You just write the logic that makes your agent worth using. 

You can build across TypeScript, C#, and Python. It supports Model Context Protocol for shared tools and memory, and agent-to-agent communication for multi-agent work. You get native support for Adaptive Cards, message extensions, embedded web apps, dialogs, and Microsoft Graph. 

Pick your language, scaffold a project, and ship something small that does one job well, then put it in front of your team. The fastest way to understand this platform is to build on it, and the fastest way to build is to start now:

npm install -g @microsoft/teams.cli
teams project new typescript my-agent

What’s next

This is a series, so here’s some of what’s coming. We’ll go deep on building for public interactions, the channel and meeting scenarios that make Teams different. We’ll cover Model Context Protocol and agent-to-agent patterns with real code. We’ll walk through publishing and reaching users at scale.  We’ll break down privacy and compliance challenges. And we’ll share what we’re learning from the developers already building with us. 

We’re building a collaborative agentic platform, and we’d rather build it with you than for you. We encourage you to give us your feedback and be part of the future we want to work in. 

Welcome to Building Agents for Teams!

Resources

• Agents in Teams
• Teams SDK welcome and overview
• Code samples

The post Building Agents for Teams: Turning conversations into outcomes appeared first on Microsoft 365 Developer Blog.

Merged PR 62457: Fix source-build poison leak from dotnet-user-jwts r…

We are pleased to announce the release of .NET 11 Preview 6. Follow the main announcement and blog announcement.

Browse the release notes for a full list of improvements in this release:

• .NET MAUI
• ASP.NET Core
• C#
• F#
• Container images
• EF Core & Data
• Libraries
• MSBuild
• NuGet
• Runtime
• SDK
• Windows Forms
• WPF

Get started

To get started with .NET 11, install the .NET 11 SDK.

If you're on Windows using Visual Studio, we recommend installing the latest Visual Studio 2026 Insiders. You can also use Visual Studio Code and the C# Dev Kit extension with .NET 11.