Dan Lorenc, co-founder and CEO of Chainguard, joins host Priyanka Raghavan to explore Sigstore and its role in securing the software supply chain. They unpack the challenges of supply chain security, including verifying the origin and integrity of software artifacts, and explain the problems Sigstore is designed to solve. The conversation goes under the hood to examine how Sigstore works, covering key components such as code signing, verification, the certificate authority model, and transparency logs—often compared conceptually to blockchain for their auditability. The episode also highlights real-world adoption, community resources for getting started, and closes with a discussion of Chainguard Images and how development teams can use them to build with more secure base images.

This episode is sponsored by IEEE Computer Society.

Download audio: https://traffic.libsyn.com/secure/seradio/712-dan-lorenc-sigstore.mp3?dest-id=23379

Let the squad help you build your application! Carl and Richard talk to Brady Gaster about Squad, a tool for creating an AI development team using GitHub Copilot. Brady discusses creating specialist agents across various aspects of building an application to keep context as small as possible, along with token consumption. Often, agents communicate with other agents to work through project problems, generating persistent information about the project, including skills as needed. Squad continues to evolve and get more powerful - try it with your application!



Download audio: https://dts.podtrac.com/redirect.mp3/api.spreaker.com/download/episode/70651701/dotnetrocks_1994_building_software_using_squad.mp3

In today’s digital economy, business leaders face a relentless challenge: how to deliver innovation, scale, and resilience without spiraling costs or compromising performance. At the heart of this challenge lies data infrastructure, which is often one of the most critical and most constrained layers of the enterprise stack.

At Microsoft, we’ve seen firsthand how legacy systems, particularly on-premises databases like Oracle, can become a bottleneck to progress. These systems are expensive to maintain, difficult to scale, and increasingly out of step with the agility modern organizations require. But we also understand that migration is not a trivial decision. Concerns about downtime, compatibility, security, and retraining are real.

That’s why we’ve spent the last several years investing in PostgreSQL. Our mission is to make PostgreSQL the most performant, scalable, and enterprise-ready open database platform available. With Azure Database for PostgreSQL and the newly introduced Azure HorizonDB, we’re delivering on that vision.

The cost of standing still

Staying on legacy infrastructure might feel like a safe choice, but it’s rarely the best one. The costs of maintaining aging on-premises databases are rising. Hardware refresh cycles, escalating licensing fees, and the need for niche expertise all add up. Organizations can spend most of their IT budgets and time just maintaining existing systems, leaving little room for innovation.

Some Oracle customers have cited rising licensing costs, performance bottlenecks, and scalability limits as major pain points. Others have reported high support costs and a need for advanced AI capabilities as primary reasons for considering a move away from Oracle databases.

But migration comes with its own set of challenges. What if your applications aren’t compatible with a new platform? What if your team lacks the skills to manage a new system? What if performance suffers or what if something breaks? These are valid concerns, and they are precisely the challenges we’ve engineered PostgreSQL on Azure to solve.

Apollo Hospitals: A case study in transformation

Apollo Hospitals, one of Asia’s largest healthcare providers, faced these very questions. With more than 74 hospitals and over 10,000 beds, Apollo’s digital infrastructure is mission critical. Their in-house hospital information system, built on Oracle, was becoming increasingly difficult to maintain. Performance bottlenecks were impacting care delivery, and the cost of scaling was unsustainable.

Apollo Hospitals made the bold, strategic decision to migrate their databases to Azure Database for PostgreSQL. Their IT and development teams worked closely with Microsoft and their cloud partner to ensure a seamless transition. The results were transformative. Since the migration, Apollo has seen:

• 90% of transactions complete within five seconds, a significant leap in responsiveness for clinical systems.
• Uptime has improved to 99.95%, ensuring that critical hospital operations remain uninterrupted.
• Deployment timelines have dropped by 40%, allowing the organization to roll out new features and updates faster than ever before.

Perhaps most importantly, Apollo has achieved a 60% reduction in operational costs and a 3x improvement in overall system performance. Apollo’s story is a powerful example of what’s possible when you pair the right technology with the right migration strategy.

Smarter Oracle to PostgreSQL migrations with AI-assisted tooling

One of the biggest barriers to migration is the complexity of converting Oracle schemas, stored procedures, and application code. Enterprise applications often rely on thousands of stored procedures, functions, and application-side code (Java, .NET, etc.) built around Oracle-specific syntax. Manually rewriting and validating this code is time-consuming, error-prone, and expensive.

To address this, we introduced the AI-assisted Oracle-to-PostgreSQL migration tool, now available in preview as part of the PostgreSQL extension for Visual Studio Code. This tool is powered by GitHub Copilot and a multi-agent AI system that automates the end-to-end conversion process.

Oracle to PostgreSQL AI-assisted migration tool in action

The tool begins by analyzing Oracle schemas and stored procedures, converting them into PostgreSQL-compatible formats using intelligent pattern recognition and transformation logic. It doesn’t stop at the database layer. It also scans application code, such as Java or .NET, and updates database drivers, rewrites SQL queries, and modifies stored procedure calls to align with PostgreSQL syntax. The tool generates automated unit tests to validate the converted logic and runs post-conversion validation in a scratch PostgreSQL environment to check for functional parity.

The tool uses a hybrid AI architecture with specialized agents for migration, validation, and documentation. It reduces manual effort and minimizes human error. The tool also produces side-by-side comparisons and detailed reports, giving teams the transparency and control they may need to trust the process. By embedding AI-assisted conversion directly into the PostgreSQL extension for VS Code, we’re meeting developers where they work. With GitHub Copilot integration, schema conversion, code refactoring, and validation become part of the same inner loop as code editing and CI/CD. The result is a streamlined, intelligent workflow that reduces friction and accelerates delivery.

Post-migration enterprise-grade performance, scale, and security

PostgreSQL on Azure is more than a cost-effective alternative to legacy systems. With Azure Database for PostgreSQL, and the new Azure HorizonDB service, a move to Azure provides high-performance, scale, and security built and optimized for your most business-critical enterprise workloads.

Azure Database for PostgreSQL continuing innovation

With the introduction of v6-series compute SKUs, customers can now scale vertically up to 192 vCores. This is ideal for high-throughput transactional workloads and complex analytical queries. For workloads that require horizontal scaling, elastic clusters powered by the open-source Citus extension enable distributed PostgreSQL deployments across multiple nodes. This architecture supports multi-tenant SaaS applications, IoT platforms, and large-scale analytics with ease.

Storage performance in Azure Database for PostgreSQL has also taken a leap forward. SSD v2 storage delivers high IOPS and low latency, ensuring that even the most demanding workloads run smoothly. Integrated monitoring and tuning tools like Azure Monitor provide real-time insights and automated optimization, helping teams maintain peak performance without manual intervention.

As always, security remains a top priority. Azure Database for PostgreSQL includes enterprise-grade protections such as Microsoft Defender for Cloud, Entra ID integration, private endpoints, confidential compute SKUs, and end-to-end encryption. These features help organizations meet compliance requirements and safeguard sensitive data.

And because PostgreSQL is open source, there are no licensing fees. It’s one of the most widely used databases in the world, with a vibrant community and deep Microsoft support.

Azure HorizonDB: The future of PostgreSQL at scale

For organizations with extreme performance and scale requirements, we’ve introduced Azure HorizonDB, which is a new, cloud-native PostgreSQL service built for the most demanding workloads. Currently in private preview, Azure HorizonDB supports up to 3,072 vCores and 128 TB of auto-scaling storage. It delivers sub-millisecond multi-zone commit latencies and up to 3x higher throughput than self-managed PostgreSQL. Azure HorizonDB also builds on the AI and agentic capabilities of Azure Database for PostgreSQL with built-in AI model management and DiskANN advanced filtering capabilities, making it ideal for next-generation applications that require real-time analytics and intelligent data processing.

Because Azure HorizonDB is PostgreSQL-compatible, organizations can start with Azure Database for PostgreSQL today and move to Azure HorizonDB if the need arises. This allows for a smooth transition path without the need for replatforming or rewriting applications.

Open source, engineered for the enterprise

Microsoft is proud to be one of the top corporate contributors to the PostgreSQL project. Our engineering teams have upstreamed key innovations, and we’re committed to continuing this work so that PostgreSQL remains the most capable and trusted open-source database for the cloud era.

We believe that open-source data platforms like PostgreSQL are foundational to the next generation of intelligent applications. Our goal is to make PostgreSQL not only accessible but exceptional for enterprise workloads. That means investing in performance, security, developer experience, and ecosystem integration.

The payoff: Innovation, agility, and confidence

Migrating to PostgreSQL on Azure isn’t just about fixing what’s broken. It’s also about unlocking what’s next. Apollo Hospitals, as an example, is now exploring AI-powered clinical dashboards, real-time analytics with Microsoft Fabric, and containerized workloads with Azure Kubernetes Service. Their teams are more agile, their systems are more resilient, and their foundation is ready for the future. As Sridhar Yadla, Apollo’s General Manager, put it:

We’re no longer stuck reacting to problems. Now we’re thinking proactively and looking at how we can evolve.

That’s the power of PostgreSQL on Azure.

Ready to modernize?

If you’re considering a move from Oracle to PostgreSQL, we’ve built the tools, the platform, and the partner network to help you succeed.

Download our latest e-book and explore the Azure Database for PostgreSQL documentation to learn how to plan, execute, and accelerate your journey.

The post From legacy to leadership: How PostgreSQL on Azure powers enterprise agility and innovation appeared first on Microsoft Azure Blog.

Microsoft combines accelerated computing with cloud scale engineering to bring advanced AI capabilities to our customers. For years, we’ve worked with NVIDIA to integrate hardware, software and infrastructure to power many of today’s most important AI breakthroughs.

What’s new at NVIDIA GTC
Expanded Microsoft Foundry capabilities to build, deploy and operate production-ready AI agents on NVIDIA accelerators and open NVIDIA Nemotron models
New Azure AI infrastructure optimized for inference-heavy, reasoning-based workloads, including the first hyperscale cloud to power on next-generation NVIDIA Vera Rubin NVL72 systems
Deeper integration across Microsoft Foundry, Microsoft Fabric and NVIDIA Omniverse libraries and open frameworks to support Physical AI systems from simulation to real‑world operations
From Frontier models to production-ready agents
At the foundation of this system is Microsoft Foundry: serving as the operating system for building, deploying and operating AI at enterprise scale. Foundry builds on Azure to bring together models, tools, data and observability into a single system designed for production agents. Today we’re expanding those capabilities across Foundry Agent Service and NVIDIA Nemotron models.

The next-generation Foundry Agent Service and Observability in Foundry Control Plane are now generally available, enabling organizations to build and operate AI agents at production scale. Foundry Agent Service allows teams to quickly develop agents that reason, plan and act across tools, data and workflows. Once created, Foundry Control Plane provides the developer end-to-end visibility into agent behavior, unlocking both developer productivity as well as enterprise trust. Companies such as Corvus Energy are already using Foundry to replace manual inspection workflows with agent-driven operational intelligence across their global fleet.

We are further simplifying the path from prototype to production with the availability of Voice Live API integration with Foundry Agent Service, in public preview, which enables developers to build voice-first, multimodal, real-time agentic experiences. This pairs with the general availability of a refreshed Microsoft Foundry portal and expanded integrations for Palo Alto Networks’ Prisma AIRS and Zenity, delivering deeper builder experiences and runtime security across the entire agent lifecycle.

NVIDIA Nemotron models are also now available through Microsoft Foundry, joining the widest selection of models on any cloud, including the latest reasoning, frontier and open models. This bolsters our recent partnership announcement bringing Fireworks AI to Microsoft Foundry, enabling customers to fine-tune open-weight models like NVIDIA Nemotron into low-latency assets that can be distributed to the edge.

Scaling AI infrastructure for the world’s most demanding workloads
Inference AI workloads are reshaping cost, performance and system design requirements. To operationalize agentic AI at scale, customers need purpose-built infrastructure for inference‑heavy, reasoning‑based workloads that can be deployed and operated consistently across global and regulated environments.

Microsoft’s AI infrastructure approach is engineered to seamlessly bring next-generation NVIDIA systems into Azure datacenters that are designed for power, cooling networking and rapid generational upgrades. This allows our customers to move with speed and agility and stay at the leading edge from generation to generation.

In less than a year, we’ve deployed hundreds of thousands of liquid-cooled Grace Blackwell GPUs across our global datacenter footprint, and now we are excited to be the first hyperscale cloud to power on NVIDIA’s newest Vera Rubin NVL72 in our labs. Over the next few months, Vera Rubin NVL72 will be rolled out into our modern, liquid-cooled Azure datacenters.

Microsoft’s infrastructure innovation with NVIDIA also extends to sovereign and regulated environments to give customers control of both where AI runs and how it evolves over time. Recently, we announced Foundry Local support for modern infrastructure and large AI models, and today we now have initial support for NVIDIA Vera Rubin platform on Azure Local, extending accelerated AI capabilities to customer-controlled environments. This approach allows organizations to plan for next-generation AI workloads, including reasoning-based and agentic systems, while maintaining Azure-consistent operations, governance and security through our unified software layer with Azure Arc and Foundry Local.

YouTube Video

Bringing AI into the physical world
As AI moves beyond digital experiences, Microsoft and NVIDIA are collaborating to support the next wave of Physical AI. At GTC, this work centers on NVIDIA Physical AI Data Factory Blueprint, with Microsoft Foundry as the platform for hosting and operating Physical AI systems on Azure at cloud scale.

By integrating this blueprint with Azure services as part of a Physical AI Toolchain, Microsoft enables developers to build, train and operate physical AI and robotics workflows that connect physical assets, simulation and cloud training environments into repeatable, enterprise-grade pipelines. To support, we are introducing a public Azure Physical AI Toolchain GitHub repository integrated with the Nvidia Physical AI Data Factory and with core Azure services.

To further the impact of AI in real‑world, physical environments, today Microsoft and NVIDIA are deepening the integration between Microsoft Fabric and NVIDIA Omniverse libraries, connecting live operational data with physically accurate digital twins and simulation. This allows organizations to see what’s happening across their physical systems, understand it in real time and use AI to decide what to do next. In practice, customers in manufacturing and operations and beyond are using this approach to move beyond dashboards and alerts to coordinated, AI‑driven action across machines, facilities and workflows.

From innovation to impact
Microsoft is delivering reliable, production‑scale AI by bringing together its global AI infrastructure, platforms and real‑world systems with the latest innovation from NVIDIA. For customers, this means the ability to operate intelligence continuously, running inference-heavy, reasoning-based and physical AI workloads with the performance, security and governance required for real businesses and regulated industries.

Whether powering always-on agents, scaling next-generation AI infrastructure or deploying intelligent systems in factories, energy facilities and sovereign environments, Microsoft and Nvidia are helping customers move faster from insight to action.

Yina Arenas leads product strategy and execution for Microsoft Foundry, overseeing the end–to–end AI product portfolio, infrastructure, developer experiences and foundation model integration across OpenAI, Anthropic, Mistral, DeepSeek and others. She delivers an enterprise ready, production grade AI platform trusted by global customers for secure, reliable and scalable AI.

The post Microsoft at NVIDIA GTC: New solutions for Microsoft Foundry, Azure AI infrastructure and Physical AI appeared first on Microsoft Azure Blog.

This week, we are excited to kick off SQLCon 2026 alongside FabCon in Atlanta. Bringing these SQL and Fabric communities together creates a unique opportunity to learn, connect, and share what’s next across the Microsoft databases portfolio.

This year is especially meaningful, as it marks the return of a Microsoft‑led SQL community event, while also showcasing how SQL continues to evolve as a critical part of Fabric. It is not just about new technology, but about reconnecting with each other and building the future of SQL together.

It’s inspiring to see the Microsoft SQL community continue to grow and engage, with user groups worldwide keeping conversations active across the SQL portfolio and a lot of customers using Microsoft SQL to innovate every day. With a comprehensive portfolio built on strategic common foundations and available across edge, PaaS, and SaaS, Microsoft databases form a unified platform for modern enterprise needs, whether you are migrating and modernizing, building cloud-native AI applications, or unifying your data.

Learn more about what’s happening at SQLCon
Migrate and modernize with Azure SQL
Many of our customers are not modernizing in one big leap. You are evolving from SQL Server to hybrid and then to cloud services, and you want that journey to feel familiar, predictable, and low risk. That is exactly what Azure SQL is designed to deliver. Built on a consistent Microsoft SQL foundation from on premises to the cloud, Azure SQL brings AI capabilities directly into your database experience, along with enterprise‑grade security, high availability, and the flexibility to scale as your needs grow. Azure SQL is fully SQL compatible, delivers strong performance and low latency, and supports hybrid scenarios through Azure Arc.

AI agents are becoming an important accelerator for database migration and modernization at Microsoft, helping our customers reduce manual effort and move faster with more guided experiences across the journey. The general availability of GitHub Copilot in SSMS 22 is a great example of that investment in action: you can use the same GitHub Copilot experience you already use in Visual Studio and VS Code, now inside SQL Server Management Studio (SSMS), with chat and code assistance that helps you write, edit, and refactor T‑SQL more quickly and confidently. Whether you are a developer or database administrator (DBA), new to SQL or highly experienced, GitHub Copilot can support common workflows like improving queries and assisting with troubleshooting and administration tasks right where you work, and we are continuing to expand what it can do.

Today we are announcing savings plan for databases, a flexible, spend-based pricing option that helps you save up to 35%1 vs. pay-as-you-go prices on a one-year commitment. Savings plan for databases is designed for modern, evolving database environments: Customers commit to a fixed hourly spend for one year and receive lower prices across eligible Azure database services. Savings are automatically applied to the highest-value usage each hour, helping reduce costs while supporting migration, modernization, and architectural change.

Build cloud-native AI apps at scale
Once you move to the cloud, the questions shift. How do you build faster, scale smarter, and unlock more value from your data without re‑architecting everything you have already built? That is where Azure SQL Database Hyperscale comes in.

With Azure SQL Database Hyperscale, customers gain better price-performance, elastic scale and resilience for any workload, without the cost or disruption of rewriting T‑SQL or reworking operational models. Its unique architecture, built on shared storage and multiple replicas, allows you to scale reads independently from writes. With built‑in HTAP isolation, applications can handle massive transactional and analytical workloads without complex redesign. New capabilities now in public preview extend that foundation even further, including the SQL MCP Server for securely connecting SQL data to AI agents and Copilots, as well as larger 160 and 192 vCore options for high‑throughput workloads.

We’re delivering faster, more capable vector indexes to power AI applications. Recent enhancements improve vector search performance and efficiency with no code changes required. With full insert, update, and delete support, vector indexes stay current in real time, enabling dynamic applications. Features like quantization, iterative filtering, and tighter query optimizer integration provide faster, more predictable results, helping teams build responsive AI experiences directly on their SQL data.

Temenos built its next‑generation banking platform, Temenos Core, on Azure using Azure SQL Database Hyperscale to achieve global scale, high availability, and resilient performance. The platform processes billions of transactions daily and more than 17,500 transactions per second at peak. By building on Hyperscale, Temenos reduced onboarding time, accelerated innovation, and shifted banks from worrying about downtime to competing on availability and digital innovation.

Unify your data estate with SQL database in Fabric
We continue to raise the bar on enterprise readiness for SQL database in Fabric by bringing enterprise-grade security and compliance capabilities directly into the platform. Today at SQLCon, we announced the general availability of features including SQL Auditing, Customer‑Managed Keys, and Dynamic Data Masking, and the preview of workspace‑level Private Link. We brought these enhancements to help customers meet strict governance and regulatory requirements without adding operational complexity. The result is confidence that your SQL workloads in Fabric are secure, compliant, and ready for production.

SQL database in Fabric is becoming even more powerful for AI‑driven applications. The same vector indexing enhancements available in Azure SQL Database Hyperscale are now built into SQL database in Fabric as well. Because both are powered by the same Microsoft SQL engine, customers benefit from consistent performance, capabilities, and innovation across the SQL portfolio—making it easier to build intelligent applications wherever their data lives.

Finally, moving to SQL database in Fabric is simpler than ever. The Migration Assistant now supports SQL database in Fabric as a target destination. It provides a Copilot-assisted experience that helps SQL developers assess readiness, migrate schema, identify compatibility issues, and copy data with less manual effort. By preserving familiar SQL skills and workflows, customers can modernize at their own pace while accelerating time to value on Fabric’s unified analytics and AI platform.

Learn more about SQL database in Fabric
There is one more Fabric innovation that matters deeply for how we deliver Microsoft databases as a unified platform. As applications grow more sophisticated, most organizations now rely on a mix of SQL and NoSQL databases across cloud, on‑premises, and edge environments. Provisioning, monitoring, and maintaining health across a growing database fleet often requires multiple tools and portals, making it harder to see what’s happening and manage at scale.

To address this, we are introducing the Database Hub in Microsoft Fabric, now available in early access. The Database Hub provides a unified database management experience that brings together databases across edge, cloud, and Fabric into one coherent view. From a single place, database teams can explore, observe, govern, and optimize their entire estate, including Azure SQL, Azure Cosmos DB, Azure Database for PostgreSQL, SQL Server enabled by Azure Arc, and Azure Database for MySQL without changing how each service is deployed or operated.

Built for scale, the Database Hub introduces an agent-assisted, human-in-the-loop approach to database management. Intelligent agents continuously reason over estate-wide signals to surface what changed, explain why it matters, and guide teams toward what to do next, while built-in observability, delegated governance, and Copilot-powered insights help teams move from insight to action with greater confidence. With the Database Hub, teams spend less time navigating tools and more time enabling what comes next: unlocking deeper integration across applications, analytics, and AI from a single control plane for the Microsoft databases portfolio.

Database Hub is available today in early access. Sign up today and see how the Database Hub can bring clarity and control to your database estate.

Moving forward with the SQL community
SQLCon is about bringing the SQL community together. It is about rebuilding connections and shared learning. It also reflects our long-term commitment to SQL. With a comprehensive portfolio built on strategic common foundations and available across edge, PaaS, and SaaS, Microsoft databases provide a unified platform for modern enterprise needs, whether you are migrating and modernizing, building cloud-native AI applications, or unifying your data. We are investing in SQL for the future, alongside the community that continues to shape it.

Finally, SQLCon is coming to Europe! Join the global data and SQL community from 28 Sep – 01st October, 2026 in Barcelona, Spain for hands-on learning, expert insights, and real-world stories. Register to be a part of it. I can’t wait to see you there.

Additional SQL resources
Get early access to Database Hub in Fabric
Microsoft Azure Summit: Migrate and Modernize with Agentic AI
What is new about SQL database in Fabric
Learn more about savings plan for databases
1Customers may see savings estimated to be between 0% and 35%. The 35% savings estimate is based on one Azure SQL Database serverless running for 12 months at a pay-as-you-go rate vs. a reduced rate for a 1-year savings plan. Based on Azure pricing as of March 2026. Prices are subject to change. Actual savings may vary based on location, database service, and/or usage. 

The post Advancing agentic AI with Microsoft databases across a unified data estate appeared first on Microsoft Azure Blog.

The Microsoft Rewards Total Prize Drop is officially underway, and it’s bringing the biggest rewards yet. For a limited time, Microsoft Rewards members can enter for a chance to win a $1,000,000 USD cash grand prize or one of three customizable Mercedes‑Benz cars. Terms apply.

And that’s just the top of the drop. Every single day, thousands of Instant Win prizes are up for grabs. Many of these chances come from something you already do: searching on Bing. Each search gives you another shot at an Instant Win, and another way to earn bonus entries.

This is where the fun really begins. Everyday things you’re already doing could turn into real chances to win. Search for what you love. Check out what’s trending. Play Jewel on Xbox. Test‑drive Microsoft 365. Browse with Edge. Keep Copilot close by when you download the app. Explore the newest PCs. Real actions, real prizes, real people. Just ask Ivan from Singapore, our most recent winner, who scored the $1 million prize in the Ultimate Giveaway. Could you be next?

                    

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Why join Microsoft Rewards?
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Enter today. Total Prize Drop ends May 21, 2026.

<sub>Sweepstakes + Instant Win: United States, Puerto Rico, United Kingdom, Germany, Canada, Japan, France, Spain, Mexico, Austria, Norway, Ireland, New Zealand, Switzerland, South Africa, Czech Republic, Greece, Peru, Ecuador, Costa Rica, Guatemala, Finland, Romania, Luxembourg
NO PURCHASE NECESSARY. Instant Win and Sweepstakes: Ends 5/21/26 at 11:59:59 PM PT. Must be age of majority to enter. For Official Rules, including odds, and prize descriptions, see Instant Win rules: https://aka.ms/win-IW-Rules and Sweepstakes rules: https://aka.ms/win-Sweeps-Rules. Sweepstakes open only to legal residents of the 50 United States, D.C. & P.R., Canada, the United Kingdom, France, Germany, Ireland, Austria, Greece, Finland, Luxembourg, Spain, Switzerland, Norway, Mexico, Peru, Ecuador, Costa Rica, Guatemala, New Zealand, Japan, the Czech Republic, Romania and South Africa. Sweepstakes Grand Prize: one (1) prize of $1,000,000 USD in cash (equivalent to approximately $1,380,000 CAD / £740,000 GBP / €860,000 EUR / Fr. 800,000 CHF / kr 10,100,000 NOK / $18,000,000 MXN / S/ 3,400,000 PEN / ₡498 000 000 CRC / Q7,000,000 GTQ / $1,730,000 NZD / ¥157,000,000 JPY / Kč 20,800,000 CZK / lei 4,350,000 RON / R 16,500,000 ZAR). Grand Prize will be awarded in USD dollars. Free Entries into the Grand Prize Draw with Microsoft Rewards Account: print full name, address, phone number (with area code), date of birth, and email address on a 3 x 5-inch card and mail it to “Microsoft Rewards Prize Drop Sweepstakes, Free to Enter” at the address corresponding to your country of residence in the Sweepstakes Official Rules. Requests must be postmarked by 5/21/26 and received by 5/29/26. Additional Sweepstakes entry opportunities will be available, see terms here. These additional entry methods are subject to the Sweepstakes Official Rules for the Sweepstakes including (but not limited to) any and all eligibility and registration requirements, as well as any limitation on the total number of entries which may be earned across all entry methods. Connect time charges may apply. Canadian and Mexican residents: Skill-testing question applies. Void where prohibited.

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NO PURCHASE NECESSARY. Ends 5/21/26 at 11:59:59 PM PT. Must be age of majority. Open to U.S. + D.C./P.R., CA, UK, FR, DE, NL, IE, AT, GR, FI, LU, ES, CH, NO, MX, PE, EC, CR, GT, NZ, JP, SG, KR, CN, HK, CZ, RO, and ZA. To enter and for Official Rules, including odds, and prize descriptions, see Rules: https://aka.ms/win-IW-Rules. Connect time charges may apply. Canadian and Mexican residents: Skill-testing question applies. Void where prohibited.</sub>