Meet First Round of Speakers for Microsoft JDConf 2025: Code the future with Java and AI
We are excited to share the initial lineup of speakers and sessions for Microsoft JDConf 2025, taking place on April 9-10. Whether you are an experienced developer or just starting out, JDConf offers valuable opportunities to explore the latest advancements in Java, Cloud and AI technologies, gain practical insights, and connect with Java experts from across the globe. Secure your spot now at jdconf.com. Here are the initial sessions and speakers who will provide valuable insights into Java, Cloud, and AI. Java 25. Explore The Hidden Gems of Java 25 with Mohamed Taman as he uncovers key Java SE features, updates, and fixes that will simplify migration to new Java and enhance your daily development workflow. Virtual Threads. Virtual Threads in Action with Jakarta EE Core Profile by Daniel Kec will explore Helidon 4, the first Jakarta EE Core Profile runtime built on a pure Virtual Thread-based web server. Spring Boot. Bootiful Spring Boot: A DOGumentary by Josh Long will dive into Spring Boot 3.x and Java 21, exploring AI, modularity, and powerful optimizations like virtual threads, GraalVM, and AppCDS. Jakarta EE 12. What Comes After Jakarta EE 11? Reza Rahman and Emily Jiang will share roadmap, contribution pathways, and key updates, including Security, Concurrency, Messaging, and new APIs. GitHub Copilot. Use GitHub Copilot in your favorite Java IDEs by Julia Kordick and Brian Benz will show how to maximize productivity with GitHub Copilot’s latest features in IntelliJ, VS Code, and Eclipse. AI Dev Experience. Boosting AI Developer Experience with Quarkus, LangChain4j, and Azure OpenAI by Daniel Oh will demonstrate how this trio streamlines development and powers intelligent applications. Spring AI. How to Build Agents with Spring AI by Adib Saikali will showcase building intelligent AI agents, covering key patterns like self-editing memory, task orchestration, & collaborative multi-agent systems. LangChain4j. AI-Powered Development: Hands-On Techniques for Immediate Impact by Lize Raes will explore AI tools like Cursor, Devin, and GitHub Workspace to help developers accelerate workflows and embrace AI-driven coding practices. Data and AI. Powering Spring AI with RAG and NoSQL by Theo van Kraay will demo how integrating Cosmos DB as vector store with Spring AI enables scalable, intelligent and high performing applications. Automated Refactoring. The State of AI in Large Scale Automated Refactoring by Jonathan Schneider will show how OpenRewrite’s Lossless Semantic Tree enhances AI-driven refactoring for accurate decision-making. Java Modernization. Cloud Migration of Java Applications Using Various Tools and Technique by Yoshio Terada will demo modernizing legacy apps with tools like VS Code, GitHub Copilot, and Azure Migrate. AI-Driven Testing. Test Smarter, Not Harder: AI-Driven Test Development by Loiane Groner will demo how AI-powered tools like GitHub Copilot enhance TDD through automated test generation and improved test coverage, even for legacy code. RSVP Now Join us at Microsoft JDConf 2025 and code the future with Java, Cloud and AI. RSVP today at jdconf.com to secure your spot. Your registration grants access to live streams, on-demand sessions, and a collection of valuable resources. Stay tuned for updates on more engaging sessions and inspiring speakers. Connect with a community shaping tomorrow’s technology and gain practical insights from industry leaders. Follow the conversation using #JDConf, and visit jdconf.com for the latest agenda and schedule. Secure your spot now at jdconf.com!Enhancing Security for Azure Container Apps with Aqua Security
Azure Container Apps (ACA) is a developer-first serverless platform that allows you to run scalable containerized workloads at any scale. Being serverless provides inherent security benefits by reducing the attack surface, but it also presents some unique challenges for any security solution. Hence, we’re happy to announce that our partner, Aqua has just certified Azure Container Apps for their suite of security solutions. Azure Container Apps: Built-In Security Features Due to its purpose-built nature ACA offers several built-in security features that help protect your containerized applications: Isolation: ACA runs your workload without the need for root access to the underlying host. Additionally, it’s trivial and requires minimal overhead to isolate different teams in their own environments without the need to painfully cordon off each team via Kubernetes namespaces. Network Security: ACA supports virtual network integration, allowing you to control inbound and outbound traffic to your applications on a both a per app basis as well as for an entire environment all at once. Additionally, we provide protection against common layer-7 vulnerabilities such as redirection attacks. Managed Identity: ACA integrates with Azure Active Directory, enabling secure access to other Azure services without managing credentials. While these features provide a solid foundation, securing containerized workloads requires a comprehensive approach that addresses the entire lifecycle of your applications. This is where Aqua’s suite of tools excels. Elevating ACA's Security Posture using Aqua Aqua Security is a certified security solution for ACA, offering a full-lifecycle approach to securing your containerized applications. Here’s how Aqua enhances ACA's security capabilities: Supply Chain Security: Aqua scans container images for tampering and potential supply chain attacks, ensuring that only verified and secure images are deployed. Comprehensive Image Scanning: Aqua scans container images in Azure Container Registry (ACR) and CI/CD pipelines for vulnerabilities, misconfigurations, malware, and embedded secrets, enabling developers to address issues early. Image Assurance Policies: Aqua enforces policies to ensure that only compliant images are deployed, minimizing risks and ensuring adherence to security and compliance standards. Agentless Discovery and Scanning: Aqua automatically discovers and scans all running services and assets, providing broad visibility into your ACA workloads. Runtime Protection with MicroEnforcer: Aqua's MicroEnforcer provides non-invasive runtime security, detecting and preventing threats such as cryptocurrency mining, reverse shell execution, and unauthorized access. By leveraging Aqua's security solutions, organizations can confidently meet the most stringent security requirements for their ACA workloads. For more information on how to use Aqua's tooling with ACA, visit the Aqua blog: Securing Azure Container AppsIntroducing Serverless GPUs on Azure Container Apps
We're excited to announce the public preview of Azure Container Apps Serverless GPUs accelerated by NVIDIA. This feature provides customers with NVIDIA A100 GPUs and NVIDIA T4 GPUs in a serverless environment, enabling effortless scaling and flexibility for real-time custom model inferencing and other machine learning tasks. Serverless GPUs accelerate the speed of your AI development team by allowing you to focus on your core AI code and less on managing infrastructure when using NVIDIA accelerated computing. They provide an excellent middle layer option between Azure AI Model Catalog's serverless APIs and hosting models on managed compute. It provides full data governance as your data never leaves the boundaries of your container while still providing a managed, serverless platform from which to build your applications. Serverless GPUs are designed to meet the growing demands of modern applications by providing powerful NVIDIA accelerated computing resources without the need for dedicated infrastructure management. "Azure Container Apps' serverless GPU offering is a leap forward for AI workloads. Serverless NVIDIA GPUs are well suited for a wide array of AI workloads from real-time inferencing scenarios with custom models to fine-tuning. NVIDIA is also working with Microsoft to bring NVIDIA NIM microservices to Azure Container Apps to optimize AI inference performance.” - Dave Salvator, Director, Accelerated Computing Products, NVIDIA Key benefits of serverless GPUs Scale-to zero GPUs: Support for serverless scaling of NVIDIA A100 and T4 GPUs. Per-second billing: Pay only for the GPU compute you use. Built-in data governance: Your data never leaves the container boundary. Flexible compute options: Choose between NVIDIA A100 and T4 GPUs. Middle-layer for AI development: Bring your own model on a managed, serverless compute platform. Scenarios Whether you choose to use NVIDIA A100 or T4 GPUs will depend on the types of apps you're creating. The following are a couple example scenarios. For each scenario with serverless GPUs, you pay only for the compute you use with per-second billing, and your apps will automatically scale in and out from zero to meet the demand. NVIDIA T4 Real-time and batch inferencing: Using custom open-source models with fast startup times, automatic scaling, and a per-second billing model, serverless GPUs are ideal for dynamic applications that don't already have a serverless API in the model catalog. NVIDIA A100 Compute intensive machine learning scenarios: Significantly speed up applications that implement fine-tuned custom generative AI models, deep learning, or neural networks. High performance computing (HPC) and data analytics: Applications that require complex calculations or simulations, such as scientific computing and financial modeling as well as accelerated data processing and analysis among massive datasets. Get started with serverless GPUs Serverless GPUs are now available for workload profile environments in West US 3, Australia East, and Sweden Central regions with more regions to come. You will need to have quota enabled on your subscription in order to use serverless GPUs. By default, all Microsoft Enterprise Agreement customers will have one quota. If additional quota is needed, please request it here. Note: In order to achieve the best performance with serverless GPUs, use an Azure Container Registry (ACR) with artifact streaming enabled for your image tag. Follow steps here to enable artifact streaming on your ACR. From the portal, you can select to enable GPUs for your Consumption app in the container tab when creating your Container App or your Container App Job. You can also add a new consumption GPU workload profile to your existing Container App environment through the workload profiles UX in portal or through the CLI commands for managing workload profiles. Deploy a sample Stable Diffusion app To try out serverless GPUs, you can use the stable diffusion image which is provided as a quickstart during the container app create experience: In the container tab select the Use quickstart image box. In the quickstart image dropdown, select GPU hello world container. If you wish to pull the GPU container image into your own ACR to enable artifact streaming for improved performance, or if you wish to manually enter the image, you can find the image at mcr.microsoft.com/k8se/gpu-quickstart:latest. For full steps on using your own image with serverless GPUs, see the tutorial on using serverless GPUs in Azure Container Apps. Learn more about serverless GPUs With serverless GPUs, Azure Container Apps now simplifies the development of your AI applications by providing scale-to-zero compute, pay-as you go pricing, reduced infrastructure management, and more. To learn more, visit: Using serverless GPUs in Azure Container Apps (preview) | Microsoft Learn Tutorial: Generate images using serverless GPUs in Azure Container Apps (preview) | Microsoft LearnNew Features in Azure Container Apps VS Code extension
👆 Install VS Code extension Summary of Major Changes New Managed Identity Support for connecting container apps to container registries. This is now the preferred method for securing these resources, provided you have sufficient privileges. New Container View: Introduced with several commands for easier editing of container images and environment variables. One-Click Deployment: Deploy to Container App... added to the top-level container app node. This supports deployments from a workspace project or container registry. To manage multiple applications in a workspace project or enable faster deployments with saved settings, use Deploy Project from Workspace. It can be accessed via the workspace view. Improved Activity Log Output: All major commands now include improved activity log outputs, making it easier to track and manage your activities. Quickstart Image for Container App Creation: The "Create container app..." command now initializes with a quickstart image, simplifying the setup process. New Commands and Enhancements Managed Identity support for new connections to container registries New command Deploy to Container App... found on the container app item. This one-click deploy command allows deploying from a workspace project or container registry while in single revision mode. New Container view under the container app item allows direct access to the container's image and environment variables. New command Edit Container Image... allows editing of container images without prompting to update environment variables. Environment Variable CRUD Commands: Multiple new commands for creating, reading, updating, and deleting environment variables. Convert Environment Variable to Secret: Quickly turn an environment variable into a container app secret with this new command. Changes and Improvements Command Create Container App... now always starts with a quickstart image. Renamed the Update Container Image... command to Edit Container.... This command is now found on the container item. When running Deploy Project from Workspace..., if remote environment variables conflict with saved settings, prompt for update. Add new envPath option useRemoteConfiguration. Deploying an image with the Docker extension now allows targeting specific revisions and containers. When deploying a new image to a container app, only show ingress prompt when more than the image tag is changed. Improved ACR selection dropdowns, providing better pick recommendations and sorting by resource group. Improved activity log outputs for major commands. Changed draft deploy prompt to be a quick pick instead of a pop-up window. We hope these new features and improvements will simplify deployments and make your Azure Container Apps experience even better. Stay tuned for more updates, and as always, we appreciate your feedback! Try out these new features today and let us know what you think! Your feedback is invaluable in helping us continue to improve and innovate. Azure Container Apps VS Code Extension Full changelog:See live data on Azure Container Apps with the Aspire dashboard
Azure Container Apps will be rolling out support this month for the new Aspire dashboard announced in .NET 8. This improvement makes it easier than ever for developers hosting on ACA to monitor their applications, identify abnormalities in their metrics, and debug errors. This blog post will tell you about the Aspire dashboard and why it can save product teams a great deal of money, stress, and development time. Then, we will walk through how to enable and access the dashboard for your project in ACA.Azure App Service Logging: How to Monitor Your Web Apps in Real-Time
As a developer, having visibility into the behavior of your applications is crucial to maintaining the reliability and performance of your software. Luckily, Azure App Service provides two powerful logging features to help you monitor your web apps in real-time: App Service Logs and Log Stream. In this blog post, we'll explore how to configure these features for both Windows and Linux Web Apps in Azure App Service.Unlock New AI and Cloud Potential with .NET 9 & Azure: Faster, Smarter, and Built for the Future
.NET 9, now available to developers, marks a significant milestone in the evolution of the .NET platform, pushing the boundaries of performance, cloud-native development, and AI integration. This release, shaped by contributions from over 9,000 community members worldwide, introduces thousands of improvements that set the stage for the future of application development. With seamless integration with Azure and a focus on cloud-native development and AI capabilities, .NET 9 empowers developers to build scalable, intelligent applications with unprecedented ease. Expanding Azure PaaS Support for .NET 9 With the release of .NET 9, a comprehensive range of Azure Platform as a Service (PaaS) offerings now fully support the platform’s new capabilities, including the latest .NET SDK for any Azure developer. This extensive support allows developers to build, deploy, and scale .NET 9 applications with optimal performance and adaptability on Azure. Additionally, developers can access a wealth of architecture references and sample solutions to guide them in creating high-performance .NET 9 applications on Azure’s powerful cloud services: Azure App Service: Run, manage, and scale .NET 9 web applications efficiently. Check out this blog to learn more about what's new in Azure App Service. Azure Functions: Leverage serverless computing to build event-driven .NET 9 applications with improved runtime capabilities. Azure Container Apps: Deploy microservices and containerized .NET 9 workloads with integrated observability. Azure Kubernetes Service (AKS): Run .NET 9 applications in a managed Kubernetes environment with expanded ARM64 support. Azure AI Services and Azure OpenAI Services: Integrate advanced AI and OpenAI capabilities directly into your .NET 9 applications. Azure API Management, Azure Logic Apps, Azure Cognitive Services, and Azure SignalR Service: Ensure seamless integration and scaling for .NET 9 solutions. These services provide developers with a robust platform to build high-performance, scalable, and cloud-native applications while leveraging Azure’s optimized environment for .NET. Streamlined Cloud-Native Development with .NET Aspire .NET Aspire is a game-changer for cloud-native applications, enabling developers to build distributed, production-ready solutions efficiently. Available in preview with .NET 9, Aspire streamlines app development, with cloud efficiency and observability at its core. The latest updates in Aspire include secure defaults, Azure Functions support, and enhanced container management. Key capabilities include: Optimized Azure Integrations: Aspire works seamlessly with Azure, enabling fast deployments, automated scaling, and consistent management of cloud-native applications. Easier Deployments to Azure Container Apps: Designed for containerized environments, .NET Aspire integrates with Azure Container Apps (ACA) to simplify the deployment process. Using the Azure Developer CLI (azd), developers can quickly provision and deploy .NET Aspire projects to ACA, with built-in support for Redis caching, application logging, and scalability. Built-In Observability: A real-time dashboard provides insights into logs, distributed traces, and metrics, enabling local and production monitoring with Azure Monitor. With these capabilities, .NET Aspire allows developers to deploy microservices and containerized applications effortlessly on ACA, streamlining the path from development to production in a fully managed, serverless environment. Integrating AI into .NET: A Seamless Experience In our ongoing effort to empower developers, we’ve made integrating AI into .NET applications simpler than ever. Our strategic partnerships, including collaborations with OpenAI, LlamaIndex, and Qdrant, have enriched the AI ecosystem and strengthened .NET’s capabilities. This year alone, usage of Azure OpenAI services has surged to nearly a billion API calls per month, illustrating the growing impact of AI-powered .NET applications. Real-World AI Solutions with .NET: .NET has been pivotal in driving AI innovations. From internal teams like Microsoft Copilot creating AI experiences with .NET Aspire to tools like GitHub Copilot, developed with .NET to enhance productivity in Visual Studio and VS Code, the platform showcases AI at its best. KPMG Clara is a prime example, developed to enhance audit quality and efficiency for 95,000 auditors worldwide. By leveraging .NET and scaling securely on Azure, KPMG implemented robust AI features aligned with strict industry standards, underscoring .NET and Azure as the backbone for high-performing, scalable AI solutions. Performance Enhancements in .NET 9: Raising the Bar for Azure Workloads .NET 9 introduces substantial performance upgrades with over 7,500 merged pull requests focused on speed and efficiency, ensuring .NET 9 applications run optimally on Azure. These improvements contribute to reduced cloud costs and provide a high-performance experience across Windows, Linux, and macOS. To see how significant these performance gains can be for cloud services, take a look at what past .NET upgrades achieved for Microsoft’s high-scale internal services: Bing achieved a major reduction in startup times, enhanced efficiency, and decreased latency across its high-performance search workflows. Microsoft Teams improved efficiency by 50%, reduced latency by 30–45%, and achieved up to 100% gains in CPU utilization for key services, resulting in faster user interactions. Microsoft Copilot and other AI-powered applications benefited from optimized runtime performance, enabling scalable, high-quality experiences for users. Upgrading to the latest .NET version offers similar benefits for cloud apps, optimizing both performance and cost-efficiency. For more information on updating your applications, check out the .NET Upgrade Assistant. For additional details on ASP.NET Core, .NET MAUI, NuGet, and more enhancements across the .NET platform, check out the full Announcing .NET 9 blog post. Conclusion: Your Path to the Future with .NET 9 and Azure .NET 9 isn’t just an upgrade—it’s a leap forward, combining cutting-edge AI integration, cloud-native development, and unparalleled performance. Paired with Azure’s scalability, these advancements provide a trusted, high-performance foundation for modern applications. Get started by downloading .NET 9 and exploring its features. Leverage .NET Aspire for streamlined cloud-native development, deploy scalable apps with Azure, and embrace new productivity enhancements to build for the future. For additional insights on ASP.NET, .NET MAUI, NuGet, and more, check out the full Announcing .NET 9 blog post. Explore the future of cloud-native and AI development with .NET 9 and Azure—your toolkit for creating the next generation of intelligent applications.
Connect Privately to Azure Front Door with Azure Container Apps
Azure Container Apps is a fully managed serverless container service that enables you to deploy and run containerized applications with per-second billing and autoscaling without having to manage infrastructure. The service also provides support for a number of enhanced networking capabilities to address security and compliance needs such as network security groups (NSGs), Azure Firewall, and more. Today, Azure Container Apps is excited to announce public preview for another key networking capability, private endpoints for workload profile environments. This feature allows customers to connect to their Container Apps environment using a private IP address in their Azure Virtual Network, thereby eliminating exposure to the public internet and securing access to their applications. With the introduction of private endpoints for workload profile environments, you can now also establish a direct connection from Azure Front Door to your Container Apps environment via Private Link. By enabling Private Link for an Azure Container Apps origin, customers benefit from an extra layer of security that further isolates their traffic from the public internet. Currently, you can configure this connectivity through CLI (portal support coming soon). In this post, we will do a brief overview of private endpoints on Azure Container Apps and the process of privately connecting it to Azure Front Door. Getting started with private endpoints on Azure Container Apps Private endpoints can be enabled either during the creation of a new environment or within an existing one. For new environments, you simply navigate to the Networking tab, disable public network access, and enable private endpoints. To manage the creation of private endpoints in an existing environment, you can use the new Networking blade, which is also in public preview. Since private endpoints use a private IP address, the endpoint for a container app is inaccessible through the public internet. This can be confirmed by the lack of connectivity when opening the application URL. If you prefer using CLI, you can find further guidance in enabling private endpoints at Use a private endpoint with an Azure Container Apps environment (preview). Adding container apps as a private origin for Azure Front Door With private endpoints, you can securely connect them to Azure Front Door through Private Link as well. The current process involves CLI commands that guide you in enabling an origin for Private Link and approving the private endpoint connection. Once approved, Azure Front Door assigns a private IP address from a managed regional private network, and you can verify the connectivity between your container app and the Azure Front Door. For a detailed tutorial, please navigate to Create a private link to an Azure Container App with Azure Front Door (preview). Troubleshooting Have trouble testing the private endpoints? After creating a private endpoint for a container app, you can build and deploy a virtual machine to test the private connection. With no public inbound ports, this virtual machine would be associated with the virtual network defined during creation of the private endpoint. After creating the virtual machine, you can connect via Bastion and verify the private connectivity. You may find outlined instructions at Verify the private endpoint connection. Conclusion The public preview of private endpoints and private connectivity to Azure Front Door for workload profile environments is a long-awaited feature in Azure Container Apps. We encourage you to implement private endpoints for enhanced security and look forward to your feedback on this experience at our GitHub page. Additional Resources To learn more, please visit the following links to official documentation: Networking in Azure Container Apps environment - Private Endpoints Use a private endpoint with an Azure Container Apps environment Create a private link to an Azure Container App with Azure Front Door (preview) What is a private endpoint? What is Azure Private Link?Easily deploy .NET apps to Azure Container Apps with default configuration for data protection
The Azure Container Apps and .NET team have made it easier than ever to deploy your .NET application by supporting automatic configuration for data protection. This support is currently available as an opt-in feature in the Container Apps API version 2024-02-02-preview. This blog post will discuss the feature and what it enables, how to determine if your application is correctly configured, and how to enable configuration for data protection across a variety of .NET versions.
