This is a visualization of numbers from 1 to 1,000,000, added in order in blocks of 1,000, located in the 2-D plane according to their prime factors:

The animation was created by John Williamson. The mathematical process begins by representing each integer as a vector of length 80,000: the first value is the number of times "2" is used in its prime factorization, the next for "3", and so on through the primes. Then all of those vectors together represent one million points in an 80,000-dimensional space, which is then reduced to two dimensions using a dimension-reducing algorithm. The interesting structure that results is partly an artifact of the algorithm, but also a results of the fractal nature of the primes on the number line.

That's all from the blog for this week. Have a great weekend, and we'll be back next week. See you then!

Artificial Intelligence holds major potential for healthcare, from predicting patient length of stay to diagnostic imaging, anti-fraud, and many more use cases. To be successful in using AI, healthcare needs solutions, not projects. Learn how you can close the gap to your AI in healthcare solution by accelerating your initiative using Microsoft Azure blueprints. 

To rapidly acquire new capabilities and implement new solutions, healthcare IT and developers can now take advantage of industry-specific Azure Blueprints. Blueprints include resources such as example code, test data, security, and compliance support. These are packages that include reference architectures, guidance, how-to guides and other documentation, and may also include executable code and sample test data built around a key use case of interest to healthcare organizations. Blueprints also contain components to support privacy, security, and compliance initiatives, including threat models, security controls, responsibility matrices, and compliance audit reports.

Using these blueprints, your healthcare IT team can quickly implement a new type of solution in your secure Azure cloud. With a blueprint, however, you get 50 percent to 90 percent of the end solution. Then, you can simply devote your efforts and resources to customizing the blueprint solution.

You can learn more by watching the Accelerating Artificial Intelligence (AI) in Healthcare Using Microsoft Azure Blueprints Webcast. This session is intended for healthcare provider, payer, pharmaceuticals, and life sciences organizations. Key roles include senior technical decision makers, IT Managers Cloud Architects, and developers.

Key take-aways:

• Opportunities for AI in healthcare
• Key decision points for AI in healthcare solutions including architecture, cost, resources, process
• AI in healthcare blueprints available for Microsoft Azure, and how to get started
• Opportunities to work with Microsoft partners to accelerate your AI in healthcare initiative using the blueprint

Register or watch Accelerating Artificial Intelligence (AI) in Healthcare Using Microsoft Azure Blueprints -- Part 1: Getting Started (AZR311PAL) on demand.

This blog post is co-authored by Xiaoyong Zhu, Nile Wilson (Microsoft AI CTO Office), Ben Cutler (Project Natick), and Lucas Joppa (Microsoft Chief Environmental Officer).

At Microsoft, we put our cloud and artificial intelligence (AI) tools in the hands of those working to solve global environmental challenges, through programs such as AI for Earth. We also use these same tools to understand our own interaction with the environment, such as the work being done in concert with Project Natick.

Project Natick seeks to understand the benefits and difficulties in deploying subsea datacenters worldwide; it is the world's first deployed underwater datacenter and it was designed with an emphasis on sustainability. Phase 2 extends the research accomplished in Phase 1 by deploying a full-scale datacenter module in the North Sea, powered by renewable energy. Project Natick uses AI to monitor the servers and other equipment for signs of failure and to identify any correlations between the environment and server longevity.

Because Project Natick operates like a standard land datacenter, the computers inside can be used for machine learning to provide AI to other applications, just as in any other Microsoft datacenter. We are also using AI to monitor the surrounding aquatic environment, as a first step to understanding what impact, if any, the datacenter may have.

Figure 1. Project Natick datacenter pre-submergence

Monitoring marine life using object detection

The Project Natick datacenter is equipped with various sensors to monitor server conditions and the environment, including two underwater cameras, which are available as live video streams (check out the livestream on the Project Natick homepage). These cameras allow us to monitor the surrounding environment from two fixed locations outside the datacenter in real time.

Figure 2. Live camera feed from Project Natick datacenter (Source: Project Natick homepage)

We want to count the marine life seen by the cameras. Manually counting the marine life in each frame in the video stream requires a significant amount of effort. To solve this, we can leverage object detection to automate the monitoring and counting of marine life.

Figure 3. From the live camera feed, we observe a variety of aquatic life, including left, ray; middle, fish; right, arrow worm

In each frame, we count the number of marine creatures. We model this as an object detection problem. Object detection combines the task of classification with localization, and outputs both a category and a set of coordinates representing the bounding box for each object detected in the image. This is illustrated in Figure 4.

Figure 4. Object detection tasks in computer vision. left, input image; right, object detection with bounding boxes

How to choose an object detection model

Over the past few years, many exciting deep learning approaches for object detection have emerged. Models such as Faster R-CNN use a two-stage procedure to first propose regions containing some object, followed by classification of the proposed region and adjusting the proposed bounding box. Using a one-stage approach, models such as You Only Look Once (YOLO) and Single Shot MultiBox Detector (SSD), or RetinaNet with focal loss, consider a fixed set of boxes for detection and skip the region proposal stage, which are usually faster compared with two-stage detectors.

To achieve real-time object detection for videos, we need to balance between speed and accuracy. From the video stream, we observed that there are only a few types of aquatic life that come within view—fish, arrow worms, and rays. The limited number of animal categories allows us to choose a relatively light-weight object detection model which can be run on CPUs.

By comparing the speed and accuracy of different deep learning model architectures, we chose to use SSD with MobileNet as our network architecture.

Figure 5. Object detection approaches (tradeoffs between accuracy and inference time). Marker shapes indicate meta-architecture and colors indicate feature extractor. Each (meta-architecture, feature extractor) pair corresponds to multiple points on this plot due to changing input sizes, stride, etc. (source)

An AI Oriented Architecture for environmental monitoring

AI Oriented Architecture (AOA) is a blueprint for enterprises to use AI to accelerate digital transformation. An AOA enables organizations to map a business solution to the set of AI tools, services and infrastructure that will enable them to realize the business solution. In this example, we use an AI Oriented Architecture to design a deep learning solution for environmental monitoring.

Figure 6 shows an AI Oriented Architecture for monitoring marine life near the underwater datacenter. We first save the streamed video file from Azure Media Service using OpenCV, then label the video frames using VoTT and put the labelled data in Azure Blob Storage. Once the dataset is labelled and placed in Azure Blob Storage, we start training an object detection model using Azure. After we have trained the model, we deploy the model to the Natick datacenter, so the model can run inference on the input stream directly. The result is then either posted to PowerBI or displayed directly in the UI for intuitive debugging. Each of these steps is discussed in the following sections.

Figure 6. AI Oriented Architecture for detecting underwater wildlife

The key ingredients of the environment monitoring solution include the following:

• Dataset
  • Labelling data using the Visual Object Tagging Tool (VoTT)
  • Azure Blob Storage to store the dataset for easy access during training and evaluation
• Tools
  • TensorFlow Object Detection API
• Azure
  • Azure GPU cluster, or the CPU cluster available in Project Natick Datacenter
• Development and deployment tools
  • Visual Studio Tools for AI, an extension to develop and debug models in the integrated development environment (IDE)

Labelling data for object detection

The first step is to label the video files. The video streams are publicly available (here and here), which can be saved to local mp4 files using OpenCV. To facilitate the labelling process, we then label the mp4 video files using the open source tool VoTT developed by Microsoft. VoTT is a commonly used tool built for labelling objects in videos.

For this problem, we scope it to monitor fish and arrow worms. We labelled 200 images in total for the two classes (arrow worms and fish), and the labelled data is available in the GitHub repository.

Figure 7. Sample image of the labelled file

Training an object detection model using Azure

We used TensorFlow to perform object detection. TensorFlow comes with the TensorFlow Object Detection API which has some built-in network architectures, making it easy to train a neural network to recognize underwater animals.

Because the dataset is small (200 images in total for arrow worms and fish), the problem is how to train an accurate enough object detector with limited labelled data and avoid overfitting. We train the object detector for 1,000 steps, initialized from COCO weights, with strong data augmentation such as flipping, color adjustment (including hue, brightness, contrast, and saturation), as well as bounding box jittering, to make sure the model can generalize well under most of the conditions.

We also use more anchor ratios, in particular 0.25:1 and 4:1, in addition to the regularly used anchor ratios (such as 2:1), to make sure the model can capture most of the animals. This is especially useful to capture arrow worms since they are long and narrow in shape.

The code and object detection configurations are available in this GitHub repository.

Figure 8. Training loss for the underwater creature detector

Deploying the model to the Project Natick datacenter

Another question we asked was - can we deploy the model to the Natick datacenter to monitor the wildlife teeming around the data center?

We chose to use CPUs to process the input videos and tested locally to make sure it works well. However, the default TensorFlow pre-built binary does not have optimizations such as AVX or FMA built-in to fully utilize modern CPUs. To better utilize the CPUs, we built the TensorFlow binary from source code, turning on all the optimization for Intel CPU by following Intel’s documentation. With all the optimization, we can increase the processing speed by 50 percent from around two frame per second to three frame per second. The build command is like below:

bazel build --config=mkl -c opt --copt=-mavx --copt=-mavx2 --copt=-mfma --copt=-mavx512f --copt=-mavx512pf --copt=-mavx512cd --copt=-mavx512er --copt="-DEIGEN_USE_VML"

//tensorflow/tools/pip_package:build_pip_package

Real-time environmental monitoring with Power BI

Environmental scientists and aquatic scientists may benefit from a more intuitive way of monitoring the statistics of the underwater datacenter, such that they can quickly gain insight as to what is going on, through powerful visualization via Power BI.

Power BI has a notion of real-time datasets which provides the ability to accept streamed data and update dashboards in real time. It is intuitive to call the REST API to post data to the Power BI dashboard with a few lines of code:

# REST API endpoint, given to you when you create an API streaming dataset
# Will be of the format: https://api.powerbi.com/beta/<tenant id>/datasets/< dataset id>/rows?key=<key id>
REST_API_URL = ' *** Your Push API URL goes here *** '
# ensure that timestamp string is formatted properly
now = datetime.strftime(datetime.now(), "%Y-%m-%dT%H:%M:%S%Z")
# data that we're sending to Power BI REST API
data = '[{{ "timestamp": "{0}", "fish_count": "{1}", "arrow_worm_count": "{2}" }}]'.format(now, fish_count, arrow_worm_count)
req = urllib2.Request(REST_API_URL, data)
response = urllib2.urlopen(req)

Because the animals may move quickly, we need to carefully balance between capturing data for many frames in short succession, sending to the Power BI dashboard, and consuming compute resources. We chose to push the analyzed data (for example, fish count) to Power BI three times per second to achieve this balance.

Figure 9. Power BI dashboard running together with the video frame. Bottom: GIF showing the E2E result

Summary

Monitoring the environmental impact is an important topic, and AI can help make this process more scalable, and automated. In this post, we explained how we developed a deep learning solution for environment monitoring near the underwater data center. In this solution, we show how to ingest and store the data, and train an underwater animal detector to detect the marine life seen by the cameras. The model is then deployed to the machines in the data center to monitor the marine life. At the same time, we also explored how to analyze the video streams and leverage Power BI’s streaming APIs to monitor the marine life over time.

If you have questions or comments, please leave a message on our GitHub repository.

We continue to expand the Azure Marketplace ecosystem. From July 16 to 31, 50 new offers successfully met the onboarding criteria and went live. See details of the new offers below:

Virtual Machines

	Active Directory Domain Controller 2016: This 2016 virtual machine comes preloaded with the Active Directory Domain Services role, DNS server role, and remote administration tools for AD, DNS, and the required PowerShell modules.
	Akamai Enterprise Application Access: Try a new and convenient alternative to traditional remote-access technologies, such as VPNs, RDP, and proxies. A cloud architecture closes inbound firewall ports while providing authenticated users access to only their specific apps.
	Amazon S3 API for Azure Blob / Multicloud Storage: Distribute and migrate data between multiple clouds with transparent S3-to-Azure API translation. Flexify.IO enables cloud-agnostic and multi-cloud deployments by combining storage spaces into a single virtual namespace.
	beekeeper fully automated patch management: beekeeper by Infront Consulting Group Ltd. is an innovative solution that automates patch management. Utilizing its workload engine, beekeeper automates pre- and post-patching tasks.
	BlueCat DNS Edge Service Point for Azure: Edge reduces your attack surface, detects malicious behavior, reduces the time needed to remediate breaches, and adds visibility and control to corporate networks under siege from an explosion of malware attacks that exploit DNS.
	centos 7 with joomla: Centos 7 php with joomla pre install.
	Corda Enterprise Single Node: Corda Enterprise by R3 is a commercial distribution of Corda software optimized to meet the demands of modern-day business. It includes a blockchain application firewall and cross-distribution and cross-version wire compatibility.
	Digital transformation platform: Looking for a platform to help you navigate digital transformation while retaining familiar Microsoft technologies? Mavim offers infinitely scalable software that facilitates the creation of a dynamic, virtual representation of your organization.
	Fusio open source API: Fusio by tunnelbiz.com is an open-source API management platform to help you build and manage REST APIs. Fusio provides you with the tools to quickly build an API from different data sources and create customized responses.
	GigaSECURE Cloud 5.4.00 - Hourly (100 pack): GigaSECURE Cloud by Gigamon Inc. delivers intelligent network traffic visibility for workloads running in Azure and enables increased security, operational efficiency, and scale across virtual networks (VNets).
	GoAnywhere MFT for Linux: HelpSystems' GoAnywhere MFT is a flexible managed file-transfer solution that automates and secures file transfers using a centralized, enterprise-level approach with support for all popular file-transfer and encryption protocols.
	Grafana Certified by Bitnami: Grafana is an open-source analytics and monitoring dashboard for more than 40 data sources, including Graphite, Elasticsearch, Prometheus, MySQL, and PostgreSQL.
	H2O Driverless AI: This artificial intelligence platform automates some of the most difficult data science and machine learning workflows, such as feature engineering, model validation, model tuning, model selection, and model deployment.
	Intellicus BI Server (25 Users): Intellicus BI Server is an enterprise reporting and business intelligence platform with drag-and-drop interactive capability to pull KPIs to personalized dashboards and monitor the business parameters on a browser or a mobile device.
	Intellicus BI Server (50 Users): Intellicus BI Server is an enterprise reporting and business intelligence platform with drag-and-drop interactive capability to pull KPIs to personalized dashboards and monitor the business parameters on a browser or a mobile device.
	Microsoft Web Application Proxy - WAP 2016 Server: Deploy a Microsoft Web Application Proxy 2016 server preloaded with the ADFS WAP role and ADFS WAP PowerShell modules alongside the prerequisites for you to build an ADFS farm or add to an existing one.
	Project Tools Product Suite: Profecia IT (Pty) Ltd.'s Project Tools Product Suite is an automated reporting tool that collects and captures data via the mobile application, then completes your report automatically while your data is being captured.
	Qualys Virtual Firewall Appliance: The Qualys Virtual Firewall Appliance provides a continuous view of security events and compliance, putting a spotlight on your Azure infrastructure. It acts as an extension to the Qualys Cloud Platform.
	Ripple Development & Training Suit(Techlatest.net): If you're looking to get started with Ripple blockchain development and want to have an out-of-box environment up and running in minutes, this virtual machine is for you.
	RSA NetWitness Suite 11.1: RSA NetWitness 11.1 strengthens the RSA NetWitness Evolved SIEM offering through deeper and extended visibility and threat intelligence to help increase productivity.
	Secured Nginx on Ubuntu 16.04 LTS: Nginx can be deployed to serve dynamic HTTP content on the network using FastCGI, SCGI handlers for scripts, WSGI application servers, or Phusion Passenger modules, and it can serve as a software load balancer.
	secured-mariadb-on-ubuntu-16-04: MariaDB turns data into structured information in a wide array of applications, ranging from banking to websites. It is an enhanced, drop-in replacement for MySQL.
	SharePoint Term Extractor: DIQA Projektmanagement GmbH's SharePoint Term Extractor attaches to one or more SharePoint libraries and automatically extracts relevant terms for contained documents in common file formats. You can then use the terms to tag documents.
	SoftEther VPN Server Windows 2016: Quickly deploy SoftEther VPN server on Windows 2016. SoftEther VPN is an alternative to OpenVPN and Microsoft's VPN servers, and it supports Microsoft SSTP VPN for Windows.
	ThingsBoard Professional Edition with Cassandra: The Professional Edition is a closed-source version of the ThingsBoard IoT platform. It features several value-add features, including platform integrations, device and asset groups, a scheduler, and advanced white-labeling.

Web Applications

	Archive2Azure - Intelligent Information Management: Archive2Azure is an Azure-powered platform for modernizing your data estate, delivering long-term, secure, and cost-effective retention and management of organizational data.
	Barracuda WAF-as-a-Service: This cloud-delivered solution enables anyone to protect web apps against the OWASP’s top 10 threats, distributed denial of service attacks, zero-day attacks, and more in just minutes. Barracuda’s security can be configured in just five steps.
	fedora linux: fedora linux server by tunnelbiz.com is an operating system with the latest open-source technology.
	Gieom: Gieom helps define controls in your manual processes to manage your business risks. It supplies information about each risk factor, assesses its impact on a scale of 1-10, lists the probability of it happening, and provides a mitigation plan.
	Kyligence Enterprise: Powered by Apache Kylin, Kyligence Enterprise empowers business analysts to architect business intelligence on Hadoop with industry-standard data warehouse and BI methodology.
	Vormetric Data Security Manager v6.1.0: The Vormetric Data Security Manager (DSM) from Thales eSecurity serves as the center point for multi-cloud advanced encryption. You control encryption keys and policies.

Consulting Services

	Advanced Azure DevOps: 3 Day Workshop: In this hands-on course from Opsgility LLC, students will learn about automation and configuration management for Azure Infrastructure-as-a-Service and Platform-as-a-Service using the Azure Resource Manager.
	Azure Data Security Healthcheck: 2-Wk Workshop: The Data Security Healthcheck by Coeo Ltd. will identify and review data assets and end points, as well as potential attack vectors and vulnerabilities, recommending strategies and solutions to mitigate these risks.
	Azure EDI Cloud Migration & Integration: 5-Day PoC: EDI in the cloud is supported by Azure Integration Services, requiring no on-premises footprint, servers, or dedicated administrative staff. This proof of concept lays the foundation for B2B apps using EDI.
	Azure Enterprise Architecture: 1-Day Workshop: This on-site technical workshop by igroup will gather requirements and focus on what infrastructure and/or services are required to deploy an existing software application.
	Azure Machine Learning (ML): 2 Day Workshop: This course by Opsgility LLC explores Azure Machine Learning for students who are either new to machine learning or new to Microsoft Azure. This course is designed for data professionals and data scientists.
	Azure Migration & Integration: FREE 1-Day Briefing: TwoConnect's Azure Integration Services (AIS) migration briefing helps guide you in your effort to develop a plan to migrate your on-premises apps and integrations to the cloud.
	Azure Migration: 7-Day Assessment: Get an overview of your infrastructure environment, including dependencies and performance. Sentia will provide a recommended model of operations, securing a seamless migration and avoiding excess costs.
	Big Data and Machine Learning: 2 Day Workshop: This Azure Big Data and machine learning bootcamp by Opsgility LLC is designed to give students a clear architectural understanding of the application of Big Data patterns in Azure.
	BizTalk to Azure Integration: 3-Day Assessment: Migrating BizTalk apps to Azure Integration Services (AIS) and other Azure services is a multi-step process that begins with an expert analysis of existing apps.
	BizTalk VM to Azure VM: 2-Day Assessment: Moving virtual machines from on-premises to Azure can lower costs associated with BizTalk Server infrastructure. TwoConnect's BizTalk VM to Azure VM assessment can create a migration plan for your VM situation.
	Carbonite Endpoint Protection - Azure 1000 Bundle: Our team will deploy our Platform-as-a-Service offering onto a customer's Azure Enterprise Agreement, which will allow the customer to back up endpoints to Azure. Our team will also provide training.
	Cognitive and AI: 2 Day Workshop: This course by Opsgility LLC introduces you to Microsoft Cognitive Services and its features, including search, audio, computer vision, and language processing services. This course is designed for IT developers.
	DevOps in Azure: 2 Day Workshop: In this hands-on course by Opsgility LLC, students are introduced to fundamental DevOps concepts, as well as core technologies and services in Azure. This course is designed for IT professionals, developers, and DevOps engineers.
	InsurHUB for IFRS 17: 4-Hour Workshop: BDO’s team of experts will detail how the cloud-based solution InsurHUB can help your organization address IFRS 17 compliance using Microsoft Azure. IFRS 17 concerns financial reporting for insurance companies in Canada.
	Migrate to Azure Stack - Windows 1Tb (4-Wks): Our team will ensure that all aspects of your Windows migration project is a success. We utilize Carbonite Migrate technology for efficient migration of Windows workloads to Azure Stack with near-zero downtime.
	NetX- Veritas NetBackup: 2-Day Assessment: NetX has developed a Veritas NetBackup assessment service that evaluates the health of a NetBackup environment and includes an upgrade path to the latest version, as well as cloud readiness.
	On-Demand Training and Lab: 4-Wk Workshop: This training in the SkillMeUp series by Opsgility LLC provides on-demand courses and live lab environments for an immersive learning experience. SkillMeUp caters to nontechnical learners as well as to IT pros.
	Public Service to Azure API: 3-Day Assessment: Host your public-facing services on Azure to bring tremendous benefits in availability, security, and cost. TwoConnect's assessment includes a service review, a back-end review, and a migration plan.
	SaaS Integration with Azure Logic Apps: 3-Day POC: Azure Integration Services (AIS) makes it easy to integrate with any Software-as-a-Service app. This proof of concept by TwoConnect will enable you to show the benefits of AIS and other Azure services.

The Integration Runtime (IR) is the compute infrastructure used by Azure Data Factory to provide data integration capabilities across different network environments. If you need to perform data integration and orchestration securely in a private network environment, which does not have a direct line-of-sight from the public cloud environment, you can install a self-hosted IR on premises behind your corporate firewall, or inside a virtual private network.

Untill now, you were required to create at least one such compute infrastructure in every Data Factory by design for hybrid and on-premise data integration capabilities. Which implies if you have ten such data factories being used by different project teams to access on-premise data stores and orchestrate inside VNet, you would have to create ten self-hosted IR infrastructures, adding additional cost and management concerns to the IT teams.

With the new capability of self-hosted IR sharing, you can share the same self-hosted IR infrastructure across data factories. This lets you reuse the same highly available and scalable self-hosted IR infrastructure from different data factories within the same Azure Active Directory tenant. We are introducing a new concept of a Linked self-hosted IR which references another self-hosted IR infrastructure. This does not introduce any change in the way you currently author pipelines in Data Factory and works the same way as the self-hosted IR does. So once you have created a Linked self-hosted IR, you can start using the same way as you would use a self-hosted IR in the Linked Services.

New Self-hosted IR Terminologies (sub-types):

• Shared IR – The original self-hosted IR which is running on a physical infrastructure. By default, self-hosted IR do not have sub-type, but after sharing is enabled on a self-hosted IR, it then carries a sub-type as shared denoting that it is shared with other data factories.
• Linked IR – The IR which references another Shared IR. This is a logical IR and uses the infrastructure of another self-hosted IR (shared).

High-level architecture outlining the Self-hosted IR sharing mechanism across data factories:

Authoring/ creating a Linked self-hosted IR

Reference the step-by-step guide for sharing a self-hosted IR with multiple data factories.

References:

• Create a self-hosted IR infrastructure using Azure Resource Manager template on Azure VM
• Create a highly available and scalable self-hosted IR cluster
• Tutorial – Copy data from an on-premises SQL Server database to Azure Blob storage using self-hosted IR
• Security considerations while hybrid data movement involving self-hosted IR

Now in preview

Reduce your exposure to brute force attacks from the virtual machine blade - One way to reduce exposure to an attack is to limit the amount of time that a port on your virtual machine is open. Ports only need to be open for a limited amount of time for you to perform management or maintenance tasks. Just-In-Time VM Access helps you control the time that the ports on your virtual machines are open. It leverages network security group (NSG) rules to enforce a secure configuration and access pattern.

Respond to threats faster with Security Center’s Confidence Score - Azure Security Center provides you with visibility across all your resources running in Azure and alerts you of potential or detected issues. Security Center can help your team triage and prioritize alerts with a new capability called Confidence Score. The Confidence Score automatically investigates alerts by applying industry best practices, intelligent algorithms, and processes used by analysts to determine whether a threat is legitimate and provides you with meaningful insights.

Tuesdays with Corey

Now generally available

DPDK (Data Plane Development Kit) for Linux VMs now generally available - Data Plane Development Kit (DPDK) for Azure Linux Virtual Machines (VMs) offers a fast user space packet processing framework for performance intensive applications that bypass the VM’s kernel network stack. DPDK provides a key performance differentiation in driving network function virtualization implementations. Customers in Azure can now use DPDK capabilities running in Linux VMs with multiple Linux OS distributions (Ubuntu, RHEL, CentOS and SLES) to achieve higher packets per second (PPS).

Azure SQL Data Warehouse Gen2 now generally available in France and Australia - Azure SQL Data Warehouse (Azure SQL DW) is a fast, flexible, and secure analytics platform offering you a SQL-based view across data. It is elastic, enabling you to provision a cloud data warehouse and scale to terabytes in minutes. Azure SQL DW Gen2 brings the best of Microsoft software and hardware innovations to dramatically improve query performance and concurrency. Compute Optimized Gen2 tier is now available in 22 regions.

Azure Friday

News and updates

Multi-member consortium support with Azure Blockchain Workbench 1.3.0 - Continuing a monthly release cadence, Azure Blockchain Workbench 1.3.0 is now available. This release offers faster and more reliable deployment, better transaction reliability, ability to deploy Workbench in a multi-member Ethereum PoA consortium, simpler pre-deployment script for AAD, and sample code and a tool for working with the Workbench API.

Hardening the security of Azure IoT Edge - The Azure IoT Edge security manager is a well-bounded security core for protecting the IoT Edge device and all its components by abstracting the secure silicon hardware. It is the focal point for security hardening and provides technology integration point to original device manufacturers (OEM). The IoT Edge security manager in essence comprises software working in conjunction with secure silicon hardware where available and enabled to help deliver the highest security assurances possible.

Public Environment Repository in Labs - We're releasing a public repository of Azure Resource Manager templates for each lab. You can use the repository to create environments without having to connect to an external GitHub source by yourself. The repository includes frequently used templates such as Azure Web Apps, Service Fabric clusters, and developer SharePoint farm environments.

Speech Services August 2018 update - Announces the release of another update to the Cognitive Services Speech SDK (version 0.6.0). With this release, we have added the support for Java on Windows 10 (x64) and Linux (x64). We are also extending the support for .NET Standard 2.0 to the Linux platform. The sample section of the SDK has been updated with samples showcasing the use of the newly supported languages. There are also changes that impact the Speech Devices SDK.

Cross-subscription disaster recovery for Azure virtual machines - Announces cross-subscription disaster recovery (DR) support for Azure virtual machines using Azure Site Recovery (ASR). You can now configure DR for Azure IaaS applications to a different subscription with in the same Azure Active Directory tenant. Now you can replicate your virtual machines to a different Azure region of your choice within a geographical cluster across subscriptions, which will help you meet the business continuity and disaster recover requirements for your IaaS applications without altering subscription topology of your Azure environment. Disaster recovery between Azure regions is available in all Azure regions where ASR is available.

Additional news and updates

• Managed instance general purpose name changes
• Migrate projects to the Inheritance process model: VSTS Sprint 139 Update
• Azure IoT Edge 1.0.1 release
• Data Factory supports service principal and MSI authentication for Azure Blob connectors

Several updates support improved experiences with Azure HDInsight, including:

• Azure HDInsight is now available in South India
• A_V2 series VMs are available in Azure HDInsight
• Kafka 1.1 support on Azure HDInsight
• G-series VMs are available in Azure HDInsight

The Azure Podcast

Azure tips & tricks

Technical content and training

Migrate Windows Server 2008 to Azure with Azure Site Recovery - Azure Site Recovery lets you easily migrate your Windows Server 2008 machines including the operating system, data and applications on it to Azure. All you need to do is perform a few basic setup steps, create storage accounts in your Azure subscription, and then get started with Azure Site Recovery by replicating servers to your storage accounts. Azure Site Recovery orchestrates the replication of data and lets you migrate replicating servers to Azure when you are ready. You can use Azure Site Recovery to migrate your servers running on VMware virtual machines, Hyper-V or physical servers.

Azure Block Blob Storage Backup - Azure Blob Storage is Microsoft's massively scalable cloud object store. Blob Storage is ideal for storing any unstructured data such as images, documents and other file types. Although Blob storage supports replication out-of-box, it's important to understand that the replication of data does not protect against application errors. In this blog post, Hemant Kathuria outlines a backup solution that you can use to perform weekly full and daily incremental back-ups of storage accounts containing block blobs for any create, replace, and delete operations. The solution also walks through storage account recovery should it be required.

Logic Apps, Flow connectors will make Automating Video Indexer simpler than ever - Video Indexer recently released a new and improved Video Indexer V2 API. This RESTful API supports both server-to-server and client-to-server communication and enables Video Indexer users to integrate video and audio insights easily into their application logic, unlocking new experiences and monetization opportunities. To make the integration even easier, we also added new Logic Apps and Flow connectors that are compatible with the new API. Learn how to get started quickly with the new connectors using Microsoft Flow templates that use the new connectors to automate extraction of insights from videos.

WebJobs in Azure with .NET Core 2.1 - A WebJob is a program running in the background of an App Service. It runs in the same context as your web app at no additional cost. Creating a WebJob in .NET Core isn't hard, but you have to know some tricks, especially if you want to use some .NET Core goodies like logging and DI. In this post, Sander Rossel shows how to build a WebJob using .NET Core 2.1 and release it to Azure using Visual Studio, the Azure portal, and VSTS.

Azure Machine Learning in plain English - Data scientist and author Siraj Raval recently released a 12-minute video overview of Azure Machine Learning. The video included in this post begins with a overview of cloud computing and Microsoft Azure generally, before getting into the details of some specific Azure services for machine learning.

//DevTalk : App Service – SSL Settings Revamp - App Service SSL settings experience is one of the most used features in App Service. Based on customer feedback, we made several changes to the user experience to address and improve the overall experience of managing certificates in Azure App Service. Check out this post to learn about improvements to editing SSL bindings, private certificate details, uploading certificates, and adding public certificates.

Azure Content Spotlight – API Management Suite – VSTS extension v2.0 - This spotlight is for a VSTS extension: the API Management Suite. The purpose of the extension to VSTS is to bring API Management into the release lifecycle allowing you to do many of the activities supported in the Azure Portal. Also included is a security checker to ensure all released endpoints are secure. The source is available on GitHub.

Operationalize Your Deep Learning Models with Azure CLI 2.0 - Francesca Lazzeri, AI & Machine Learning Scientist at Microsoft, shows how to deploy your deep learning models on a Kubernetes cluster as a web service using Azure Command-Line Interface (Azure CLI) 2.0. This approach simplifies the model deployment process by using a set of Azure ML CLI commands.

AI Show

Customers and partners

Azure Marketplace consulting offers: May - The Azure Marketplace is the premier destination for all your Azure software and consulting needs. In May, twenty-six consulting offers successfully met the onboarding criteria and went live, including: App Migration to Azure 10-Day Workshop from Imaginet and Cloud Governance: 3-Wk Assessment from Cloudneeti.

The IoT Show

Industries

Driving industry transformation with Azure – Getting started – Edition 1 - Through dedicated industry resources from Microsoft and premier partners, new solutions, content, and guidance are released almost daily. This first post in what promises to be a monthly series aggregates a series of the newest resources focused on how Azure can address common challenges and drive new opportunities in a variety of industries.

Expanded Azure Blueprint for FFIEC compliant workloads - Announces the general availability of the expanded Blueprint for Federal Financial Institution Examination Council (FFIEC) regulated workloads. As more financial services customers moving to the Azure cloud platform, this expanded Blueprint explains how to deploy four different reference architectures in a secure and compliant way. It also takes the guesswork out of figuring out what security controls Microsoft implements on your behalf when you build on Azure, and how to implement the customer-responsible security controls.

A Cloud Guru's Azure This Week

Being a working parent of two young children, I try to limit how much time I spend on household errands. I am one of those shoppers who has become conditioned to shopping based on convenience and ease. Availability of the products I want, and need must be available to me via all channels I shop — always! There is nothing more frustrating than shopping online to have my order cancelled because it can’t be fulfilled or shopping in store and finding the shelf empty. Sometimes I can delay my purchase. But if not, I either look for an alternative product or I’ll take my business to another retailer. Either way, it means I’m taking my dollars elsewhere, and both the local retailer and consumer brand lose a sale and potentially long-term relationship should out-of-stock be a regular occurrence.

Advanced analytics can solve out-of-stock challenges

An improved SKU assortment using advanced analytics to more closely monitor, predict and provide a course of action for out-of-stocks may prevent this experience. Today, we can solve for this scenario and like scenarios by developing algorithms that provide predictive insights that optimize available SKUs, tailoring assortments by store to ensure products are stocked to meet consumer demand.

An advanced analytics solution must be able to handle millions of SKUs and segment data into detailed comparisons. The outcome is the ability to maximize sales at every store by tuning product assortments using advanced analytics and visualization tools to enable insights. Doing this successfully could result in an estimated 5-10 percent sales increase.

Azure offers several out-of-the box services that can be used to build a scalable analytics solution that is cost effective and comprehensive. And if developing a solution is not a viable option, Microsoft works with partners such as Neal Analytics who have proven capabilities solving this business challenge at scale.

Assortment Optimization Solution

How machine learning is applied to the out-of-stock example

To determine how to solve out-of-stocks with a SKU assortment optimization solution, read the Inventory optimization through SKU Assortment + machine learning use case. This document provides options for solving the out-of-stock challenge and a solution overview leveraging Azure Services, including an approach by Neal Analytics, Microsoft 2017 Global Partner of the Year for business analytics. 

I post regularly about new developments on social media.  If you would like to follow me you can find me on Linkedin and Twitter.

Hello VLDB attendees!

Welcome to Rio De Janeiro. I wanted to take this opportunity to share with you some of the exciting work in data that’s going on in the Azure Data team at Microsoft, and to invite you to take a closer look.

Microsoft has long been a leader in database management with SQL Server, recognized as the top DBMS by Gartner for the past three years in a row. The emergence of the cloud and edge as the new frontiers for computing, and thus data management, is an exciting direction—data is now dispersed within and beyond the enterprise, on-premises, on-cloud, and on edge devices, and we must enable intelligent analysis, transactions, and responsible governance for all data everywhere, from the moment it is created to the moment it is deleted, through the entire life-cycle of ingestion, updates, exploration, data prep, analysis, serving, and archival.

These trends require us to fundamentally re-think data management. Transactional replication can span continents. Data is not just relational. Interactive, real-time, and streaming applications with enterprise level SLAs are becoming common. Machine learning is a foundational analytic task and must be supported while ensuring that all data governance policies are enforced, taking full advantage of advances in deep learning and hardware acceleration via FPGAs and GPUs. Microsoft is a very data-driven company, and to support product teams such as Bing, Office, Skype, Windows, and Xbox, the Azure Data team operates some of the world’s largest data services for our internal customers. This grounds our thinking about how data management is changing, through close collaborations with some of the most sophisticated application developers on the planet. Of course, even in a company like Microsoft, the majority of data owners and users are domain experts, not database experts. This means that even though the underlying complexity of data management is growing rapidly, we need to greatly simplify how users deal with their data. Indeed, a large cloud database service contains millions of customer databases, and requires us to handle many of the tasks previously handled by database administrators.

We are excited about the opportunity to re-imagine data management. We are making broad and deep investments in SQL Server and open source technologies, in Azure data services that leverage them, as well as in new built-for-cloud technologies. We have an ambitious vision of the future of data management that embraces Data Lakes and NoSQL, on-premises, in the cloud, and on edge devices. There has never been a better time to be part of database systems innovation at Microsoft, and we invite you to explore the opportunities to be part of our team.

This is an exciting time in our industry with many companies competing for talent and customers, and as you consider options, we want to highlight how Microsoft is differentiated in several respects. First, we have a unique combination of a world-class data management ecosystem in SQL Server and a leading public cloud in Azure. Second, our culture puts customers first with a commitment to bringing them the best of open source technologies alongside the best of Microsoft. Third, we have a deep commitment to innovation. Product teams collaborate closely with research and advanced development groups at Cloud Information Services Lab, Gray Systems Lab, and Microsoft Research to go farther faster, and to maintain strong ties with the research community.

In this blog, I’ve listed the many services and ongoing work in the Azure Data group at Microsoft, together with links that will give you a closer look. I hope you will find these of interest.

Have a great VLDB conference!

Rohan Kumar

Corporate Vice President, Azure Data
________________________________________

Azure Data blog posts

The Microsoft data platform continues momentum for cloud-scale innovation and migration

Azure data blog posts by Rohan Kumar

SQL Server

Industry leading database management system, now available on Linux/Docker and Windows, on-premises and in the cloud.

The SQL Server blog

SQL Server 2017

Azure Cosmos DB: The industry’s first globally-distributed, multi-model database service

Azure Cosmos DB is the first globally-distributed data service that lets you elastically scale throughput and storage across any number of geographical regions while guaranteeing low latency, high availability, and consistency – backed by the most comprehensive SLAs in the industry. Azure Cosmos DB is built to power today’s IoT and mobile apps, and tomorrow’s AI-hungry future.

It is the first cloud database to natively support a multitude of data models and popular query APIs, is built on a novel database engine capable of ingesting sustained volumes of data, and provides blazing-fast queries – all without having to deal with schema or index management. And it is the first cloud database to offer five well-defined consistency models, so you can choose just the right one for your app.

Azure Cosmos DB: The industry's first globally-distributed, multi-model database service

Azure Data Lake Analytics - An on-demand analytics job service to power intelligent action

Easily develop and run massively parallel data transformation and processing programs in U-SQL, R, Python, and .NET over petabytes of data. With no infrastructure to manage, you can process data on demand, scale instantly, and only pay per job. There is no infrastructure to worry about because there are no servers, virtual machines, or clusters to wait for, manage, or tune. Instantly scale the processing power for any job.

Azure Data Lake Analytics

Azure Data Catalog – Find, understand, and govern data

Companies collectively own Exabytes of data across hundreds of billions of streams, files, tables, reports, spreadsheets, VMs, etc. But for the most part, companies don't know where their data is, what's in it, how it's being used, or if it's secure. Our job is to fix that. We are building an automated infrastructure to find and classify any form of data anywhere it lives, from on-premises to cloud, figure out what the data contains, and how it should be managed/protected. Our global scale infrastructure will track all of this data and provide a search engine to make the data discoverable and easily re-usable. From AI to distributed systems we are using cutting edge technologies to make data useful.

Azure Data Factory – Managed, hybrid data integration service at scale

Create, schedule, and manage your data integration at scale. Work with data wherever it lives, in the cloud or on-premises, with enterprise-grade security. Accelerate your data integration projects by taking advantage of over 70 available data source connectors. Use the graphical user interface to build and manage your data pipelines. Transform raw data into finished, shaped data ready for consumption by business intelligence tools or custom applications. Easily lift your SQL Server Integration Services (SSIS) packages to Azure, and let Azure Data Factory manage your resources so you can increase productivity and lower total cost of ownership (TCO).

Azure Data Factory

Azure HDInsight – Managed cluster service for the full spectrum of Hadoop and Spark

Azure HDInsight is a fully-managed cluster service that makes it easy, fast, and cost-effective to process massive amounts of data. Use popular open-source frameworks such as Hadoop, Spark, Hive, LLAP, Kafka, Storm, ML Services, and more. Azure HDInsight enables a broad range of scenarios such as ETL, Data Warehousing, Machine Learning, IoT, and more. A cost-effective service that is powerful and reliable. Pay only for what you use. Create clusters on demand, then scale them up or down. Decoupled compute and storage provide better performance and flexibility.

Azure HDInsight

Azure SQL Database - The intelligent relational cloud database service

The world’s first intelligent database service that learns and adapts with your application, enabling you to dynamically maximize performance with very little effort on your part. Working around the clock to learn, profile, and detect anomalous database activities, Threat Detection identifies potential threats to the database, and like an airplane’s flight data recorder, Query Store collects detailed historical information about all queries, greatly simplifying performance forensics by reducing the time to diagnose and resolve issues.

Azure SQL Database

Adaptive query processing support for Azure SQL Database

Improved Automatic Tuning boosts your Azure SQL Database performance

Query Store: A flight data recorder for your database

Azure SQL Data Warehouse - Fast, flexible, and secure analytics platform

A fast, fully managed, elastic, petabyte-scale cloud data warehouse. Azure SQL Data Warehouse (SQL DW) lets you independently scale compute and storage, while pausing and resuming your data warehouse within minutes through a distributed processing architecture designed for the cloud. Seamlessly create your hub for analytics along with native connectivity with data integration and visualization services, all while using your existing SQL and BI skills. Through PolyBase, Azure Data Warehouse brings data lake data into the warehouse with support for rich queries over files and unstructured data.

Azure SQL Data Warehouse

Blazing fast data warehousing with Azure SQL Data Warehouse

Azure SQL Database Threat Detection, your built-in security expert

Azure SQL Data Warehouse now generally available in all Azure regions worldwide

Azure Stream Analytics - A serverless, real-time analytics service to power intelligent action

Easily develop and run massively parallel real-time analytics on multiple IoT or non-IoT streams of data using a simple SQL-like language. Use custom code for advanced scenarios. With no infrastructure to manage, you can process data on-demand, scale instantly, and only pay per job. Azure Stream Analytics seamlessly integrates with Azure IoT Hub and Azure IoT Suite. Azure Stream Analytics is also available on Azure IoT Edge enabling near-real-time analytical intelligence closer to IoT devices so that they can unlock the full value of device-generated data.

Azure Stream Analytics

Gray Systems Lab (GSL) and Cloud and Information Services Lab (CISL)

The Azure Data Office of the CTO is the home of the Gray Systems Lab (GSL) and the Cloud and Information Services Lab (CISL). These are applied research groups, employing scientists and engineers focusing on everything data, from SQL Server in the cloud to massive-scale distributed systems for Big Data, to hardware-accelerated data processing to self-healing streaming solutions. The labs were founded in 2008 and 2012 respectively, have since produced 70+ papers in top database and system conferences, have filed numerous patents, and are continuously engaged in deep academic collaborations, through internships and sponsorship of academic projects. This research focus is matched with an equally strong commitment to open-source (with several committers in Apache projects who together contributed over 500K LOC to open-source), and continuous and deep engagement with product teams.

Strong product partnerships provide an invaluable path for innovation to affect the real world—the labs’ innovations today govern hundreds of thousands of servers in our Big Data infrastructure, and ship with several cloud and on-premises products. Microsoft’s cloud-first strategy gives researchers in our group a unique vantage point, where PBs of telemetry data and first-party workloads make every step of our innovation process principled and data-driven. The labs have locations in Microsoft’s Redmond and Silicon Valley campuses, as well as in the UW-Madison campus. To hear more, please contact Carlo Curino at carlo.curino@microsoft.com or Alan Halverson at alanhal@microsoft.com.

User interface design process involves a lot a creativity that starts on a whiteboard where designers share ideas. Once a design is drawn, it is usually captured within a photograph and manually translated into some working HTML wireframe to play within a web browser. This takes efforts and delays the design process. What if a design is refactored on the whiteboard and the browser reflects changes instantly? In that sense, by the end of the session there is a resulting prototype validated between the designer, developer, and customer. Introducing Sketch2Code, a web based solution that uses AI to transform a handwritten user interface design from a picture to a valid HTML markup code.

Let’s understand the process of transforming handwritten image to HTML using Sketch2Code in more details.

• First the user uploads an image through the website.
• A custom vision model predicts what HTML elements are present in the image and their location.
• A handwritten text recognition service reads the text inside the predicted elements.
• A layout algorithm uses the spatial information from all the bounding boxes of the predicted elements to generate a grid structure that accommodates all.
• An HTML generation engine uses all these pieces of information to generate an HTML markup code reflecting the result.

Below is the the application workflow:

The Sketch2Code uses the following elements:

• A Microsoft Custom Vision Model: This model has been trained with images of different handwritten designs tagging the information of most common HTML elements like buttons, text box, and images.
• A Microsoft Computer Vision Service: To identify the text written into a design element a Computer Vision Service is used.
• An Azure Blob Storage: All steps involved in the HTML generation process are stored, including the original image, prediction results and layout grouping information.
• An Azure Function: Serves as the backend entry point that coordinates the generation process by interacting with all the services.
• An Azure website: User font-end to enable uploading a new design and see the generated HTML results.

The above elements form the architecture as follows:

You can find the code, solution development process, and all other details on GitHub. Sketch2Code is developed in collaboration with Kabel and Spike Techniques.

We hope this post helps you get started with AI and motivates you to become an AI developer.

Tara

Endpoint Routing in 2.2

What is it?

We’re making a big investment in routing starting in 2.2 to make it interoperate more seamlessly with middleware. For 2.2 this will start with us making a few changes to the routing model, and adding some minor features. In 3.0 the plan is to introduce a model where routing and middleware operate together naturally. This post will focus on the 2.2 improvements, we’ll discuss 3.0 a bit further in the future.

So, without further ado, here are some changes coming to routing in 2.2.

How to use it?

The new routing features will be on by default for 2.2 applications using MVC. UseMvc and related methods with the 2.2 compatibility version will enable the new ‘Endpoint Routing’ feature set. Existing conventional routes (using MapRoute) or attribute routes will be mapped into the new system.

public void ConfigureServices(IServiceProvider services)
{
    ...
    
    services.AddMvc().SetCompatibilityVersion(CompatibilityVersion.Version_2_2);
}

public void Configure(IApplicationBuilder app)
{
    ....
    
    app.UseMvc();
}

If you need to specifically revert the new routing features, this can be done by setting an option. We’ve tried to make the new endpoint routing system as backwards compatible as is feasible. Please log issues at https://github.com/aspnet/Routing if you encounter problems.

We don’t plan to provide an experience in 2.2 for using the new features without MVC – our focus for right now is to make sure we can successfully shift MVC applications to the new infrastructure.

Link Generator Service

We’re introducing a new singleton service that will support generating a URL. This new service can be used from middleware, and does not require an HttpContext. For right now the set of things you can link to is limited to MVC actions, but this will expand in 3.0.

public class MyMiddleware
{
    public MyMiddleware(RequestDelegate next, LinkGenerator linkGenerator) { ... }
    
    public async Task Invoke(HttpContext httpContext)
    {
        var url = _linkGenerator.GenerateLink(new { controller = "Store",
                                                    action = "ListProducts" });
    
        httpContext.Response.ContentType = "text/plain";
        return httpContext.Response.WriteAsync($"Go to {url} to see some cool stuff.");
    }
}

This looks a lot like MVC’s link generation support (IUrlHelper) for now — but it’s usable anywhere in your application. We plan to expand the set of things that are possible during 2.2.

Performance Improvements

One of the biggest reasons for us to revisit routing in 2.2 is to improve the performance of routing and MVC’s action selection.

We still have more work to, but the results so far are promising:

This chart shows the trend of Requests per Second (RPS) of our MVC implementation of the TechEmpower plaintext benchmark. We’ve improved the RPS of this benchmark about 10% from 445kRPS to 515kRPS.

To test more involved scenarios, we’ve used the Swagger/OpenAPI files published by Azure and Github to build code-generated routing benchmarks. The Azure API benchmark has 5160 distinct HTTP endpoints, and the Github benchmark has 243. The new routing system is significantly faster at processing the route table of these real world APIs than anything we’ve had before. In particular MVC’s features that select actions such as matching on HTTP methods and [Consumes(...)] are significantly less costly.

Improvements to link generation behavior for attribute routing

We’re also using this opportunity to revisit some of the behaviors that users find confusing when using attribute routing. Razor Pages is based on MVC’s attribute routing infrastructure and so many new users have become familiar with these problems lately. Inside the team, we refer to this feature as ‘route value invalidation’.

Without getting into too many details, conventional routing always invalidates extra route values when linking to another action. Attribute routing didn’t have this behavior in the past. This can lead to mistakes when linking to another action that uses the same route parameter names. Now both forms of routing invalidate values when linking to another action.

A conceptual understanding

The new routing system is called ‘Endpoint Routing’ because it represents the route table as a set of Endpoints that can be selected by the the routing system. If you’ve ever thought about how attribute routing might work in MVC, the above description should not be surprising. The new part is that a bunch of concerns traditionally handled by MVC have been pushed down to a very low level of the routing system. Endpoint routing now processes HTTP methods, [Consumes(...)], versioning, and other policies that used to be part of MVC’s action selection process.

In contrast to this, the existing routing system models the application is a list of ‘Routes’ that need to be processed in order. What each route does is a black-box to the routing system – you have to run the route to see if it will match.

To make MVC’s conventional routing work, we flatten the list of actions multiplied by the number of routes into a list of endpoints. This flattening allows us to process all of MVC’s requirements very efficiently inside the routing system.

The list of endpoints gets compiled into a tree that’s easy for us to walk efficiently. This is similar to what attribute routing does today but using a different algorithm and much lower complexity. Since routing builds a graph based on the endpoints, this means that the complexity of the tree scales very directly with your usage of features. We’re confident that we can scale up this design nicely while retaining the pay-for-play characteristics.

New round-tripping route parameter syntax

We are introducing a new catch-all parameter syntax {**myparametername}. During link generation, the routing system will encode all the content in the value captured by this parameter except the forward slashes.
Note that the old parameter syntax {*myparametername} will continue to work as it did before. Examples:

• For a route defined using the old parameter syntax : /search/{*page},
  a call to Url.Action(new { category = "admin/products" }) would generate a link /search/admin%2Fproducts (notice that the forward slash is encoded)
• For a route defined using the new parameter syntax : /search/{**page},
  a call to Url.Action(new { category = "admin/products" }) would generate a link /search/admin/products

What is coming next?

Expect more refinement and polish on the LinkGenerator API in the next preview. We want to make sure that this new API will support a variety of scenarios for the foreseeable future.

How can you help?

There are a few areas where you can provide useful feedback during this preview. We’re interested in any thoughts you have of course, these are a few specific things we’d like opinions on. The best place to provide feedback is by opening issues at https://github.com/aspnet/Routing

What are you using IRouter for? The ‘Endpoint Routing’ system doesn’t support IRouter-based extensibility, including inheriting from Route. We want what you’re using IRouter for today so we can figure out how to accomplish those things in the future.

What are you using IActionConstraint for? ‘Endpoint Routing’ supports IActionConstraint-based extensibility from MVC, but we’re trying to find better ways to accomplish these tasks.

What are your ‘most wanted’ issues from Routing? We’ve revisited a bunch of old closed bugs and brought back a few for reconsideration. If you feel like there are missing details or bugs in routing that we should consider please let us know.

Caveats and notes

We’ve worked to make the new routing system backwards compatible where possible. If you run into issues we’d love for you to report them at https://github.com/aspnet/Routing.

DataTokens are not supported in 2.2.0-preview1. We plan to address this for the next preview.

By nature the new routing system does not support IRouter based extensibility.

Generating links inside MVC to conventionally routed actions that don’t yet exist will fail (resulting in the empty string). This is in contrast to the current MVC behavior where linking usually succeeds even if the action being linked hasn’t been defined yet.

We know that the performance of link generation will be bad in 2.2.0-preview1. We worked hard to get the API definitions in so that you could try it out, and ignored performance. Expect the performance of URL generation to improve significantly for the next preview.

Endpoint routing does not support WebApiCompatShim. You must use the 2.1 compatibility switch to continue using the compat shim.

As GopherCon kicks off today with nearly 2,000 gophers gathering in Denver, we’re excited to share our latest offerings and announcements for Go developers. Since making the Azure SDK for Go generally available earlier this year, our teams have been hard at work building Go tools and services for Azure, Visual Studio Code, and Visual Studio Team Services. We continue to strive to help Go developers build better cloud apps, faster, with an expanding range of services covering the cloud-native workflow:

• Write and test code with Visual Studio Code, the most popular editor amongst Go developers. Debug with visual breakpoints, apply Go formatting on save, and use code completions to increase developer speed and productivity.
• Host your private Git repositories, then integrate and release apps with Visual Studio Team Services and Azure DevOps Projects.
• Run code, containers, and apps on Azure Kubernetes Service, a fully-managed Kubernetes cluster, or with Azure App Service. Or, use your favorite Linux distribution on Azure Virtual Machines.
• Store structured data in managed PostgreSQL and MySQL databases, objects in Blob Storage, and cache items in Redis Cache. You can also use Cosmos DB, a globally-replicated, multi-model database that is compatible with MongoDB.
• Communicate between microservices with Azure Service Bus, Event Hubs, and Event Grid.
• Authenticate users and manage a directory with OpenID Connect and Azure Active Directory.
• Gather and monitor traces with Application Insights, and soon OpenCensus.

New SDK packages and Buffalo-Azure Project

To continue improving the experience of Go developers on Azure we’re building new packages and improving existing ones, starting with the Azure SDK for Go and related samples. Since the start of the year, we’ve also published new packages for Service Bus, Event Hubs, and Blob Storage, among others. We’re always listening to customer feedback, so if you’d like another package or an improvement to an existing one, please let us know on the Go SDK’s GitHub issue tracker.

Packages aren’t all, though. You’ve asked for frameworks and templates to get started faster with Go and with Azure, and we’ve listened by adding plugins to the Buffalo project to help you get up to speed quickly. Buffalo is an emerging framework for rapidly generating components for Go web apps, and the Buffalo-Azure project adds plugins to help provision app and database resources, use Service Bus queues for worker tasks, and generate handlers for Event Grid events. Want support for other services or have feedback on these? Please open issues in the project’s tracker. Our roadmap is informed by your needs!

“Get started” videos

To help you learn and get started with Go on Azure, our gophers recently took over Microsoft Channel9 studios, and recorded a series of videos demonstrating how to build and run Go apps with Azure, Visual Studio Code, and Visual Studio Team Services. Check them out in the playlist below!

We’re far from done...

Our team seeks to provide services, tools, runtimes, documentation, and guidance to make writing and maintaining Go cloud apps simpler and more fun for you, so your input as a Go developer is vital! If you’re at GopherCon, drop by our booth and chat with us. You can also open requests in our trackers to tell us what you’re working on and how Azure can better serve you.

Last but not least, in addition to updates to these products and services, be sure to check out the announcement on the Microsoft + Open Source blog for Go community-related projects and activities we’re leading and contributing to.

Image credits: @AshleyMcNamara

Read more

• Azure SDK for Go
• Go on Azure sample code
• Azure Dev Center for Go

What does hybrid cloud mean to IT professionals, and why are so many companies using it? Microsoft conducted a survey with research firm Kantar TNS in January 2018, asking more than 1700 respondents to chime in. Surveys were collected from IT professionals, developers, and business decision makers to identify how they perceive hybrid cloud, what motivates adoption, and what features they see as most important. Survey participants in the United States, the United Kingdom, Germany, and India were asked their thoughts about hybrid, which for the survey was defined as consisting of “private cloud or on-premises resources/applications integrated with one or more public clouds”. We’ve created a summary infographic of the survey that you can review. A few survey highlights:

• Hybrid is common, with a total of 67 percent of respondents now using or planning to deploy a hybrid cloud. Many of those hybrid users have made the move recently, 54 percent of users in the past two years.
• Cost, a consistent IT experience, and the ability to scale quickly were all given as important reasons for moving to hybrid cloud.
• The perceived benefits of hybrid cloud, as well as some of the challenges, vary by the geographic location of respondents. For example, increased security was the top benefit cited in the United Kingdom and Germany, while the top United States benefit was better scalability of compute resources.
• The top use case given for hybrid cloud was controlling where important data is stored at 71 percent. Using the cloud for backup and disaster recovery was a close second at 69 percent.

We invite you to download and share our infographic on the state of today’s hybrid cloud. For a more complete review of the State of Hybrid Cloud 2018 survey findings, watch the on-demand webinar Among the Clouds: Enterprises Still Prefer Hybrid in 2018.

For more information about hybrid networking, identity, management and data on Azure, you can also check out this new Azure Essentials segment, Integrating Azure with your on-premises infrastructure.

State of Hybrid Cloud 2018 survey

Participants for this online survey were recruited from (non-Microsoft) local market lists selected by Microsoft and the international research firm Kantar TNS, which was hired to conduct the outreach. Survey participants included IT professionals, professional developers, and business decision makers/influencers who use, are planning, or have considered a hybrid cloud deployment. Surveyed company sizes were from mid-market to enterprise (250+). The survey was conducted January 4 - 24, 2018. For the purposes of this survey, hybrid cloud was defined as follows. Hybrid cloud consists of private cloud or on-premises resources/applications integrated with one or more public clouds.

In the modern workplace, rising expectations to innovate and improve productivity are putting pressure on employees to do more in less time. The world’s most successful organizations are addressing this by adopting new ways of working that leverage Microsoft 365 with OneDrive and SharePoint to manage and collaborate on content.

Today, we are announcing upcoming capabilities that, along with our recent investments, combine the power of artificial intelligence (AI) and machine learning with content stored in OneDrive and SharePoint to help you be more productive, make more informed decisions, and keep more secure.

Be more productive

A key to being productive is leveraging existing content so you’re not reinventing the wheel. Historically this has been challenging due to the exponential growth of digital content, particularly with image, video, and audio files. Until now, these rich file types have been cumbersome to manage and painful to sift through to find what you need, when you need it.

Video and audio transcription—Beginning later this year, automated transcription services will be natively available for video and audio files in OneDrive and SharePoint using the same AI technology available in Microsoft Stream. While viewing a video or listening to an audio file, a full transcript (improving both accessibility and search) will show directly in our industry-leading viewer, which supports over 320 different file types. This will help you utilize your personal video and audio assets, as well as collaborate with others to produce your best work.

Once you’re ready to make a video broadly available across the organization, you can upload and publish to Microsoft Stream. You’ll continue to get transcription services plus other AI driven capabilities, including in-video face detection and automatic captions. Importantly, your audio and video content never leaves the Microsoft Cloud; it is not passed through potentially costly and insecure third-party services.

Searching audio, video, and images—Announced last September, we are unlocking the value of photos and images stored in OneDrive and SharePoint. Using native, secure AI, we determine where photos were taken, recognize objects, and extract text in photos. This recognition and text extraction allows you to search for images as easily as you search for documents. For example, you could search a folder of scanned receipts for the receipt that mentions “sushi.” Video and audio files also become fully searchable thanks to the transcription services described earlier.

Intelligent files recommendations—Later this year, we’ll introduce a new files view to OneDrive and the Office.com home page to recommend relevant files to you. Suggested files are based on the intelligence of the Microsoft Graph and its understanding of how you work, who you work with, and activity on content shared with you across Microsoft 365. This deep understanding of user behavior and relationships among coworkers is unique to Microsoft 365 and continues to be enriched as you collaborate on content in OneDrive and SharePoint.

AI also makes it easier to create new documents by reusing existing content. The Tap feature in Word 2016 and Outlook 2016 intelligently recommends content stored in OneDrive and SharePoint by understanding the context of what you are working on. This allows you to leverage and repurpose a paragraph, table, graphic, chart, or more from another file while working on a new document or email.

Make more informed decisions

OneDrive and SharePoint make your life easier thanks to innovative AI that helps you make more informed decisions while working with content.

File insights—Earlier this year, we rolled out an updated file card, providing access statistics for any file stored in OneDrive and SharePoint. This allows you to see who has looked at the file and what they have been doing, and it helps you decide your next action. Later this year, we’ll bring these valuable file statistics directly into the native Office application experience.

Additionally, we’ll introduce additional insights to the file card with “Inside look,” giving you important information at a glance—including time to read and key points from the document, so you can choose to dive in deeper or save it for later.

Intelligent sharing—Later this year, you’ll have the option to easily share relevant content with meeting attendees. For instance, if you just presented a PowerPoint presentation, you’ll be prompted to share it with the other attendees once the meeting is over. In the OneDrive mobile app, we’ll automatically prompt you to share photos taken during the same meeting, perhaps of a whiteboard where you brainstormed new ideas with your colleagues—all based on your Outlook calendar. This type of real-world intelligence allows you to quickly keep everyone informed and move on to your next task and is exclusively available when you store your content in OneDrive and SharePoint.

Data insights—Earlier this year at the SharePoint Virtual Summit, we showed you how you could immediately enrich your OneDrive and SharePoint content with intelligence by leveraging the flexibility of Microsoft Flow and the power of Azure Cognitive Services. Since these services are powered by Microsoft Azure, you can get sentiment analysis, key word extraction, and even custom image recognition—all while keeping your content secure in the Microsoft Cloud and away from potentially costly and insecure third-party services. Additionally, you can use information provided by these cognitive services to set up custom workflows to organize images, trigger notifications, or invoke more extensive business processes directly in OneDrive and SharePoint with deep integration to Microsoft Flow.

Keep more secure

When your files are stored in OneDrive and SharePoint, AI also helps to protect your content, keep you compliant, and thwart malicious attacks.

OneDrive files restore—Earlier this year, we released OneDrive files restore including integration with Windows Defender Antivirus to protect you from ransomware attacks by identifying breaches and guiding you through remediation and file recovery. With a full 30 days of file history and sophisticated machine learning to help us spot potential attacks early, OneDrive gives you peace of mind for every file you store. Best of all, moving your files to OneDrive has never been easier thanks to Known Folder Move.

Intelligent compliance—In addition to being able to apply native data loss prevention (DLP) policies and conduct native eDiscovery searches on textual content stored in OneDrive and SharePoint, with the innovations discussed above, we’re making it even easier to use these key compliance capabilities with audio, video, and images later this year. Soon you’ll be able to leverage the text extracted from photos and audio/video transcriptions to automatically apply these policies and protect this content.

Get started

As you can see, by leveraging Microsoft’s industry-leading investments in AI we have made OneDrive and SharePoint in Microsoft 365 the smartest place to store your content. In fact, Microsoft is recognized as a leader by Gartner in both their Content Collaboration Platforms Magic Quadrant and Content Services Platforms Magic Quadrant reports, as well as Forrester in both their cloud and hybrid Forrester Wave: Enterprise File Sync and Share Platforms Q4 2017 reports.

You can start realizing these benefits and more by moving your content to OneDrive and SharePoint today, just as Fortune 500 customers MGM Resorts International, Walmart, Johnson Controls International, and Textron are doing. You’ll automatically get more value as we continue to invest in these and other new AI capabilities to help you achieve more.

Microsoft has a bold vision to transform content collaboration for the modern workplace inclusive of files, dynamic web sites and portals, streaming video, AI, and mixed reality, while reducing costs and improving compliance and security. Be sure to join us at Microsoft Ignite from September 24–28, 2018 in Orlando, Florida, or on-demand, where we’ll continue to unveil how AI will accelerate content collaboration in the modern workplace.

The post Microsoft 365 is the smartest place to store your content appeared first on Microsoft 365 Blog.

Thanks to the explosion of IoT we now have millions of devices, machines, products, and assets connected and streaming terabytes of data. But connecting to devices, ingesting and storing their sensor data is just the first step. The whole point of collecting this data is to extract actionable insights — insights that will trigger some sort of action that will result in business value such as:

• Optimized factory operations: reduce cycle time, increase throughput, increase machine utilization, reduce costs, reduce unplanned downtime.
• Improved product quality: reduce manufacturing defects, identify design features that are causing manufacturing problems.
• Better understanding of customer demand: validate usage assumptions, understand product usage patterns.
• New sources of revenue: support attached services, Product-as-a-Service models.
• Improved customer experience: respond more quickly to issues, help them optimize their usage of your product.

Extracting insights from IoT data is essentially a big data analytics challenge. It’s about analyzing lots of data, coming in fast, from different sources and in different formats. But it’s not your garden-variety analytics problem because: (1) data comes from “things” (as opposed to from humans or other software systems), (2) IoT data is almost always real-time, streamed, time-series data, coming in at different frequencies, and (3) IoT data often supports scenarios that require real-time decisions.

What are the things we typically want to do with IoT data (once we collect it and store it)? In order of sophistication:

1. Visualize it:  to answer “What’s happening?” questions.
2. Analyze it: to answer “Why is this happening?” questions.
3. Make predictions: to peer into the future to answer “What’s going to happen?” questions.
4. Act on the insights: is about doing something with the insights we extracted. Usually to fix or improve something.

With end actions ranging from sending a simple command to a machine, to tweaking operational parameters, to performing an action on another software system, to implementing company-wide improvement programs.

IoT solutions are complex and contain lots of moving parts. As someone tasked with implementing an IoT solution for your company, it may be hard to understand exactly what you should build versus what you should buy. The IoT market is still very fragmented and in flux, and the lines between what’s a platform and what’s a solution are often blurry.

Recommended next steps

To help you get started today, cut through the overwhelming amount of information and provide a path for your company to take the first actionable step in using an IoT solution, we just released the Extracting insights from IoT data overview. Here you can learn more about the value of IoT data, the anatomy of an IoT solution, available options for IoT data analytics, how to act on the insights you extract, and build vs. buy considerations. Listen from software vendors developing IoT solutions on Azure and from customers extracting real value out of their IoT investments.

I post regularly about new developments on social media. If you would like to follow me you can find me on Linkedin and Twitter.

1. A tsunami of healthcare data

Healthcare is drowning in data. An article by CIO.com outlines How CIOs Can Prepare for Healthcare ‘Data Tsunami.’ Digitization of healthcare information, EHR systems, precision and personalized medicine, health information exchange, consumer health, Internet of Medical Things (IoMT), and other major trends affecting healthcare are accelerating this data growth rate. Artificial Intelligence (AI) and Machine Learning (ML) are powerful tools that empower healthcare organizations to process the tsunami of healthcare data in near real time, maximize the value of this data, and delivering actionable insights near real-time insights that in turn enable healthcare to maximize the Quadruple Aim Objectives of improving patient outcomes, reducing healthcare costs, and improving the experiences of both patients and healthcare professionals. Increasingly healthcare organizations run AI / ML workloads in the cloud to reduce costs, and improve security, agility, and scalability.

2. Healthcare professional burnout

Clinician burnout is a major concern across healthcare providers with 42 percent of physicians indicating burnout in a recent research study by Medscape, and their job is the major lifestyle factor, with too many bureaucratic tasks (for example charting, paperwork) cited as the major task factor. Too much healthcare data and administrative tasks around the processing of this data exacerbates these challenges. AI / ML can automate the processing of healthcare data and associated mundane tasks, in near real time, freeing up healthcare workers, empowering them with actionable insights, and enabling them to spend more time with patients.

3. Healthcare costs are redlining

Healthcare costs are skyrocketing. In 2016, healthcare costs in the US are estimated at nearly 18 percent of the GDP! Healthcare is becoming less affordable worldwide, and a serious chasm is widening between those that can afford healthcare and those that cannot. AI can automate tasks making healthcare more efficient, reducing costs, and improving access for example through 24 x 7 healthcare chatbots. AI has also been widely and very successfully used in anti-fraud, helping to further reduce associated costs. AI powered by the cloud empowers healthcare with strategic, transformative new capabilities in an agile and scalable way, while enabling healthcare organizations to reduce costs.

4. Ransomware disrupts healthcare and breaches erode patient trust

Ransomware incidents such as WannaCry have been very disruptive to healthcare worldwide with many healthcare organizations including healthcare providers experiencing degraded IT services, and some having to direct patients elsewhere. This degrades the quality of care and in a worst case can be a direct threat to patient safety. Cybersecurity breaches, including those affecting healthcare payers with massive databases of sensitive healthcare information seriously degrade the patient experience, and erode patient trust in the healthcare system. AI promises to empower cybersecurity teams in healthcare organizations with the ability to detect malware quickly and detect vulnerable systems and risky healthcare workers enabling proactive remediation or training to mitigate the risk of future incidents.

Healthcare wants solutions, not IT projects

Download the new, free AI in Healthcare guide to find out more about how these trends are driving a new set of transformational use cases and workloads powered by AI and delivered from the Microsoft Azure cloud. Why start from scratch, though? See how you can accelerate your healthcare AI initiative with free blueprints that include not only documentation and security and compliance support, but also example code, test data, and automated deployment to rapidly establish an AI solution reference starting point that you can then customize to achieve your target AI solution faster. Need help? Microsoft is working with an army of partners to expedite AI solutions to the healthcare industry. See within this guide key partners you can reach out to now to help you further accelerate your AI initiatives.

Collaboration

What other trends and solutions are you seeing for AI in healthcare? We welcome any feedback or questions you may have below. AI in healthcare is a fast-moving field. New developments are emerging daily. Many of these new developments are not things you can read about yet in a textbook. I post daily about these new developments and solutions in healthcare, AI, cloud computing, security, privacy, compliance, and blockchain on social media. Reach out to connect with me on LinkedIn and Twitter.

Today, we released a new Windows 10 Preview Build of the SDK to be used in conjunction with Windows 10 Insider Preview (Build 17744 or greater). The Preview SDK Build 17744 contains bug fixes and under development changes to the API surface area.

The Preview SDK can be downloaded from developer section on Windows Insider.

For feedback and updates to the known issues, please see the developer forum. For new developer feature requests, head over to our Windows Platform UserVoice.

Things to note:

• This build works in conjunction with previously released SDKs and Visual Studio 2017. You can install this SDK and still also continue to submit your apps that target Windows 10 build 1803 or earlier to the store.
• The Windows SDK will now formally only be supported by Visual Studio 2017 and greater. You can download the Visual Studio 2017 here.
• This build of the Windows SDK will only install on Windows 10 Insider Preview builds.
• In order to assist with script access to the SDK, the ISO will also be able to be accessed through the following URL: https://go.microsoft.com/fwlink/?prd=11966&pver=1.0&plcid=0x409&clcid=0x409&ar=Flight&sar=Sdsurl&o1=17744 once the static URL is published.

C++/WinRT Update for build 17709 and beyond:

This update introduces many improvements and fixes for C++/WinRT. Notably, it introduces the ability to build C++/WinRT without any dependency on the Windows SDK. This isn’t particularly interesting to the OS developer, but even in the OS repo it provides benefits because it does not itself include any Windows headers. Thus, a developer will typically pull in fewer or no dependencies inadvertently. This also means a dramatic reduction in the number of macros that a C++/WinRT developer must guard against. Removing the dependency on the Windows headers means that C++/WinRT is more portable and standards compliant and furthers our efforts to make it a cross-compiler and cross-platform library. It also means that the C++/WinRT headers will never be mangled by macros. If you previously relied on C++/WinRT to include various Windows headers that you will now have to include them yourself. It has always been good practice to include any headers you depend on explicitly and not rely on another library to include them for you.

Highlights

Support get_strong and get_weak to create delegates: This update allows a developer to use either get_strong or get_weak instead of a raw this pointer when creating a delegate pointing to a member function.

Add async cancellation callback: The most frequently requested feature for C++/WinRT’s coroutine support has been the addition of a cancellation callback.

Simplify the use of APIs expecting IBuffer parameters: Although most APIs prefer collections or arrays, enough APIs rely on IBuffer that it should be easier to use such APIs from C++. This update provides direct access to the data behind an IBuffer implementation using the same data naming convention used by the C++ standard library containers. This also avoids colliding with metadata names that conventionally begin with an uppercase letter.

Conformance: Improved support for Clang and Visual C++’s stricter conformance modes.

Improved code gen: Various improvements to reduce code size, improve inlining, and optimize factory caching.

Remove unnecessary recursion: When the command line refers to a folder rather than a specific winmd, cppwinrt will no longer search recursively for winmd files. It causes performance problems in the OS build and can lead to usage errors that are hard to diagnose when developers inadvertently cause cppwinrt to consume more winmds than expected. The cppwinrt compiler also now handles duplicates more intelligently, making it more resilient to user error and poorly-formed winmd files.

Declare both WINRT_CanUnloadNow and WINRT_GetActivationFactory in base.h: Callers don’t need to declare them directly. Their signatures have also changed, amounting to a breaking change. The declarations alleviate most of the pain of this change. The change is necessitated by the fact that C++/WinRT no longer depends on the Windows headers and this change removes the dependency on the types from the Windows headers.

Harden smart pointers: The event revokers didn’t revoke when move-assigned a new value. This lead us to take a closer look at the smart pointer classes. We noticed that they were not reliably handling self-assignment. This is rooted in the com_ptr class template that most of the others rely on. We fixed com_ptr and updated the event revokers to handle move semantics correctly to ensure that they revoke upon assignment. The handle class template has also been hardened by the removal of the implicit constructor that made it easy to write incorrect code. This also turned bugs in the OS into compiler errors fixed in this PR.

Breaking Changes

Support for non-WinRT interfaces is disabled by default. To enable, simply #include <unknwn.h> before any C++/WinRT headers.

winrt::get_abi(winrt::hstring) now returns void* instead of HSTRING. Code requiring the HSTRING ABI can simply use a static_cast.

winrt::put_abi(winrt::hstring) returns void** instead of HSTRING*. Code requiring the HSTRING ABI can simply use a reinterpret_cast.

HRESULT is now projected as winrt::hresult. Code requiring an HRESULT can simply static_cast if you need to do type checking or support type traits, but it is otherwise convertible as long as <unknwn.h> is included first.

GUID is now projected as winrt::guid. Code implementing APIs with GUID parameters must use winrt::guid instead, but it is otherwise convertible as long as <unknwn.h> is included first.

The signatures of WINRT_CanUnloadNow and WINRT_GetActivationFactory has changed. Code must not declare these functions at all and instead include winrt/base.h to include their declarations.

The winrt::handle constructor is now explicit. Code assigning a raw handle value must call the attach method instead.

winrt::clock::from_FILETIME has been deprecated. Code should use winrt::clock::from_file_time instead.

What’s New:

MSIX Support

It’s finally here! You can now package your applications as MSIX. These applications can be installed and run on any device with 17682 build or later.

To package your application with MSIX, use the MakeAppx tool. To install the application – just click on the MSIX file. To learn more about MSIX, watch this introductory video: link

Feedback and comments are welcome on our MSIX community: http://aka.ms/MSIXCommunity

MSIX is not currently supported by the App Certification Kit nor the Microsoft Store at this time.

MC.EXE

We’ve made some important changes to the C/C++ ETW code generation of mc.exe (Message Compiler):

The “-mof” parameter is deprecated. This parameter instructs MC.exe to generate ETW code that is compatible with Windows XP and earlier. Support for the “-mof” parameter will be removed in a future version of mc.exe.

As long as the “-mof” parameter is not used, the generated C/C++ header is now compatible with both kernel-mode and user-mode, regardless of whether “-km” or “-um” was specified on the command line. The header will use the _ETW_KM_ macro to automatically determine whether it is being compiled for kernel-mode or user-mode and will call the appropriate ETW APIs for each mode.

• The only remaining difference between “-km” and “-um” is that the EventWrite[EventName] macros generated with “-km” have an Activity ID parameter while the EventWrite[EventName] macros generated with “-um” do not have an Activity ID parameter.

The EventWrite[EventName] macros now default to calling EventWriteTransfer (user mode) or EtwWriteTransfer (kernel mode). Previously, the EventWrite[EventName] macros defaulted to calling EventWrite (user mode) or EtwWrite (kernel mode).

• The generated header now supports several customization macros. For example, you can set the MCGEN_EVENTWRITETRANSFER macro if you need the generated macros to call something other than EventWriteTransfer.
• The manifest supports new attributes.
• Event “name”: non-localized event name.
• Event “attributes”: additional key-value metadata for an event such as filename, line number, component name, function name.
• Event “tags”: 28-bit value with user-defined semantics (per-event).
• Field “tags”: 28-bit value with user-defined semantics (per-field – can be applied to “data” or “struct” elements).
• You can now define “provider traits” in the manifest (e.g. provider group). If provider traits are used in the manifest, the EventRegister[ProviderName] macro will automatically register them.
• MC will now report an error if a localized message file is missing a string. (Previously MC would silently generate a corrupt message resource).
• MC can now generate Unicode (utf-8 or utf-16) output with the “-cp utf-8” or “-cp utf-16” parameters.

Known Issues:

The SDK headers are generated with types in the “ABI” namespace. This is done to avoid conflicts with C++/CX and C++/WinRT clients that need to consume types directly at the ABI layer[1]. By default, types emitted by MIDL are *not* put in the ABI namespace, however this has the potential to introduce conflicts from teams attempting to consume ABI types from Windows WinRT MIDL generated headers and non-Windows WinRT MIDL generated headers (this is especially challenging if the non-Windows header references Windows types).

To ensure that developers have a consistent view of the WinRT API surface, validation has been added to the generated headers to ensure that the ABI prefix is consistent between the Windows headers and user generated headers. If you encounter an error like:

5>c:program files (x86)windows kits10include10.0.17687.0winrtwindows.foundation.h(83): error C2220: warning treated as error – no ‘object’ file generated

5>c:program files (x86)windows kits10include10.0.17687.0winrtwindows.foundation.h(83): warning C4005: ‘CHECK_NS_PREFIX_STATE’: macro redefinition

5>g:<PATH TO YOUR HEADER HERE>(41): note: see previous definition of ‘CHECK_NS_PREFIX_STATE’

It means that some of your MIDL generated headers are inconsistent with the system generated headers.

There are two ways to fix this:

• Preferred: Compile your IDL file with the /ns_prefix MIDL command line switch. This will cause all your types to be moved to the ABI namespace consistent with the Windows headers. This may require code changes in your code however.
• Alternate: Add #define DISABLE_NS_PREFIX_CHECKS before including the Windows headers. This will suppress the validation.

Windows App Certification Kit Crashes

The Windows App Certification Kit will crash when running. To avoid this failure we recommend not installing the Windows App Certification Kit. You can uncheck this option during setup.

API Updates, Additions and Removals

When targeting new APIs, consider writing your app to be adaptive in order to run correctly on the widest number of Windows 10 devices. Please see Dynamically detecting features with API contracts (10 by 10) for more information.

The following APIs have been added to the platform since the release of 17134. The APIs listed below have been removed.

There have been no changes to this API surface since build 17738.

Additions:

namespace Windows.AI.MachineLearning {
  public interface ILearningModelFeatureDescriptor
  public interface ILearningModelFeatureValue
  public interface ILearningModelOperatorProvider
  public sealed class ImageFeatureDescriptor : ILearningModelFeatureDescriptor
  public sealed class ImageFeatureValue : ILearningModelFeatureValue
  public interface ITensor : ILearningModelFeatureValue
  public sealed class LearningModel : IClosable
  public sealed class LearningModelBinding : IIterable<IKeyValuePair<string, object>>, IMapView<string, object>
  public sealed class LearningModelDevice
  public enum LearningModelDeviceKind
  public sealed class LearningModelEvaluationResult
  public enum LearningModelFeatureKind
  public sealed class LearningModelSession : IClosable
  public struct MachineLearningContract
  public sealed class MapFeatureDescriptor : ILearningModelFeatureDescriptor
  public sealed class SequenceFeatureDescriptor : ILearningModelFeatureDescriptor
  public sealed class TensorBoolean : ILearningModelFeatureValue, ITensor
  public sealed class TensorDouble : ILearningModelFeatureValue, ITensor
  public sealed class TensorFeatureDescriptor : ILearningModelFeatureDescriptor
  public sealed class TensorFloat : ILearningModelFeatureValue, ITensor
  public sealed class TensorFloat16Bit : ILearningModelFeatureValue, ITensor
  public sealed class TensorInt16Bit : ILearningModelFeatureValue, ITensor
  public sealed class TensorInt32Bit : ILearningModelFeatureValue, ITensor
  public sealed class TensorInt64Bit : ILearningModelFeatureValue, ITensor
  public sealed class TensorInt8Bit : ILearningModelFeatureValue, ITensor
  public enum TensorKind
  public sealed class TensorString : ILearningModelFeatureValue, ITensor
  public sealed class TensorUInt16Bit : ILearningModelFeatureValue, ITensor
  public sealed class TensorUInt32Bit : ILearningModelFeatureValue, ITensor
  public sealed class TensorUInt64Bit : ILearningModelFeatureValue, ITensor
  public sealed class TensorUInt8Bit : ILearningModelFeatureValue, ITensor
}
namespace Windows.ApplicationModel {
  public sealed class AppInstallerInfo
  public sealed class LimitedAccessFeatureRequestResult
  public static class LimitedAccessFeatures
  public enum LimitedAccessFeatureStatus
  public sealed class Package {
    IAsyncOperation<PackageUpdateAvailabilityResult> CheckUpdateAvailabilityAsync();
    AppInstallerInfo GetAppInstallerInfo();
  }
  public enum PackageUpdateAvailability
  public sealed class PackageUpdateAvailabilityResult
}
namespace Windows.ApplicationModel.Calls {
  public sealed class VoipCallCoordinator {
    IAsyncOperation<VoipPhoneCallResourceReservationStatus> ReserveCallResourcesAsync();
  }
}
namespace Windows.ApplicationModel.Chat {
  public static class ChatCapabilitiesManager {
    public static IAsyncOperation<ChatCapabilities> GetCachedCapabilitiesAsync(string address, string transportId);
    public static IAsyncOperation<ChatCapabilities> GetCapabilitiesFromNetworkAsync(string address, string transportId);
  }
  public static class RcsManager {
    public static event EventHandler<object> TransportListChanged;
  }
}
namespace Windows.ApplicationModel.DataTransfer {
  public static class Clipboard {
    public static event EventHandler<ClipboardHistoryChangedEventArgs> HistoryChanged;
    public static event EventHandler<object> HistoryEnabledChanged;
    public static event EventHandler<object> RoamingEnabledChanged;
    public static bool ClearHistory();
    public static bool DeleteItemFromHistory(ClipboardHistoryItem item);
    public static IAsyncOperation<ClipboardHistoryItemsResult> GetHistoryItemsAsync();
    public static bool IsHistoryEnabled();
    public static bool IsRoamingEnabled();
    public static bool SetContentWithOptions(DataPackage content, ClipboardContentOptions options);
    public static SetHistoryItemAsContentStatus SetHistoryItemAsContent(ClipboardHistoryItem item);
  }
  public sealed class ClipboardContentOptions
  public sealed class ClipboardHistoryChangedEventArgs
  public sealed class ClipboardHistoryItem
  public sealed class ClipboardHistoryItemsResult
  public enum ClipboardHistoryItemsResultStatus
  public sealed class DataPackagePropertySetView : IIterable<IKeyValuePair<string, object>>, IMapView<string, object> {
    bool IsFromRoamingClipboard { get; }
    string SourceDisplayName { get; }
  }
  public enum SetHistoryItemAsContentStatus
}
namespace Windows.ApplicationModel.Store.Preview {
  public enum DeliveryOptimizationDownloadMode
  public enum DeliveryOptimizationDownloadModeSource
  public sealed class DeliveryOptimizationSettings
  public static class StoreConfiguration {
    public static bool IsPinToDesktopSupported();
    public static bool IsPinToStartSupported();
    public static bool IsPinToTaskbarSupported();
    public static void PinToDesktop(string appPackageFamilyName);
    public static void PinToDesktopForUser(User user, string appPackageFamilyName);
  }
}
namespace Windows.ApplicationModel.Store.Preview.InstallControl {
  public enum AppInstallationToastNotificationMode
  public sealed class AppInstallItem {
    AppInstallationToastNotificationMode CompletedInstallToastNotificationMode { get; set; }
    AppInstallationToastNotificationMode InstallInProgressToastNotificationMode { get; set; }
    bool PinToDesktopAfterInstall { get; set; }
    bool PinToStartAfterInstall { get; set; }
    bool PinToTaskbarAfterInstall { get; set; }
  }
  public sealed class AppInstallManager {
    bool CanInstallForAllUsers { get; }
  }
  public sealed class AppInstallOptions {
    string CampaignId { get; set; }
    AppInstallationToastNotificationMode CompletedInstallToastNotificationMode { get; set; }
    string ExtendedCampaignId { get; set; }
    bool InstallForAllUsers { get; set; }
    AppInstallationToastNotificationMode InstallInProgressToastNotificationMode { get; set; }
    bool PinToDesktopAfterInstall { get; set; }
    bool PinToStartAfterInstall { get; set; }
    bool PinToTaskbarAfterInstall { get; set; }
    bool StageButDoNotInstall { get; set; }
  }
  public sealed class AppUpdateOptions {
    bool AutomaticallyDownloadAndInstallUpdateIfFound { get; set; }
  }
}
namespace Windows.ApplicationModel.UserActivities {
  public sealed class UserActivity {
    bool IsRoamable { get; set; }
  }
}
namespace Windows.Data.Text {
  public sealed class TextPredictionGenerator {
    CoreTextInputScope InputScope { get; set; }
    IAsyncOperation<IVectorView<string>> GetCandidatesAsync(string input, uint maxCandidates, TextPredictionOptions predictionOptions, IIterable<string> previousStrings);
    IAsyncOperation<IVectorView<string>> GetNextWordCandidatesAsync(uint maxCandidates, IIterable<string> previousStrings);
  }
  public enum TextPredictionOptions : uint
}
namespace Windows.Devices.Display.Core {
  public sealed class DisplayAdapter
  public enum DisplayBitsPerChannel : uint
  public sealed class DisplayDevice
  public enum DisplayDeviceCapability
  public sealed class DisplayFence
  public sealed class DisplayManager : IClosable
  public sealed class DisplayManagerChangedEventArgs
  public sealed class DisplayManagerDisabledEventArgs
  public sealed class DisplayManagerEnabledEventArgs
  public enum DisplayManagerOptions : uint
  public sealed class DisplayManagerPathsFailedOrInvalidatedEventArgs
  public enum DisplayManagerResult
  public sealed class DisplayManagerResultWithState
  public sealed class DisplayModeInfo
  public enum DisplayModeQueryOptions : uint
  public sealed class DisplayPath
  public enum DisplayPathScaling
  public enum DisplayPathStatus
  public struct DisplayPresentationRate
  public sealed class DisplayPrimaryDescription
  public enum DisplayRotation
  public sealed class DisplayScanout
  public sealed class DisplaySource
  public sealed class DisplayState
  public enum DisplayStateApplyOptions : uint
  public enum DisplayStateFunctionalizeOptions : uint
  public sealed class DisplayStateOperationResult
  public enum DisplayStateOperationStatus
  public sealed class DisplaySurface
  public sealed class DisplayTarget
  public enum DisplayTargetPersistence
  public sealed class DisplayTask
  public sealed class DisplayTaskPool
  public enum DisplayTaskSignalKind
  public sealed class DisplayView
  public sealed class DisplayWireFormat
  public enum DisplayWireFormatColorSpace
  public enum DisplayWireFormatEotf
  public enum DisplayWireFormatHdrMetadata
  public enum DisplayWireFormatPixelEncoding
}
namespace Windows.Devices.Enumeration {
  public enum DeviceInformationKind {
    DevicePanel = 8,
  }
  public sealed class DeviceInformationPairing {
    public static bool TryRegisterForAllInboundPairingRequestsWithProtectionLevel(DevicePairingKinds pairingKindsSupported, DevicePairingProtectionLevel minProtectionLevel);
  }
}
namespace Windows.Devices.Enumeration.Pnp {
  public enum PnpObjectType {
    DevicePanel = 8,
  }
}
namespace Windows.Devices.Lights {
  public sealed class LampArray
  public enum LampArrayKind
  public sealed class LampInfo
  public enum LampPurposes : uint
}
namespace Windows.Devices.Lights.Effects {
  public interface ILampArrayEffect
  public sealed class LampArrayBitmapEffect : ILampArrayEffect
  public sealed class LampArrayBitmapRequestedEventArgs
  public sealed class LampArrayBlinkEffect : ILampArrayEffect
  public sealed class LampArrayColorRampEffect : ILampArrayEffect
  public sealed class LampArrayCustomEffect : ILampArrayEffect
  public enum LampArrayEffectCompletionBehavior
  public sealed class LampArrayEffectPlaylist : IIterable<ILampArrayEffect>, IVectorView<ILampArrayEffect>
  public enum LampArrayEffectStartMode
  public enum LampArrayRepetitionMode
  public sealed class LampArraySolidEffect : ILampArrayEffect
  public sealed class LampArrayUpdateRequestedEventArgs
}
namespace Windows.Devices.PointOfService {
  public sealed class BarcodeScannerCapabilities {
    bool IsVideoPreviewSupported { get; }
  }
  public sealed class ClaimedBarcodeScanner : IClosable {
    event TypedEventHandler<ClaimedBarcodeScanner, ClaimedBarcodeScannerClosedEventArgs> Closed;
  }
  public sealed class ClaimedBarcodeScannerClosedEventArgs
  public sealed class ClaimedCashDrawer : IClosable {
    event TypedEventHandler<ClaimedCashDrawer, ClaimedCashDrawerClosedEventArgs> Closed;
  }
  public sealed class ClaimedCashDrawerClosedEventArgs
  public sealed class ClaimedLineDisplay : IClosable {
    event TypedEventHandler<ClaimedLineDisplay, ClaimedLineDisplayClosedEventArgs> Closed;
  }
  public sealed class ClaimedLineDisplayClosedEventArgs
  public sealed class ClaimedMagneticStripeReader : IClosable {
    event TypedEventHandler<ClaimedMagneticStripeReader, ClaimedMagneticStripeReaderClosedEventArgs> Closed;
  }
  public sealed class ClaimedMagneticStripeReaderClosedEventArgs
  public sealed class ClaimedPosPrinter : IClosable {
    event TypedEventHandler<ClaimedPosPrinter, ClaimedPosPrinterClosedEventArgs> Closed;
  }
  public sealed class ClaimedPosPrinterClosedEventArgs
}
namespace Windows.Devices.PointOfService.Provider {
  public sealed class BarcodeScannerDisableScannerRequest {
    IAsyncAction ReportFailedAsync(int reason);
    IAsyncAction ReportFailedAsync(int reason, string failedReasonDescription);
  }
  public sealed class BarcodeScannerEnableScannerRequest {
    IAsyncAction ReportFailedAsync(int reason);
    IAsyncAction ReportFailedAsync(int reason, string failedReasonDescription);
  }
  public sealed class BarcodeScannerFrameReader : IClosable
  public sealed class BarcodeScannerFrameReaderFrameArrivedEventArgs
  public sealed class BarcodeScannerGetSymbologyAttributesRequest {
    IAsyncAction ReportFailedAsync(int reason);
    IAsyncAction ReportFailedAsync(int reason, string failedReasonDescription);
  }
  public sealed class BarcodeScannerHideVideoPreviewRequest {
    IAsyncAction ReportFailedAsync(int reason);
    IAsyncAction ReportFailedAsync(int reason, string failedReasonDescription);
  }
  public sealed class BarcodeScannerProviderConnection : IClosable {
    IAsyncOperation<BarcodeScannerFrameReader> CreateFrameReaderAsync();
    IAsyncOperation<BarcodeScannerFrameReader> CreateFrameReaderAsync(BitmapPixelFormat preferredFormat);
    IAsyncOperation<BarcodeScannerFrameReader> CreateFrameReaderAsync(BitmapPixelFormat preferredFormat, BitmapSize preferredSize);
  }
  public sealed class BarcodeScannerSetActiveSymbologiesRequest {
    IAsyncAction ReportFailedAsync(int reason);
    IAsyncAction ReportFailedAsync(int reason, string failedReasonDescription);
  }
  public sealed class BarcodeScannerSetSymbologyAttributesRequest {
    IAsyncAction ReportFailedAsync(int reason);
    IAsyncAction ReportFailedAsync(int reason, string failedReasonDescription);
  }
  public sealed class BarcodeScannerStartSoftwareTriggerRequest {
    IAsyncAction ReportFailedAsync(int reason);
    IAsyncAction ReportFailedAsync(int reason, string failedReasonDescription);
  }
  public sealed class BarcodeScannerStopSoftwareTriggerRequest {
    IAsyncAction ReportFailedAsync(int reason);
    IAsyncAction ReportFailedAsync(int reason, string failedReasonDescription);
  }
  public sealed class BarcodeScannerVideoFrame : IClosable
}
namespace Windows.Devices.Sensors {
  public sealed class HingeAngleReading
  public sealed class HingeAngleSensor
  public sealed class HingeAngleSensorReadingChangedEventArgs
  public sealed class SimpleOrientationSensor {
    public static IAsyncOperation<SimpleOrientationSensor> FromIdAsync(string deviceId);
    public static string GetDeviceSelector();
  }
}
namespace Windows.Devices.SmartCards {
  public static class KnownSmartCardAppletIds
  public sealed class SmartCardAppletIdGroup {
    string Description { get; set; }
    IRandomAccessStreamReference Logo { get; set; }
    ValueSet Properties { get; }
    bool SecureUserAuthenticationRequired { get; set; }
  }
  public sealed class SmartCardAppletIdGroupRegistration {
    string SmartCardReaderId { get; }
    IAsyncAction SetPropertiesAsync(ValueSet props);
  }
}
namespace Windows.Devices.WiFi {
  public enum WiFiPhyKind {
    HE = 10,
  }
}
namespace Windows.Foundation {
  public static class GuidHelper
}
namespace Windows.Globalization {
  public static class CurrencyIdentifiers {
    public static string MRU { get; }
    public static string SSP { get; }
    public static string STN { get; }
    public static string VES { get; }
  }
}
namespace Windows.Graphics.Capture {
  public sealed class Direct3D11CaptureFramePool : IClosable {
    public static Direct3D11CaptureFramePool CreateFreeThreaded(IDirect3DDevice device, DirectXPixelFormat pixelFormat, int numberOfBuffers, SizeInt32 size);
  }
  public sealed class GraphicsCaptureItem {
    public static GraphicsCaptureItem CreateFromVisual(Visual visual);
  }
}
namespace Windows.Graphics.Display.Core {
  public enum HdmiDisplayHdrOption {
    DolbyVisionLowLatency = 3,
  }
  public sealed class HdmiDisplayMode {
    bool IsDolbyVisionLowLatencySupported { get; }
  }
}
namespace Windows.Graphics.Holographic {
  public sealed class HolographicCamera {
    bool IsHardwareContentProtectionEnabled { get; set; }
    bool IsHardwareContentProtectionSupported { get; }
  }
  public sealed class HolographicQuadLayerUpdateParameters {
    bool CanAcquireWithHardwareProtection { get; }
    IDirect3DSurface AcquireBufferToUpdateContentWithHardwareProtection();
  }
}
namespace Windows.Graphics.Imaging {
  public sealed class BitmapDecoder : IBitmapFrame, IBitmapFrameWithSoftwareBitmap {
    public static Guid HeifDecoderId { get; }
    public static Guid WebpDecoderId { get; }
  }
  public sealed class BitmapEncoder {
    public static Guid HeifEncoderId { get; }
  }
}
namespace Windows.Management.Deployment {
  public enum DeploymentOptions : uint {
    ForceUpdateFromAnyVersion = (uint)262144,
  }
  public sealed class PackageManager {
    IAsyncOperationWithProgress<DeploymentResult, DeploymentProgress> DeprovisionPackageForAllUsersAsync(string packageFamilyName);
  }
  public enum RemovalOptions : uint {
    RemoveForAllUsers = (uint)524288,
  }
}
namespace Windows.Media.Audio {
  public sealed class CreateAudioDeviceInputNodeResult {
    HResult ExtendedError { get; }
  }
 public sealed class CreateAudioDeviceOutputNodeResult {
    HResult ExtendedError { get; }
  }
  public sealed class CreateAudioFileInputNodeResult {
    HResult ExtendedError { get; }
  }
  public sealed class CreateAudioFileOutputNodeResult {
    HResult ExtendedError { get; }
  }
  public sealed class CreateAudioGraphResult {
    HResult ExtendedError { get; }
  }
  public sealed class CreateMediaSourceAudioInputNodeResult {
    HResult ExtendedError { get; }
  }
  public enum MixedRealitySpatialAudioFormatPolicy
  public sealed class SetDefaultSpatialAudioFormatResult
  public enum SetDefaultSpatialAudioFormatStatus
  public sealed class SpatialAudioDeviceConfiguration
  public sealed class SpatialAudioFormatConfiguration
  public static class SpatialAudioFormatSubtype
}
namespace Windows.Media.Control {
  public sealed class CurrentSessionChangedEventArgs
  public sealed class GlobalSystemMediaTransportControlsSession
  public sealed class GlobalSystemMediaTransportControlsSessionManager
  public sealed class GlobalSystemMediaTransportControlsSessionMediaProperties
  public sealed class GlobalSystemMediaTransportControlsSessionPlaybackControls
  public sealed class GlobalSystemMediaTransportControlsSessionPlaybackInfo
  public enum GlobalSystemMediaTransportControlsSessionPlaybackStatus
  public sealed class GlobalSystemMediaTransportControlsSessionTimelineProperties
  public sealed class MediaPropertiesChangedEventArgs
  public sealed class PlaybackInfoChangedEventArgs
  public sealed class SessionsChangedEventArgs
  public sealed class TimelinePropertiesChangedEventArgs
}
namespace Windows.Media.Core {
  public sealed class MediaStreamSample {
    IDirect3DSurface Direct3D11Surface { get; }
    public static MediaStreamSample CreateFromDirect3D11Surface(IDirect3DSurface surface, TimeSpan timestamp);
  }
}
namespace Windows.Media.Devices.Core {
  public sealed class CameraIntrinsics {
    public CameraIntrinsics(Vector2 focalLength, Vector2 principalPoint, Vector3 radialDistortion, Vector2 tangentialDistortion, uint imageWidth, uint imageHeight);
  }
}
namespace Windows.Media.Import {
  public enum PhotoImportContentTypeFilter {
    ImagesAndVideosFromCameraRoll = 3,
  }
  public sealed class PhotoImportItem {
    string Path { get; }
  }
}
namespace Windows.Media.MediaProperties {
  public sealed class ImageEncodingProperties : IMediaEncodingProperties {
    public static ImageEncodingProperties CreateHeif();
  }
  public static class MediaEncodingSubtypes {
    public static string Heif { get; }
  }
}
namespace Windows.Media.Protection.PlayReady {
  public static class PlayReadyStatics {
    public static IReference<DateTime> HardwareDRMDisabledAtTime { get; }
    public static IReference<DateTime> HardwareDRMDisabledUntilTime { get; }
    public static void ResetHardwareDRMDisabled();
  }
}
namespace Windows.Media.Streaming.Adaptive {
  public enum AdaptiveMediaSourceResourceType {
    MediaSegmentIndex = 5,
  }
}
namespace Windows.Networking.BackgroundTransfer {
  public enum BackgroundTransferPriority {
    Low = 2,
  }
}
namespace Windows.Networking.Connectivity {
  public sealed class ConnectionProfile {
    bool CanDelete { get; }
    IAsyncOperation<ConnectionProfileDeleteStatus> TryDeleteAsync();
  }
  public enum ConnectionProfileDeleteStatus
}
namespace Windows.Networking.NetworkOperators {
  public enum ESimOperationStatus {
    CardGeneralFailure = 13,
    ConfirmationCodeMissing = 14,
    EidMismatch = 18,
    InvalidMatchingId = 15,
    NoCorrespondingRequest = 23,
    NoEligibleProfileForThisDevice = 16,
    OperationAborted = 17,
    OperationProhibitedByProfileClass = 21,
    ProfileNotAvailableForNewBinding = 19,
    ProfileNotPresent = 22,
    ProfileNotReleasedByOperator = 20,
  }
}
namespace Windows.Perception {
  public sealed class PerceptionTimestamp {
    TimeSpan SystemRelativeTargetTime { get; }
  }
  public static class PerceptionTimestampHelper {
    public static PerceptionTimestamp FromSystemRelativeTargetTime(TimeSpan targetTime);
  }
}
namespace Windows.Perception.Spatial {
  public sealed class SpatialAnchorExporter
  public enum SpatialAnchorExportPurpose
  public sealed class SpatialAnchorExportSufficiency
  public sealed class SpatialLocation {
    Vector3 AbsoluteAngularAccelerationAxisAngle { get; }
    Vector3 AbsoluteAngularVelocityAxisAngle { get; }
  }
}
namespace Windows.Perception.Spatial.Preview {
  public static class SpatialGraphInteropPreview
}
namespace Windows.Services.Cortana {
  public sealed class CortanaActionableInsights
  public sealed class CortanaActionableInsightsOptions
}
namespace Windows.Services.Store {
  public sealed class StoreAppLicense {
    bool IsDiscLicense { get; }
  }
  public sealed class StoreContext {
    IAsyncOperation<StoreRateAndReviewResult> RequestRateAndReviewAppAsync();
    IAsyncOperation<IVectorView<StoreQueueItem>> SetInstallOrderForAssociatedStoreQueueItemsAsync(IIterable<StoreQueueItem> items);
  }
  public sealed class StoreQueueItem {
    IAsyncAction CancelInstallAsync();
    IAsyncAction PauseInstallAsync();
    IAsyncAction ResumeInstallAsync();
  }
  public sealed class StoreRateAndReviewResult
  public enum StoreRateAndReviewStatus
}
namespace Windows.Storage.Provider {
  public enum StorageProviderHydrationPolicyModifier : uint {
    AutoDehydrationAllowed = (uint)4,
  }
  public sealed class StorageProviderSyncRootInfo {
    Guid ProviderId { get; set; }
  }
}
namespace Windows.System {
  public sealed class AppUriHandlerHost
  public sealed class AppUriHandlerRegistration
  public sealed class AppUriHandlerRegistrationManager
  public static class Launcher {
    public static IAsyncOperation<bool> LaunchFolderPathAsync(string path);
    public static IAsyncOperation<bool> LaunchFolderPathAsync(string path, FolderLauncherOptions options);
    public static IAsyncOperation<bool> LaunchFolderPathForUserAsync(User user, string path);
    public static IAsyncOperation<bool> LaunchFolderPathForUserAsync(User user, string path, FolderLauncherOptions options);
  }
}
namespace Windows.System.Preview {
  public enum HingeState
  public sealed class TwoPanelHingedDevicePosturePreview
  public sealed class TwoPanelHingedDevicePosturePreviewReading
  public sealed class TwoPanelHingedDevicePosturePreviewReadingChangedEventArgs
}
namespace Windows.System.Profile {
  public enum SystemOutOfBoxExperienceState
  public static class SystemSetupInfo
  public static class WindowsIntegrityPolicy
}
namespace Windows.System.Profile.SystemManufacturers {
  public sealed class SystemSupportDeviceInfo
  public static class SystemSupportInfo {
    public static SystemSupportDeviceInfo LocalDeviceInfo { get; }
  }
}
namespace Windows.System.RemoteSystems {
  public sealed class RemoteSystem {
    IVectorView<RemoteSystemApp> Apps { get; }
  }
  public sealed class RemoteSystemApp
  public sealed class RemoteSystemAppRegistration
  public sealed class RemoteSystemConnectionInfo
  public sealed class RemoteSystemConnectionRequest {
    RemoteSystemApp RemoteSystemApp { get; }
    public static RemoteSystemConnectionRequest CreateForApp(RemoteSystemApp remoteSystemApp);
  }
  public sealed class RemoteSystemWebAccountFilter : IRemoteSystemFilter
}
namespace Windows.System.Update {
  public enum SystemUpdateAttentionRequiredReason
  public sealed class SystemUpdateItem
  public enum SystemUpdateItemState
  public sealed class SystemUpdateLastErrorInfo
  public static class SystemUpdateManager
  public enum SystemUpdateManagerState
  public enum SystemUpdateStartInstallAction
}
namespace Windows.System.UserProfile {
  public sealed class AssignedAccessSettings
}
namespace Windows.UI.Accessibility {
  public sealed class ScreenReaderPositionChangedEventArgs
  public sealed class ScreenReaderService
}
namespace Windows.UI.Composition {
  public enum AnimationPropertyAccessMode
  public sealed class AnimationPropertyInfo : CompositionObject
  public sealed class BooleanKeyFrameAnimation : KeyFrameAnimation
  public class CompositionAnimation : CompositionObject, ICompositionAnimationBase {
    void SetExpressionReferenceParameter(string parameterName, IAnimationObject source);
  }
  public enum CompositionBatchTypes : uint {
    AllAnimations = (uint)5,
    InfiniteAnimation = (uint)4,
  }
  public sealed class CompositionGeometricClip : CompositionClip
  public class CompositionGradientBrush : CompositionBrush {
    CompositionMappingMode MappingMode { get; set; }
  }
  public enum CompositionMappingMode
  public class CompositionObject : IAnimationObject, IClosable {
    void PopulatePropertyInfo(string propertyName, AnimationPropertyInfo propertyInfo);
    public static void StartAnimationGroupWithIAnimationObject(IAnimationObject target, ICompositionAnimationBase animation);
    public static void StartAnimationWithIAnimationObject(IAnimationObject target, string propertyName, CompositionAnimation animation);
  }
  public sealed class Compositor : IClosable {
    BooleanKeyFrameAnimation CreateBooleanKeyFrameAnimation();
    CompositionGeometricClip CreateGeometricClip();
    CompositionGeometricClip CreateGeometricClip(CompositionGeometry geometry);
    RedirectVisual CreateRedirectVisual();
    RedirectVisual CreateRedirectVisual(Visual source);
  }
  public interface IAnimationObject
  public sealed class RedirectVisual : ContainerVisual
}
namespace Windows.UI.Composition.Interactions {
  public sealed class InteractionSourceConfiguration : CompositionObject
  public enum InteractionSourceRedirectionMode
  public sealed class InteractionTracker : CompositionObject {
    bool IsInertiaFromImpulse { get; }
    int TryUpdatePosition(Vector3 value, InteractionTrackerClampingOption option);
    int TryUpdatePositionBy(Vector3 amount, InteractionTrackerClampingOption option);
  }
  public enum InteractionTrackerClampingOption
  public sealed class InteractionTrackerInertiaStateEnteredArgs {
    bool IsInertiaFromImpulse { get; }
  }
  public class VisualInteractionSource : CompositionObject, ICompositionInteractionSource {
    InteractionSourceConfiguration PointerWheelConfig { get; }
  }
}
namespace Windows.UI.Input.Inking {
  public enum HandwritingLineHeight
  public sealed class PenAndInkSettings
  public enum PenHandedness
}
namespace Windows.UI.Input.Inking.Preview {
  public sealed class PalmRejectionDelayZonePreview : IClosable
}
namespace Windows.UI.Notifications {
  public sealed class ScheduledToastNotificationShowingEventArgs
  public sealed class ToastNotifier {
    event TypedEventHandler<ToastNotifier, ScheduledToastNotificationShowingEventArgs> ScheduledToastNotificationShowing;
  }
}
namespace Windows.UI.Shell {
  public enum SecurityAppKind
  public sealed class SecurityAppManager
  public struct SecurityAppManagerContract
  public enum SecurityAppState
  public enum SecurityAppSubstatus
  public sealed class TaskbarManager {
    IAsyncOperation<bool> IsSecondaryTilePinnedAsync(string tileId);
    IAsyncOperation<bool> RequestPinSecondaryTileAsync(SecondaryTile secondaryTile);
    IAsyncOperation<bool> TryUnpinSecondaryTileAsync(string tileId);
  }
}
namespace Windows.UI.StartScreen {
  public sealed class StartScreenManager {
    IAsyncOperation<bool> ContainsSecondaryTileAsync(string tileId);
    IAsyncOperation<bool> TryRemoveSecondaryTileAsync(string tileId);
  }
}
namespace Windows.UI.Text {
  public sealed class RichEditTextDocument : ITextDocument {
    void ClearUndoRedoHistory();
  }
}
namespace Windows.UI.Text.Core {
  public sealed class CoreTextLayoutRequest {
    CoreTextLayoutBounds LayoutBoundsVisualPixels { get; }
  }
}
namespace Windows.UI.ViewManagement {
  public enum ApplicationViewWindowingMode {
    CompactOverlay = 3,
    Maximized = 4,
  }
}
namespace Windows.UI.ViewManagement.Core {
  public sealed class CoreInputView {
    bool TryHide();
    bool TryShow();
    bool TryShow(CoreInputViewKind type);
  }
  public enum CoreInputViewKind
}
namespace Windows.UI.WebUI {
  public sealed class BackgroundActivatedEventArgs : IBackgroundActivatedEventArgs
  public delegate void BackgroundActivatedEventHandler(object sender, IBackgroundActivatedEventArgs eventArgs);
  public sealed class NewWebUIViewCreatedEventArgs
  public static class WebUIApplication {
    public static event BackgroundActivatedEventHandler BackgroundActivated;
    public static event EventHandler<NewWebUIViewCreatedEventArgs> NewWebUIViewCreated;
  }
  public sealed class WebUIView : IWebViewControl, IWebViewControl2
}
namespace Windows.UI.Xaml {
  public class BrushTransition
  public class ColorPaletteResources : ResourceDictionary
  public class DataTemplate : FrameworkTemplate, IElementFactory {
    UIElement GetElement(ElementFactoryGetArgs args);
    void RecycleElement(ElementFactoryRecycleArgs args);
  }
  public sealed class DebugSettings {
    bool FailFastOnErrors { get; set; }
  }
  public sealed class EffectiveViewportChangedEventArgs
  public class ElementFactoryGetArgs
  public class ElementFactoryRecycleArgs
  public class FrameworkElement : UIElement {
    bool IsLoaded { get; }
    event TypedEventHandler<FrameworkElement, EffectiveViewportChangedEventArgs> EffectiveViewportChanged;
    void InvalidateViewport();
  }
  public interface IElementFactory
  public class ScalarTransition
  public class UIElement : DependencyObject, IAnimationObject {
    bool CanBeScrollAnchor { get; set; }
    public static DependencyProperty CanBeScrollAnchorProperty { get; }
    Vector3 CenterPoint { get; set; }
    ScalarTransition OpacityTransition { get; set; }
    float Rotation { get; set; }
    Vector3 RotationAxis { get; set; }
    ScalarTransition RotationTransition { get; set; }
    Vector3 Scale { get; set; }
    Vector3Transition ScaleTransition { get; set; }
    Matrix4x4 TransformMatrix { get; set; }
    Vector3 Translation { get; set; }
    Vector3Transition TranslationTransition { get; set; }
    void PopulatePropertyInfo(string propertyName, AnimationPropertyInfo propertyInfo);
    virtual void PopulatePropertyInfoOverride(string propertyName, AnimationPropertyInfo animationPropertyInfo);
    void StartAnimation(ICompositionAnimationBase animation);
    void StopAnimation(ICompositionAnimationBase animation);
  }
  public class Vector3Transition
  public enum Vector3TransitionComponents : uint
}
namespace Windows.UI.Xaml.Automation {
  public sealed class AutomationElementIdentifiers {
    public static AutomationProperty IsDialogProperty { get; }
  }
  public sealed class AutomationProperties {
    public static DependencyProperty IsDialogProperty { get; }
    public static bool GetIsDialog(DependencyObject element);
    public static void SetIsDialog(DependencyObject element, bool value);
  }
}
namespace Windows.UI.Xaml.Automation.Peers {
  public class AppBarButtonAutomationPeer : ButtonAutomationPeer, IExpandCollapseProvider {
    ExpandCollapseState ExpandCollapseState { get; }
    void Collapse();
    void Expand();
  }
  public class AutomationPeer : DependencyObject {
    bool IsDialog();
    virtual bool IsDialogCore();
  }
  public class MenuBarAutomationPeer : FrameworkElementAutomationPeer
  public class MenuBarItemAutomationPeer : FrameworkElementAutomationPeer, IExpandCollapseProvider, IInvokeProvider
}
namespace Windows.UI.Xaml.Controls {
  public sealed class AnchorRequestedEventArgs
  public class AppBarElementContainer : ContentControl, ICommandBarElement, ICommandBarElement2
  public sealed class AutoSuggestBox : ItemsControl {
    object Description { get; set; }
    public static DependencyProperty DescriptionProperty { get; }
  }
  public enum BackgroundSizing
  public sealed class Border : FrameworkElement {
    BackgroundSizing BackgroundSizing { get; set; }
    public static DependencyProperty BackgroundSizingProperty { get; }
    BrushTransition BackgroundTransition { get; set; }
  }
  public class CalendarDatePicker : Control {
    object Description { get; set; }
    public static DependencyProperty DescriptionProperty { get; }
  }
  public class ComboBox : Selector {
    object Description { get; set; }
    public static DependencyProperty DescriptionProperty { get; }
    bool IsEditable { get; set; }
    public static DependencyProperty IsEditableProperty { get; }
    string Text { get; set; }
    Style TextBoxStyle { get; set; }
    public static DependencyProperty TextBoxStyleProperty { get; }
    public static DependencyProperty TextProperty { get; }
    event TypedEventHandler<ComboBox, ComboBoxTextSubmittedEventArgs> TextSubmitted;
  }
  public sealed class ComboBoxTextSubmittedEventArgs
  public class CommandBarFlyout : FlyoutBase
  public class ContentPresenter : FrameworkElement {
    BackgroundSizing BackgroundSizing { get; set; }
    public static DependencyProperty BackgroundSizingProperty { get; }
    BrushTransition BackgroundTransition { get; set; }
  }
  public class Control : FrameworkElement {
    BackgroundSizing BackgroundSizing { get; set; }
    public static DependencyProperty BackgroundSizingProperty { get; }
    CornerRadius CornerRadius { get; set; }
    public static DependencyProperty CornerRadiusProperty { get; }
  }
  public class DataTemplateSelector : IElementFactory {
    UIElement GetElement(ElementFactoryGetArgs args);
    void RecycleElement(ElementFactoryRecycleArgs args);
  }
  public class DatePicker : Control {
    IReference<DateTime> SelectedDate { get; set; }
    public static DependencyProperty SelectedDateProperty { get; }
    event TypedEventHandler<DatePicker, DatePickerSelectedValueChangedEventArgs> SelectedDateChanged;
  }
  public sealed class DatePickerSelectedValueChangedEventArgs
  public class DropDownButton : Button
  public class DropDownButtonAutomationPeer : ButtonAutomationPeer, IExpandCollapseProvider
  public class Frame : ContentControl, INavigate {
    bool IsNavigationStackEnabled { get; set; }
    public static DependencyProperty IsNavigationStackEnabledProperty { get; }
    bool NavigateToType(TypeName sourcePageType, object parameter, FrameNavigationOptions navigationOptions);
  }
  public class Grid : Panel {
    BackgroundSizing BackgroundSizing { get; set; }
    public static DependencyProperty BackgroundSizingProperty { get; }
  }
  public class IconSourceElement : IconElement
  public interface IScrollAnchorProvider
  public class MenuBar : Control
  public class MenuBarItem : Control
  public class MenuBarItemFlyout : MenuFlyout
  public class NavigationView : ContentControl {
    UIElement ContentOverlay { get; set; }
    public static DependencyProperty ContentOverlayProperty { get; }
    bool IsPaneVisible { get; set; }
    public static DependencyProperty IsPaneVisibleProperty { get; }
    NavigationViewOverflowLabelMode OverflowLabelMode { get; set; }
    public static DependencyProperty OverflowLabelModeProperty { get; }
    UIElement PaneCustomContent { get; set; }
    public static DependencyProperty PaneCustomContentProperty { get; }
    NavigationViewPaneDisplayMode PaneDisplayMode { get; set; }
    public static DependencyProperty PaneDisplayModeProperty { get; }
    UIElement PaneHeader { get; set; }
    public static DependencyProperty PaneHeaderProperty { get; }
    NavigationViewSelectionFollowsFocus SelectionFollowsFocus { get; set; }
    public static DependencyProperty SelectionFollowsFocusProperty { get; }
    NavigationViewShoulderNavigationEnabled ShoulderNavigationEnabled { get; set; }
    public static DependencyProperty ShoulderNavigationEnabledProperty { get; }
    NavigationViewTemplateSettings TemplateSettings { get; }
    public static DependencyProperty TemplateSettingsProperty { get; }
  }
  public class NavigationViewItem : NavigationViewItemBase {
    bool SelectsOnInvoked { get; set; }
    public static DependencyProperty SelectsOnInvokedProperty { get; }
  }
  public sealed class NavigationViewItemInvokedEventArgs {
    NavigationViewItemBase InvokedItemContainer { get; }
    NavigationTransitionInfo RecommendedNavigationTransitionInfo { get; }
  }
  public enum NavigationViewOverflowLabelMode
  public enum NavigationViewPaneDisplayMode
  public sealed class NavigationViewSelectionChangedEventArgs {
    NavigationTransitionInfo RecommendedNavigationTransitionInfo { get; }
    NavigationViewItemBase SelectedItemContainer { get; }
  }
  public enum NavigationViewSelectionFollowsFocus
  public enum NavigationViewShoulderNavigationEnabled
  public class NavigationViewTemplateSettings : DependencyObject
  public class Panel : FrameworkElement {
    BrushTransition BackgroundTransition { get; set; }
  }
  public sealed class PasswordBox : Control {
    bool CanPasteClipboardContent { get; }
    public static DependencyProperty CanPasteClipboardContentProperty { get; }
    object Description { get; set; }
    public static DependencyProperty DescriptionProperty { get; }
    FlyoutBase SelectionFlyout { get; set; }
    public static DependencyProperty SelectionFlyoutProperty { get; }
    void PasteFromClipboard();
  }
  public class RelativePanel : Panel {
    BackgroundSizing BackgroundSizing { get; set; }
    public static DependencyProperty BackgroundSizingProperty { get; }
  }
  public class RichEditBox : Control {
    object Description { get; set; }
    public static DependencyProperty DescriptionProperty { get; }
    FlyoutBase ProofingMenuFlyout { get; }
    public static DependencyProperty ProofingMenuFlyoutProperty { get; }
    FlyoutBase SelectionFlyout { get; set; }
    public static DependencyProperty SelectionFlyoutProperty { get; }
    RichEditTextDocument TextDocument { get; }
    event TypedEventHandler<RichEditBox, RichEditBoxSelectionChangingEventArgs> SelectionChanging;
  }
  public sealed class RichEditBoxSelectionChangingEventArgs
  public sealed class RichTextBlock : FrameworkElement {
    FlyoutBase SelectionFlyout { get; set; }
    public static DependencyProperty SelectionFlyoutProperty { get; }
    void CopySelectionToClipboard();
  }
  public sealed class ScrollContentPresenter : ContentPresenter {
    bool CanContentRenderOutsideBounds { get; set; }
    public static DependencyProperty CanContentRenderOutsideBoundsProperty { get; }
    bool SizesContentToTemplatedParent { get; set; }
    public static DependencyProperty SizesContentToTemplatedParentProperty { get; }
  }
  public sealed class ScrollViewer : ContentControl, IScrollAnchorProvider {
    bool CanContentRenderOutsideBounds { get; set; }
    public static DependencyProperty CanContentRenderOutsideBoundsProperty { get; }
    UIElement CurrentAnchor { get; }
    double HorizontalAnchorRatio { get; set; }
    public static DependencyProperty HorizontalAnchorRatioProperty { get; }
    bool ReduceViewportForCoreInputViewOcclusions { get; set; }
    public static DependencyProperty ReduceViewportForCoreInputViewOcclusionsProperty { get; }
    double VerticalAnchorRatio { get; set; }
    public static DependencyProperty VerticalAnchorRatioProperty { get; }
    event TypedEventHandler<ScrollViewer, AnchorRequestedEventArgs> AnchorRequested;
    public static bool GetCanContentRenderOutsideBounds(DependencyObject element);
    void RegisterAnchorCandidate(UIElement element);
    public static void SetCanContentRenderOutsideBounds(DependencyObject element, bool canContentRenderOutsideBounds);
    void UnregisterAnchorCandidate(UIElement element);
  }
  public class SplitButton : ContentControl
  public class SplitButtonAutomationPeer : FrameworkElementAutomationPeer, IExpandCollapseProvider, IInvokeProvider
  public sealed class SplitButtonClickEventArgs
  public class StackPanel : Panel, IInsertionPanel, IScrollSnapPointsInfo {
    BackgroundSizing BackgroundSizing { get; set; }
    public static DependencyProperty BackgroundSizingProperty { get; }
  }
  public sealed class TextBlock : FrameworkElement {
    FlyoutBase SelectionFlyout { get; set; }
    public static DependencyProperty SelectionFlyoutProperty { get; }
    void CopySelectionToClipboard();
  }
  public class TextBox : Control {
    bool CanPasteClipboardContent { get; }
    public static DependencyProperty CanPasteClipboardContentProperty { get; }
    bool CanRedo { get; }
    public static DependencyProperty CanRedoProperty { get; }
    bool CanUndo { get; }
    public static DependencyProperty CanUndoProperty { get; }
    object Description { get; set; }
    public static DependencyProperty DescriptionProperty { get; }
    FlyoutBase ProofingMenuFlyout { get; }
    public static DependencyProperty ProofingMenuFlyoutProperty { get; }
    FlyoutBase SelectionFlyout { get; set; }
    public static DependencyProperty SelectionFlyoutProperty { get; }
    event TypedEventHandler<TextBox, TextBoxSelectionChangingEventArgs> SelectionChanging;
    void ClearUndoRedoHistory();
    void CopySelectionToClipboard();
    void CutSelectionToClipboard();
    void PasteFromClipboard();
    void Redo();
    void Undo();
  }
  public sealed class TextBoxSelectionChangingEventArgs
  public class TextCommandBarFlyout : CommandBarFlyout
  public class TimePicker : Control {
    IReference<TimeSpan> SelectedTime { get; set; }
    public static DependencyProperty SelectedTimeProperty { get; }
    event TypedEventHandler<TimePicker, TimePickerSelectedValueChangedEventArgs> SelectedTimeChanged;
  }
  public sealed class TimePickerSelectedValueChangedEventArgs
  public class ToggleSplitButton : SplitButton
  public class ToggleSplitButtonAutomationPeer : FrameworkElementAutomationPeer, IExpandCollapseProvider, IToggleProvider
  public sealed class ToggleSplitButtonIsCheckedChangedEventArgs
  public class ToolTip : ContentControl {
    IReference<Rect> PlacementRect { get; set; }
    public static DependencyProperty PlacementRectProperty { get; }
  }
  public class TreeView : Control {
    bool CanDragItems { get; set; }
    public static DependencyProperty CanDragItemsProperty { get; }
    bool CanReorderItems { get; set; }
    public static DependencyProperty CanReorderItemsProperty { get; }
    Style ItemContainerStyle { get; set; }
    public static DependencyProperty ItemContainerStyleProperty { get; }
    StyleSelector ItemContainerStyleSelector { get; set; }
    public static DependencyProperty ItemContainerStyleSelectorProperty { get; }
    TransitionCollection ItemContainerTransitions { get; set; }
    public static DependencyProperty ItemContainerTransitionsProperty { get; }
    object ItemsSource { get; set; }
    public static DependencyProperty ItemsSourceProperty { get; }
    DataTemplate ItemTemplate { get; set; }
    public static DependencyProperty ItemTemplateProperty { get; }
    DataTemplateSelector ItemTemplateSelector { get; set; }
    public static DependencyProperty ItemTemplateSelectorProperty { get; }
    event TypedEventHandler<TreeView, TreeViewDragItemsCompletedEventArgs> DragItemsCompleted;
    event TypedEventHandler<TreeView, TreeViewDragItemsStartingEventArgs> DragItemsStarting;
    DependencyObject ContainerFromItem(object item);
    DependencyObject ContainerFromNode(TreeViewNode node);
    object ItemFromContainer(DependencyObject container);
    TreeViewNode NodeFromContainer(DependencyObject container);
  }
  public sealed class TreeViewCollapsedEventArgs {
    object Item { get; }
  }
  public sealed class TreeViewDragItemsCompletedEventArgs
  public sealed class TreeViewDragItemsStartingEventArgs
  public sealed class TreeViewExpandingEventArgs {
    object Item { get; }
  }
  public class TreeViewItem : ListViewItem {
    bool HasUnrealizedChildren { get; set; }
    public static DependencyProperty HasUnrealizedChildrenProperty { get; }
    object ItemsSource { get; set; }
    public static DependencyProperty ItemsSourceProperty { get; }
  }
  public sealed class WebView : FrameworkElement {
    event TypedEventHandler<WebView, WebViewWebResourceRequestedEventArgs> WebResourceRequested;
  }
  public sealed class WebViewWebResourceRequestedEventArgs
}
namespace Windows.UI.Xaml.Controls.Maps {
  public enum MapTileAnimationState
  public sealed class MapTileBitmapRequestedEventArgs {
    int FrameIndex { get; }
  }
 public class MapTileSource : DependencyObject {
    MapTileAnimationState AnimationState { get; }
    public static DependencyProperty AnimationStateProperty { get; }
    bool AutoPlay { get; set; }
    public static DependencyProperty AutoPlayProperty { get; }
    int FrameCount { get; set; }
    public static DependencyProperty FrameCountProperty { get; }
    TimeSpan FrameDuration { get; set; }
    public static DependencyProperty FrameDurationProperty { get; }
    void Pause();
    void Play();
    void Stop();
  }
  public sealed class MapTileUriRequestedEventArgs {
    int FrameIndex { get; }
  }
}
namespace Windows.UI.Xaml.Controls.Primitives {
  public class CommandBarFlyoutCommandBar : CommandBar
  public sealed class CommandBarFlyoutCommandBarTemplateSettings : DependencyObject
  public class FlyoutBase : DependencyObject {
    bool AreOpenCloseAnimationsEnabled { get; set; }
    public static DependencyProperty AreOpenCloseAnimationsEnabledProperty { get; }
    bool InputDevicePrefersPrimaryCommands { get; }
    public static DependencyProperty InputDevicePrefersPrimaryCommandsProperty { get; }
    bool IsOpen { get; }
    public static DependencyProperty IsOpenProperty { get; }
    FlyoutShowMode ShowMode { get; set; }
    public static DependencyProperty ShowModeProperty { get; }
    public static DependencyProperty TargetProperty { get; }
    void ShowAt(DependencyObject placementTarget, FlyoutShowOptions showOptions);
  }
  public enum FlyoutPlacementMode {
    Auto = 13,
    BottomEdgeAlignedLeft = 7,
    BottomEdgeAlignedRight = 8,
    LeftEdgeAlignedBottom = 10,
    LeftEdgeAlignedTop = 9,
    RightEdgeAlignedBottom = 12,
    RightEdgeAlignedTop = 11,
    TopEdgeAlignedLeft = 5,
    TopEdgeAlignedRight = 6,
  }
  public enum FlyoutShowMode
  public class FlyoutShowOptions
  public class NavigationViewItemPresenter : ContentControl
}
namespace Windows.UI.Xaml.Core.Direct {
  public interface IXamlDirectObject
  public sealed class XamlDirect
  public struct XamlDirectContract
  public enum XamlEventIndex
  public enum XamlPropertyIndex
  public enum XamlTypeIndex
}
namespace Windows.UI.Xaml.Hosting {
  public class DesktopWindowXamlSource : IClosable
  public sealed class DesktopWindowXamlSourceGotFocusEventArgs
  public sealed class DesktopWindowXamlSourceTakeFocusRequestedEventArgs
  public sealed class WindowsXamlManager : IClosable
  public enum XamlSourceFocusNavigationReason
  public sealed class XamlSourceFocusNavigationRequest
  public sealed class XamlSourceFocusNavigationResult
}
namespace Windows.UI.Xaml.Input {
  public sealed class CanExecuteRequestedEventArgs
  public sealed class ExecuteRequestedEventArgs
  public sealed class FocusManager {
    public static event EventHandler<GettingFocusEventArgs> GettingFocus;
    public static event EventHandler<FocusManagerGotFocusEventArgs> GotFocus;
    public static event EventHandler<LosingFocusEventArgs> LosingFocus;
    public static event EventHandler<FocusManagerLostFocusEventArgs> LostFocus;
  }
  public sealed class FocusManagerGotFocusEventArgs
  public sealed class FocusManagerLostFocusEventArgs
  public sealed class GettingFocusEventArgs : RoutedEventArgs {
    Guid CorrelationId { get; }
  }
  public sealed class LosingFocusEventArgs : RoutedEventArgs {
    Guid CorrelationId { get; }
  }
  public class StandardUICommand : XamlUICommand
  public enum StandardUICommandKind
  public class XamlUICommand : DependencyObject, ICommand
}
namespace Windows.UI.Xaml.Markup {
  public sealed class FullXamlMetadataProviderAttribute : Attribute
  public interface IXamlBindScopeDiagnostics
  public interface IXamlType2 : IXamlType
}
namespace Windows.UI.Xaml.Media {
  public class Brush : DependencyObject, IAnimationObject {
    void PopulatePropertyInfo(string propertyName, AnimationPropertyInfo propertyInfo);
    virtual void PopulatePropertyInfoOverride(string propertyName, AnimationPropertyInfo animationPropertyInfo);
  }
}
namespace Windows.UI.Xaml.Media.Animation {
  public class BasicConnectedAnimationConfiguration : ConnectedAnimationConfiguration
  public sealed class ConnectedAnimation {
    ConnectedAnimationConfiguration Configuration { get; set; }
  }
  public class ConnectedAnimationConfiguration
  public class DirectConnectedAnimationConfiguration : ConnectedAnimationConfiguration
  public class GravityConnectedAnimationConfiguration : ConnectedAnimationConfiguration
  public enum SlideNavigationTransitionEffect
  public sealed class SlideNavigationTransitionInfo : NavigationTransitionInfo {
    SlideNavigationTransitionEffect Effect { get; set; }
    public static DependencyProperty EffectProperty { get; }
  }
}
namespace Windows.UI.Xaml.Navigation {
  public class FrameNavigationOptions
}
namespace Windows.Web.UI {
  public interface IWebViewControl2
  public sealed class WebViewControlNewWindowRequestedEventArgs {
    IWebViewControl NewWindow { get; set; }
    Deferral GetDeferral();
  }
  public enum WebViewControlPermissionType {
    ImmersiveView = 6,
  }
}
namespace Windows.Web.UI.Interop {
  public sealed class WebViewControl : IWebViewControl, IWebViewControl2 {
    event TypedEventHandler<WebViewControl, object> GotFocus;
    event TypedEventHandler<WebViewControl, object> LostFocus;
    void AddInitializeScript(string script);
  }
}

Removals:

namespace Windows.Gaming.UI {
  public sealed class GameMonitor
  public enum GameMonitoringPermission
}

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