Kategorie: Microsoft Azure

Microsoft is expanding the Azure Stack Edge with NVIDIA GPU preview

We’re expanding the Microsoft Azure Stack Edge with NVIDIA T4 Tensor Core GPU preview during the GPU Technology Conference (GTC Digital). Azure Stack Edge is a cloud-managed appliance that brings Azure’s compute, storage, and machine learning capabilities to the edge for fast local analysis and insights. With the included NVIDIA GPU, you can bring hardware acceleration to a diverse set of machine learning (ML) workloads.

What’s new with Azure Stack Edge

At Mobile World Congress in November 2019, we announced a preview of the NVIDIA GPU version of Azure Stack Edge and we’ve seen incredible interest in the months that followed. Customers in industries including retail, manufacturing, and public safety are using Azure Stack Edge to bring Azure capabilities into the physical world and unlock scenarios such as the real-time processing of video powered by Azure Machine Learning.

These past few months, we’ve taken our customers' feedback to make key improvements and are excited to make our preview available to even more customers today.

If you’re not already familiar with Azure Stack Edge, here are a few of the benefits:

Azure Machine Learning: Build and train your model in the cloud, then deploy it to the edge for FPGA or GPU-accelerated inferencing.
Edge Compute: Run IoT, AI, and business applications in containers at your location. Use these to interact with your local systems, or to pre-process your data before it transfers to Azure.
Cloud Storage Gateway: Automatically transfer data between the local appliance and your Azure Storage account.  Azure Stack Edge caches the hottest data locally and speaks file and object protocols to your on-prem applications.
Azure-managed appliance: Easily order and manage Azure Stack Edge from the Azure Portal.  No initial capex fees; pay as you go, just like any other Azure service.

Enabling our partners to bring you world-class business applications

Equally important to bringing you a great device is enabling our partners to bring you innovative applications to meet your business needs.  We’d love to share some of the continued investment we’re making with partners to bring their exciting developments to you.

As self-checkouts grow in prevalence, Malong Technologies is innovating in AI applications for loss prevention.

“For our customers in the retail industry, artificial intelligence innovation is happening at the edge,” said Matt Scott, co-founder and chief executive officer, Malong Technologies. “Along with our state-of-the-art solutions, our customers need hardware that is powerful, reliable, and custom-tailored for the cloud. Microsoft’s Azure Stack Edge fits the bill perfectly. We’re proud to be a Microsoft Gold Certified Partner, working with Microsoft to help our retail customers succeed.”

Increasing your manufacturing organization’s quality inspection accuracy is key to Mariner’s Spyglass Visual Inspection application.

“Mariner has standardized on Microsoft’s Azure Stack Edge for our Spyglass Visual Inspection and Spyglass Connected Factory products. These solutions are mission critical to our manufacturing customers. Azure Stack Edge provides the performance, stability and availability they require.” – Phil Morris, CEO, Mariner

Building computer vision solutions to improve performance and safety in manufacturing and other industries is a key area of innovation for XXII.

“XXII is thrilled to be a Microsoft partner and we are working together to provide our clients with real time video analysis software on edge with the Azure Stack Edge box. With this solution, Azure allow us to harvest the full potential of NVIDIA GPUs directly on edge and be able to provide our clients in retail, industry and smart city with smart video analysis that are easily deployable, scalable and easily manageable with Azure stack Edge.” – Souheil Hanoune, Chief Scientific Officer, XXII

More to come with Azure Stack Edge

There are even more exciting developments with Azure Stack Edge coming. We’re putting the final touches on much-awaited new compute and AI capabilities including virtual machines, Kubernetes clusters, and multi-node support. Along with these new features announced at Ignite 2019, Data Box Edge was renamed Azure Stack Edge to align with the Azure Stack portfolio.

Our Rugged series for sites with harsh or remote environments is also coming this year, including the battery-powered form-factor that can be carried in a backpack. The versatility of these Azure Stack Edge form-factors and cloud-managed capabilities brings cloud intelligence and compute to retail stores, factory floors, hospitals, field operations, disaster zones, and rescue operations.

Get started with the Azure Stack Edge with NVIDIA GPU preview

Thank you for continuing to partner with us as we bring new capabilities to Azure Stack Edge. We’re looking forward to hearing from you.

To get started with the preview, please email us and we’ll follow up to learn more about your scenarios.
Learn more about Azure Stack Edge.

Learn more about Azure’s Hybrid Strategy

Read about more updates from Azure during NVIDIA’s GTC.
Quelle: Azure

How Azure Machine Learning service powers suggested replies in Outlook

Microsoft 365 applications are so commonplace that it’s easy to overlook some of the amazing capabilities that are enabled with breakthrough technologies, including artificial intelligence (AI). Microsoft Outlook is an email client that helps you work efficiently with email, calendar, contacts, tasks, and more in a single place.

To help users be more productive and deliberate in their actions while emailing, the web version of Outlook and the Outlook for iOS and Android app have introduced suggested replies, a new feature powered by Azure Machine Learning service. Now when you receive an email message that can be answered with a quick response, Outlook on the web and the Outlook mobile suggest three response options that you can use to reply with only a couple of clicks or taps, helping people communicate in both their workplace and personal life, by reducing the time and effort involved in replying to an email.

The developer team behind suggested replies is comprised of data scientists, designers, and machine learning engineers with diverse backgrounds who are working to improve the lives of Microsoft Outlook users by expediting and simplifying communications. They are at the forefront of applying cutting-edge natural language processing (NLP) and machine learning (ML) technologies and leverage these technologies to understand how users communicate through email and improve those interactions from a productivity standpoint to create a better experience for users.

A peek under the hood

To process the massive amount of raw data that these interactions provide, the team uses Azure Machine Learning pipelines to build their training models. Azure Machine Learning pipelines allow the team to divide training steps into discrete steps such as data cleanup, transforms, feature extraction, training, and evaluation. The output of the Azure Machine Learning pipeline converts raw data into a model. This Machine Learning pipeline allows the data scientists to build a training pipeline in a compliant manner that enforces privacy and compliance checks.

In order to train this model, the team needed a way to build and prepare a large data set comprised of over 100 million messages. To do this, the team leveraged a distributed processing framework to sample and retrieve data from a broad user base.

Azure Data Lake Storage is used to store the training data used for training the suggested replies models. We then clean and curate the data into message reply pairs (including potential responses to an email) that are stored in Azure Data Lake Storage (ADLS). The training pipelines also consume the reply pairs stored in ADLS in order to train models. To conduct the Machine Learning training itself, the team uses GPU pools available in Azure. The training pipelines leverage these curated Message Reply pairs to learn how to suggest appropriate replies based on a given message. Once the model is created, data scientists can compare the model performance with previous models and evaluate which approaches perform better at recommending relevant suggested replies.

The Outlook team helps protect your data by using the Azure platform to prepare large-scale data sets that are required to build a feature like suggested replies in accordance with Office 365 compliance standards. The data scientists use Azure compute and workflow solutions that enforce privacy policies to create experiments and train multiple models on GPUs. This helps with the overall developer experience and provides agility in the inner development loop cycle.

This is just one of many examples of how Microsoft products are powered by the breakthrough capabilities of Azure AI to create better user experiences. The team is learning from feedback every day and improving the feature for users while also expanding the types of suggested replies offered. Keep following the Azure blog to stay up-to-date with the team and be among the first to know when this feature is released.

Learn more

Learn more about the Azure Machine Learning service.

Get started with a free trial of Azure Machine Learning service.
Quelle: Azure

New Deploy to Azure extension for Visual Studio Code

Organizations and teams that adopt DevOps methodologies are consistently seeing improvements in their ability to deliver high-quality code, with faster release cycles, and ultimately achieve higher level of satisfaction for their own customers, whether they’re internal or external. Continuous Integration and Continuous Delivery (CI/CD) is one of the pillars of DevOps, consisting in automatically building, testing and deploying applications, but setting up a full CI/CD pipeline can be a complex task.

Today, we’re sharing the launch of the Deploy to Azure extension for Visual Studio Code. This new extension allows developers working in Visual Studio Code to seamlessly create, build, and deploy their apps in a continuous manner to the cloud, without leaving the editor.

Deploy to Azure extension

The Deploy to Azure extension works with both GitHub Actions and Azure Pipelines. It helps developers by auto-generating a CI/CD pipeline definition that takes care of building and deploying your app to the cloud with Azure. You can use Deploy to Azure extension to deploy application code present in your local system, or in Azure Repos or GitHub. We plan to expand the scope to other Git repositories in future.

You can use this extension to set up CI/CD pipeline for every code push. It will give you an auto-generated and fully-customizable CI/CD pipeline, defined in a YAML file that is formatted for either GitHub Actions or Azure Pipelines. The YAML file is pre-populated with build and release tasks, which can be edited by the developers as needed.

In the workflow, we are also setting up Azure Pipelines and GitHub with relevant Azure-related configurations, as well as repository-related configurations, without you needing to do worry about the plumbing of the systems.

Installation and usage

The Deploy to Azure extension can be downloaded for free from the Visual Studio Code Marketplace. After installing it, you can invoke it from the Command Palette (Ctrl + P or Cmd + P) > Deploy to Azure: Configure Pipeline.

Once you run the pipeline creation workflow, the extension will inspect your application’s code and generate a pipeline optimized for your project.

In this first release, the Deploy to Azure extension in Visual Studio Code supports generating pipelines to deploy Node.js-based apps to Azure App Service or Azure Functions App, as well as any containerized application (with a Dockerfile) to Azure Kubernetes Service.

We’re working on adding support for creating workflows for other languages, starting with Python, and for other Azure resources. Additionally, we will roll out support for other Git repository providers; in addition to GitHub and Azure Repos which are available today, we’re working on supporting source code on BitBucket and other locations.

We will also roll out support for other Git repository providers; in addition to GitHub and Azure Repos which are available today, we’re working on supporting source code on BitBucket and other locations.

Get started

You can get started today by installing the extension. Then, start adding CI/CD pipelines to your apps and have them deployed to the cloud continuously.

Please let us know your thoughts on this extension and how it helps your workflows, and anything we can do to improve your experience. You can connect with us on the extension’s project page on GitHub.
Quelle: Azure

Unified network monitoring with Connection Monitor now in preview

Azure Network Watcher’s new and improved Connection Monitor now provides unified end-to-end connection monitoring capabilities for hybrid and Azure deployments. Users can now use the same solution to monitor connectivity for on-premises, Azure, and multi-cloud setups. In this preview phase, the solution brings together the best of two key capabilities—Network Watcher's Connection Monitor and Network Performance Monitor's (NPM) Service Connectivity Monitor. Check out the documentation and start using Connection Monitor to check connectivity in your network.

The monitoring question

Customers have long stressed over the need for unified connection monitoring for hybrid deployments, where complex applications transact across Azure, on-premises, and with other public applications to deliver business-critical functionality. These challenges escalate in multi-cloud environments. Monitoring teams then wrestle with basic challenges including:

Which monitoring solution to use in these complex set-ups?
Do I need different monitoring solutions for on-premises and Azure or any other clouds?
Where does my data go and how do I correlate data from multiple sources?
How do I get the fastest alerts when things go wrong in my network?

Connection Monitor in preview

With the new Connection Monitor, you can now configure both Azure and non-Azure virtual machines and hosts for monitoring connectivity to global endpoints from a single console. You can set up Connection Monitor and create multiple test groups for various use cases including connectivity between Azure regions, connectivity to Office 365, and connectivity between app and database tiers. With the ability to add multiple sources and destinations in one test group, configuring monitoring gets much easier. You also benefit from an aggregated view of your network parameters, with the ability to drill down to individual links at the time of troubleshooting.

You can monitor loss and latency of network connections both within Azure and between Azure and external destinations, and view the topology to localize issues. The solution identifies the top five tests in your Connection Monitor, test groups, sources, and destinations, then highlights potential problem tests. For Azure resources, issues with your hops are shown in the topology.

Alerts and data storage

Monitoring data is stored in both Azure Monitor as metrics and in Log Analytics workspaces. You can now set up fast, metrics-based alerts to react to issues expeditiously. To build additional correlations on your historical data, use Log Analytics queries.

Other benefits

Single console for configuring and monitoring connectivity and network quality from Azure and on-premises virtual machines and hosts.
Monitor multiple endpoints within and across Azure regions, on-premises sites, and global service locations.
Higher and configurable probing frequencies.
More protocols supported to give better visibility into network performance.
Cross-region, cross-workspace monitoring.
Access to historical monitoring data retained in Log Analytics.
Rich user experience.
Automation through PowerShell and CLI.

Start monitoring today

The new Connection Monitor feature will be available for no charge during preview. The general availability pricing for Connection Monitor will be available soon on the pricing page. For more details, please visit the Connection Monitor (Preview) documentation.

We're here for you

We would love to hear from you. Send us your suggestions via the User Voice page.
Quelle: Azure

New features for Form Recognizer now available

Extracting text and structure information from documents is a core enabling technology for robotic process automation and workflow automation. Since its preview release in May 2019, Azure Form Recognizer has attracted thousands of customers to extract text, key and value pairs, and tables from documents to accelerate their business processes.

Today, we're sharing the new Form Recognizner features that are available.

Updates for Azure Form Recognizer

The Form Recognizer March release is a major update that includes many new features our customers have asked for:

Customization: The service now supports training with and without labels, which makes it easier for customers to reliably extract valuable information from their forms. The APIs have also been redesigned as long-running operations to improve support for larger customer data sets. Automatic detection of key value pairs and table extraction have been enhanced and improved. A new sample labeling tool UX container will help customers label data more efficiently and extract the values of interest.
  

Form Recognizer Custom: Train with Labels, Form Recognizer Sample Labeling Tool.

In addition, Form Recognizer Sample Labeling Tool is now available as an open source project located here. You can integrate it within your solutions and make customer-specific changes to meet your needs.

Layout: We released a new Layout API that is capable of extracting text and tables from documents with high accuracy optical character recognition (OCR) results on small texts. It also extracts tables from arbitrary documents, enabling a very popular application scenario for document extraction.

Layout text and table extraction: Table extracted with 5 columns and 30 rows.

Pre-Built Receipt: The new version features major accuracy improvements. Error rates for certain fields like merchant name, phone number, transaction time, and subtotal have been reduced by more than 30 percent. We also added support for recognizing tips, receipt type, and line items, as well as providing confidence values.
   

Pre-built Receipt: Key fields extracted from itemized sales receipt.

Learn more on what’s new in Form Recognizer here.

Our customers

Acumatica and Zelros are customers using Azure Form Recognizer and have shared their experiences with Microsoft.

“By automating expense reporting with Form Recognizer, we can eliminate almost all human errors—which really helps accounting teams streamline approvals and reimbursement.“ Ajoy Krishnamoorthy, Vice President of Platform and Technology Acumatica.

Learn more in our case study with Acumatica here.

“Zelros Documents2Insights leverages Form Recognizer to speed up the insurers' and bancassurers’ underwriting process. Identity card, proof of residence, vehicle registration document, driving license, and more. Speeding up and simplifying this business process is key to improve the experience of policyholders. Zelros Documents2Insights automates the underwriting processes, based on the Cognitive Services Computer Vision API and built on top of the Form Recognizer feature, the solution automatically reads and analyzes documents. It also cross-references information in order to correct and lower the error rate, while complying with regulatory requirements. With this, we are to process documents and subscriptions faster.”  Fabien Vauchelles, CTO of Zelros

Getting started

To get started, please login to the Azure Portal to create a Form Recognizer resource. Once your resource is created you can extract data from your forms by following one of our Quickstart templetes:

Custom: Train a custom model for your forms to extract text, key value pairs, and tables.

Train without labels:

Quickstart: Train a Form Recognizer model and extract form data by using the REST API with cURL.
Quickstart: Train a Form Recognizer model and extract form data by using the REST API with Python.

Train with labels:

Quickstart: Train a Form Recognizer model with labels using the sample labeling tool.
Quickstart: Train a Form Recognizer model with labels using REST API and Python.

Prebuilt receipts: Extract data from USA sales receipts.

Quickstart: Extract receipt data using the REST API with cURL.
Quickstart: Extract receipt data using the REST API with Python.

Layout: Extract text and table structure (row and column numbers) from your documents.

 Quickstart: Extract layout data using the REST API with Python.

Quelle: Azure

Learn new strategies and technologies to optimize your hybrid cloud

IT environments are becoming more complex as organizations are combining on-premises, cloud, and edge infrastructures. There are some major benefits to having a flexible, hybrid IT environment, such as the ability to create new business value while also meeting local and industry compliance requirements, but the headaches of managing and securing these environments are hard to ignore. But, with a solid strategy and the right tools, there’s enormous potential for innovation and growth with a hybrid environment.

This is why we're sharing the upcoming one-hour Azure Hybrid Virtual Event on Tuesday, March 31, 2020 starting at 8:00 AM Pacific Time. At this free online event, you’ll get to watch demos, learn hybrid best practices, and find out which strategies work—and which don’t—from two real Azure hybrid customers: online retailer ASOS and professional services company KPMG. Julia White, Corporate Vice President of Microsoft Azure Marketing, will kick off the event with a keynote on current and future hybrid cloud trends, followed by some great sessions:

Insights from Bain & Company—building a successful hybrid cloud: Hear from Bill Radzevych, a partner at Bain & Company, about market trends and customer insights with digital transformation and cloud adoption. 
Seamlessly manage and govern resources: Learn how to seamlessly manage, govern, and secure resources across on-premises, multicloud, and the edge from a single control plane.
Bring cloud services to any infrastructure: Learn how to bring cloud services to your existing infrastructure to take advantage of cloud innovation everywhere and discuss real-world examples from companies like KPMG.
Modernize your datacenter: Learn how to modernize virtualized apps or bring cloud to your datacenter while meeting regulatory and data sovereignty requirements.
Bring AI to the edge: Learn about different ways to take advantage of edge computing to create new business opportunities.
Secure your organization: Hear from George Mudie, Chief Information Security Officer from ASOS, on how Azure Sentinel empowers their SecOps to improve organizational security and efficiency.

 

See you there

Azure Hybrid Virtual Event: Tuesday, March 31, 2020 from 8:00 AM to 9:00 AM Pacific Time.

Delivered in partnership with Intel.

Quelle: Azure

Announcing the general availability of Azure Monitor for virtual machines

Today we're announcing the general availability of Azure Monitor for virtual machines (VMs), which provides an in-depth view of VM performance trends and dependencies. You can access Azure Monitor for VMs from the Azure VM resource blade to view details about a single VM, from the Azure Virtual Machine Scale Sets (VMSS) resource blade to view details about a single VM scale set, and from Azure Monitor to understand compute issues at scale.

Azure Monitor for VMs brings together key monitoring data about your Windows and Linux VMs, allowing you to:

Troubleshoot guest-level performance issues and understand trends in VM resource utilization.
Determine whether back-end VM dependencies are connected properly and which clients of a VM may be affected by any issues the VM is having.
Discover VM hotspots at scale based on resource utilization, connection metrics, performance trends, and alerts.

Performance

Performance views are powered by Log Analytics, and offer powerful aggregation and filtering capabilities including “Top N” VM sorting and searching across subscriptions and regions, aggregation of VM metrics (such as average memory) across all VMs in a resource group across regions, percentiles of performance values over time, and breakdown and selection of VM Scale Set instances.

It can be challenging to monitor thousands of VMs. Our performance views were created to address this problem. You can use them to figure out which VMs are resource constrained, which ones are having logical disk or memory consumption issues, or to get performance diagnostics.

Maps

Azure Monitor for VMs includes dependency maps powered by the Service Map dependency agent extension. Maps deliver an Azure-centric user experience, with VM resource blade integration, Azure metadata, and dependency maps for Resource Groups and Subscriptions. Maps show how VMs and processes are interacting and can identify dependencies on third party services. Azure Monitor for VMs also monitors connection failures, live connection counts, network bytes sent and received by process, and service-level latency.

In addition to the visual experience and group-level mapping in the user experience, you can query the data sets in Log Analytics to alert on spikes in network traffic from selected workloads, query at scale for failed dependencies, and plan Azure migrations from on-premises VMs by analyzing connections over weeks or months. To assist in this analysis we offer several workbooks that provide tabular views into this rich network data set.

 

Getting started

To get started with an Azure resource, go to the resource blade for your VM or VM scale set and click on Insights in the Monitoring section. When you click Enable, you’ll be prompted to pick an existing Log Analytics workspace or create one.

Once you’re comfortable with the capabilities on a few VMs, you can view VMs at scale in Azure Monitor under Virtual Machines, and on-board to entire resource groups and subscriptions using our Get Started page, Azure Policy, or Powershell.

Check out our full documentation to get more details. Pricing is based on data ingestion and retention to your Log Analytics workspace. We’d love to hear what you like and don’t like about Azure Monitor for VMs, and where you’d like us to take it. Please click Provide Feedback in the user experience to share your thoughts.
Quelle: Azure

Azure Container Registry: Preview of customer-managed keys

The Azure Container Registry team is sharing the preview of customer-managed keys for data encryption at rest. Azure Container Registry already encrypts data at rest using service-managed keys. With the introduction of customer-managed keys you can supplement default encryption with an additional encryption layer using keys that you create and manage in Azure Key Vault. This additional encryption should help you meet your company’s regulatory or compliance needs.

Azure Container Registry encryption is supported through integration with Azure Key Vault. You can create your own encryption keys and store them in a Key Vault, or you can use Azure Key Vault API to generate encryption keys. With Azure Key Vault, you can also audit key usage.

During preview, customer-managed keys can only be enabled while creating a new registry in the Premium SKU. Enabling and disabling the feature on an existing registry will be available in an upcoming release.

With this release, you can try out the following scenarios on a customer-managed keys enabled registry:

Rotate the encryption keys using the Azure portal or the Azure command-line interface (CLI).
Geo-replicated registries and Virtual Network integration are supported.
You can enforce encryption for your registries through the built-in Azure Policy.

You can try out this feature using Azure Portal or the Azure CLI. For details, please see the documentation.

Availability and feedback

The Azure portal and CLI experience for customer-managed keys in Azure Container Registry are now in preview. As always, we love to hear your feedback on existing features as well as ideas for our product roadmap.

Roadmap: For visibility into our planned work.

UserVoice: To vote for existing requests or create a new request.

Issues: To view existing bugs and issues or log new ones.

ACR documents: For Azure Container Registry tutorials and documentation.
Quelle: Azure