Kategorie: Microsoft Azure

Azure Native Qumulo Scalable File Service provides seamless, secure data storage

The amount of data created and consumed is expected to grow exponentially over the next decade. This proliferation has radically changed enterprise data storage requirements. Today, enterprises are in search of storage solutions with unlimited capacity and performance scaling capabilities alongside their core requirements of data security and availability.

Azure cloud services have been the backbone for enterprises in their digital transformation journey. With Azure cloud services, enterprises can reduce storage costs and have access to high-availability storage products with disaster recovery capabilities. We are happy to announce that the storage suite of Azure products has grown with the addition of Azure Native Qumulo Scalable File Service. You can subscribe to this service via the Azure marketplace.

Qumulo is the industry leader in Distributed File System and Object Storage. Qumulo provides a highly scalable, highly performant, and simple-to-use cloud-native filesystem that supports a wide variety of data workloads via standard protocols (NFS, SMB, FTP, and S3). Azure Native Qumulo Scalable File Service provides seamless integration between Qumulo and Azure and enables Qumulo’s distributed file system as a native service on Azure.

“Our commitment to delivering simplicity at scale starts with the initial deployment and onboarding experience of our customers. The availability of the Azure Native Qumulo Scalable File Service directly from the Azure portal creates a more streamlined procurement process for customers looking to store and manage unstructured data in the cloud at massive scale." —Kiran Bhageshpur, CTO of Qumulo

Native integration means that customers can deploy Qumulo in less than 15 minutes. Customers no longer need to set up virtual network peering to connect to Qumulo. In fact, with this integration, virtual network peering charges have been eliminated, as Qumulo is connected via private access to the customer’s chosen virtual network. The data is stored and processed by the service in the same region as the virtual network and customers can easily leverage their own network policies with Qumulo’s enterprise-scale filesystem.

Azure Native Qumulo Scalable File Service provides the following key capabilities:

Seamless onboarding—Easily onboard and use Qumulo as a natively integrated service on Azure.
Unified billing—Get a single bill for all resources you consume on Azure, including the Qumulo service.
Private access to virtual network—The service is directly connected to your virtual network and provides access to a fully managed Qumulo Scalable File service from the virtual network of your choice.

“Azure Native ISV Services enables enterprises to provision and use select ISV solutions on Azure with a seamless, first-class experience. With the public preview launch of Azure Native Qumulo Scalable File Service, we expand Azure’s storage offerings with Qumulo’s exabyte-scale data service. With this integration, enterprises can easily create and manage a multi-petabyte-scale file system in a single namespace on Azure. We are really excited about partnering with Qumulo and integrating their data services into Azure" —Balan Subramanian, Partner Director of Product Management, Azure Developer Experiences

Get started with Azure Native Qumulo Scalable File Service:

1. Prerequisite—Create a delegated subnet in a virtual network of your choosing and add network security group details as per your enterprise policy.

2. Subscribe to Azure Native Qumulo Scalable File Service on the Azure Marketplace.

3. Seamlessly create a Qumulo resource by entering the required details about the file in the Basics tab.

4. In the Networking tab, provide the details of the virtual network and the previously created delegated subnet. Click on Review + create to create the filesystem.

Learn more

Marketplace offer: Azure Native Qumulo Scalable File Service.
Azure Native Qumulo Scalable File Service overview.
Sign up for Azure today.

Quelle: Azure

What's new in Azure Data & AI: Empowering retailers to streamline operations and accelerate time to value

The new year brings opportunity for thoughtful reflection about the past year, both personally and professionally. 2022 was a year of firsts for me—first time having clam chowder at Pike Place Market as a local, first time going shopping for heels with my daughter, and first time delivering an Azure keynote at Inspire as a Microsoft employee when pre-COVID-19, I was a Partner listening in the audience. And here is another first; the start of a new blog series where I plan to share more about noteworthy and inspiring data and AI innovations we are releasing across Microsoft. Given the National Retail Federation’s Big Show this week, I’ll also highlight how these innovations impact retail.

Let’s explore what’s new for Azure Data & AI this month:

Microsoft underscores resilient retail at NRF

A bellwether for economic and societal trends, the retail industry continues to be on the front line of adaptive innovation. And rather than trying to predict the future, retailers are working to achieve greater business agility necessary to thrive in it. This means that, like Majid Al Futtaim Retail, they automate tedious processes so employees can focus on higher-value tasks. Like Grupo Bimbo, they unify disparate data points in real time so that employees can access a central source of truth when and where they need it. And, like CCC Group, they stay laser-focused on delivering differentiated customer experiences to build loyal fans. Across each of these organizations, data is seen as an accelerant for growth, powering more personalized customer experiences, cost-efficient supply chains, and proactive responses to market trends.

Business agility requires people, processes, and technologies to work in harmony, and to align on how massive amounts of data are managed, analyzed, and actioned to respond to market demands. Increasingly, these efforts focus on driving sustainable growth that limits carbon emissions, for example by using machine learning to more accurately forecast demand to reduce excess inventory and waste.

We know cloud technologies like databases, containers, and AI can enable more accurate decisions, but it can be challenging to ensure these technologies speak to each other in the right way at the right time on a global scale. This is where Azure and the Microsoft Intelligent Data Platform—the description we use to refer to all of the Data & AI Azure products and services we offer shine. With managed databases like Cosmos DB, analytics services like Azure Synapse, and leading AI offerings, retailers can take advantage of the “by design” integration the Microsoft Intelligent Data Platform offers, which means they are able to invest more time in creating value rather than integrating and managing their data estate.

The Microsoft Intelligent Data Platform came to life through new immersive demo experiences this year at NRF and I’m going to briefly highlight what we showcased at the conference. Earlier this week at NRF, Microsoft’s Alysa Taylor and Shelley Bransten spoke on the topic of Resilient Retail and shared examples of organizations digitizing their businesses to do more with less. You can read more about their talks on our Industry blog.

Microsoft also met with customers at our NRF booth to discuss strategies for making sense of all their data. For example, these two demos highlight how tight integrations between data, analytics, and AI can help make resilient retail a reality.

Wide World Importers (WWI), a global supermarket chain, wants to maximize the value of their data estate. By using Azure Synapse pipelines with Cosmos DB, they get real time insights which are automatically shared with the right decision makers through tools like Azure Data Explorer and Power BI. They’re able to track their supply chain data in real time and use predictive AI to reduce costs. They’re also able to govern their data estate from a single application one pane of glass using Microsoft Purview.

Next, Wide World Importers taps into the power of Azure AI to build a more connected customer experience. They use Azure Form Recognizer to detect and redeem promotional offers. Azure Cognitive Search helps customers find product information more quickly by recognizing their search intent and helps WWI deliver more personalized recommendations. Pre-built AI capabilities, such as speech recognition and computer vision, also differentiate the shopping experience and provide a more accessible flow.

The general availability of Azure OpenAI Service 

As Eric Boyd mentioned in his blog, we announced the general availability of Azure OpenAI Service as part of our ongoing partnership with OpenAI. Azure OpenAI Service provides a commercialization platform for businesses to leverage advanced AI models like GPT-3.5, Codex, and DALL*E to create innovative applications. Customers of all sizes across industries are using Azure OpenAI Service to do more with less, improve experiences for end users, and streamline operational efficiencies. 

Microsoft Responsible AI Dashboard now available

The digitization of retail enables retailers to meet customer expectations with increasing precision, from providing personalized recommendations online to restocking inventory based on computer vision in physical stores. Shoppers expect the technology behind their retail experience to apply data and AI responsibly. In December, we began rolling out our new Responsible AI dashboard in Azure Machine Learning, which includes capabilities like fairness assessment, interpretability, error analysis, and causal inferencing. And today, we are excited to announce the general availability of the Microsoft Responsible AI dashboard. Retailers can leverage the Responsible AI dashboard to optimize the shopper’s experience as well as build trust and positive perception for their brands.

See how you can learn more about Responsible AI.

Full text search capabilities come to Azure Cosmos DB for Apache Cassandra

Azure Cosmos DB has seen tremendous momentum within the retail industry, given its ability to automatically and instantly scale when traffic is unpredictable without sacrificing performance or cost efficiency. Microsoft runs both the Windows store and Xbox Live on Azure Cosmos DB for this very purpose. This month, we’re announcing several performance enhancements to Azure Cosmos DB to make it easier and faster for developers to query data stores in Azure Cosmos DB. These include the ability to do full text searches in Azure Cosmos DB for Apache Cassandra through a native integration with Azure Cognitive Search, and support for GraphQL and REST through Data API builder.

For more technical detail about these and other updates to Azure Cosmos DB, visit our developer blog.

JSON support for Azure Cache for Redis Enterprise generally available

Support for JSON documents in Azure Cache for Redis Enterprise tiers, delivered via the RedisJSON module, has been made generally available as of November 2022. This turns Azure Cache for Redis Enterprise into a high-performance NoSQL document store and drives efficiency for developers to modernize their applications. The new RedisJSON module update is well suited to retail customers looking to store, search, and index product catalogs and shopper data via a single atomic operation.

To learn more on Azure Cache for Redis Enterprise and the RedisJSON module please check out the blog.

Microsoft named a Leader in the 2022 Gartner Magic Quadrant for Insight Engines

In December, Microsoft was named a leader in the 2022 Gartner Magic Quadrant for Insight Engines, which evaluates the capabilities of various vendors in the market for providing enterprise-scale search for app development. Organizations benefit, no matter the industry, but Cognitive Search is an exceptionally powerful tool for retailers, helping them to quickly find and analyze data related to customer behavior, sales, and inventory. It can also be used to personalize the shopping experience for individual customers based on their past interactions and preferences.

Learn more and download the report.

Customers innovating with Azure Data & AI

I’d like to close my inaugural “what’s new” blog post with my favorite way of making everything I’ve covered above actionable—by sharing examples of our customers succeeding. I share them as a way of helping spark the understanding—maybe even a little imagination—so that others can better envision how this amazing new Data & AI technology can be used in their own organizations.

I hope you enjoyed reading this month’s edition of what’s new in Azure Data & AI. We look forward to sharing more insights and inspiration in the months ahead. If you have a question or idea you’d like to hear perspective on, please share in the comments section.

Grupo Bimbo transforms the data analysis of commercial areas with Microsoft Solutions

Mexico—The global baking company carries out hundreds of thousands of transactions globally and needed a way for collaborators to quickly access and act on insights to improve sales. By adopting Power BI and Azure Synapse, Grupo Bimbo was able to unify internal and external data, increase business agility, and democratize insights for increased productivity across the organization. Read the full Case Study.

How online marketplace CDON used AI to become a market leader

Sweden—CDON began as a small online retailer of CDs, DVDs, and games and quickly became the Nordic’s largest online marketplace. When CDON realized legacy technologies were holding it back, the company looked to Azure to accelerate its innovation and scale. Now their developers use Azure Cognitive Search, Azure DevOps, and other services to better understand the user experience on their website and increase personalization for better performance. Read the full CDON Case Study.

How AEON Group increased profits and maximized inventory with data and AI

Japan—Since opening its first store in December 2005, Maibasuketto, a member of the AEON Group's supermarket business, has expanded its footprint at a pace of 100 stores every year. To ensure its growth was sustainable, the company embarked on an initiative to optimize store ordering and operations using Azure Cognitive Services, maximizing supply chain and inventory based on selling patterns throughout the day. Read the full AEON Group Case Study.

How Fashable reimagines fashion design with Azure Machine Learning and PyTorch

Portugal—Using Azure Machine Learning, Fashable created an AI application that generates original clothing designs to quickly get a pulse on consumer preferences. This helps fashion companies understand customer demand, get to market faster, and reduce clothing waste by only producing what they know will sell. Read the full Fashable Case Study.

WTW accelerates delivery time with Azure Migration and Analytics

United Kingdom—Operating in more than 140 countries with over 40,000 employees, Willis Towers Watson (WTW) has decades of experience working with the world’s largest loyalty programs. To efficiently govern the exponential growth in data for these programs and apply innovations in advanced analytics and AI, WTW moved its workload to Azure. Now their employees have more time to focus on uncovering insights for clients. Read the full WTW Case Study.

Quelle: Azure

General availability of Azure OpenAI Service expands access to large, advanced AI models with added enterprise benefits

Large language models are quickly becoming an essential platform for people to innovate, apply AI to solve big problems, and imagine what’s possible. Today, we are excited to announce the general availability of Azure OpenAI Service as part of Microsoft’s continued commitment to democratizing AI, and ongoing partnership with OpenAI.

With Azure OpenAI Service now generally available, more businesses can apply for access to the most advanced AI models in the world—including GPT-3.5, Codex, and DALL•E 2—backed by the trusted enterprise-grade capabilities and AI-optimized infrastructure of Microsoft Azure, to create cutting-edge applications. Customers will also be able to access ChatGPT—a fine-tuned version of GPT-3.5 that has been trained and runs inference on Azure AI infrastructure—through Azure OpenAI Service soon.

Empowering customers to achieve more

We debuted Azure OpenAI Service in November 2021 to enable customers to tap into the power of large-scale generative AI models with the enterprise promises customers have come to expect from our Azure cloud and computing infrastructure—security, reliability, compliance, data privacy, and built-in Responsible AI capabilities.

Since then, one of the most exciting things we’ve seen is the breadth of use cases Azure OpenAI Service has enabled our customers—from generating content that helps better match shoppers with the right purchases to summarizing customer service tickets, freeing up time for employees to focus on more critical tasks.

Customers of all sizes across industries are using Azure OpenAI Service to do more with less, improve experiences for end-users, and streamline operational efficiencies internally. From startups like Moveworks to multinational corporations like KPMG, organizations small and large are applying the capabilities of Azure OpenAI Service to advanced use cases such as customer support, customization, and gaining insights from data using search, data extraction, and classification.

“At Moveworks, we see Azure OpenAI Service as an important component of our machine learning architecture. It enables us to solve several novel use cases, such as identifying gaps in our customer’s internal knowledge bases and automatically drafting new knowledge articles based on those gaps. This saves IT and HR teams a significant amount of time and improves employee self-service. Azure OpenAI Service will also radically enhance our existing enterprise search capabilities and supercharge our analytics and data visualization offerings. Given that so much of the modern enterprise relies on language to get work done, the possibilities are endless—and we look forward to continued collaboration and partnership with Azure OpenAI Service."—Vaibhav Nivargi, Chief Technology Officer and Founder at Moveworks.

“Al Jazeera Digital is constantly exploring new ways to use technology to support our journalism and better serve our audience. Azure OpenAI Service has the potential to enhance our content production in several ways, including summarization and translation, selection of topics, AI tagging, content extraction, and style guide rule application. We are excited to see this service go to general availability so it can help us further contextualize our reporting by conveying the opinion and the other opinion.”—Jason McCartney, Vice President of Engineering at Al Jazeera.

“KPMG is using Azure OpenAI Service to help companies realize significant efficiencies in their Tax ESG (Environmental, Social, and Governance) initiatives. Companies are moving to make their total tax contributions publicly available. With much of these tax payments buried in IT systems outside of finance, massive data volumes, and incomplete data attributes, Azure OpenAI Service finds the data relationships to predict tax payments and tax type—making it much easier to validate accuracy and categorize payments by country and tax type.”—Brett Weaver, Partner, Tax ESG Leader at KPMG.

Azure—the best place to build AI workloads

The general availability of Azure OpenAI Service is not only an important milestone for our customers but also for Azure.

Azure OpenAI Service provides businesses and developers with high-performance AI models at production scale with industry-leading uptime. This is the same production service that Microsoft uses to power its own products, including GitHub Copilot, an AI pair programmer that helps developers write better code, Power BI, which leverages GPT-3-powered natural language to automatically generate formulae and expressions, and the recently-announced Microsoft Designer, which helps creators build stunning content with natural language prompts.

All of this innovation shares a common thread: Azure’s purpose-built, AI-optimized infrastructure.

Azure is also the core computing power behind OpenAI API’s family of models for research advancement and developer production.

Azure is currently the only global public cloud that offers AI supercomputers with massive scale-up and scale-out capabilities. With a unique architecture design that combines leading GPU and networking solutions, Azure delivers best-in-class performance and scale for the most compute-intensive AI training and inference workloads. It’s the reason the world’s leading AI companies—including OpenAI, Meta, Hugging Face, and others—continue to choose Azure to advance their AI innovation. Azure currently ranks in the top 15 of the TOP500 supercomputers worldwide and is the highest-ranked global cloud services provider today. Azure continues to be the cloud and compute power that propels large-scale AI advancements across the globe.

Source: TOP500 The List: TOP500 November 2022, Green500 November 2022.

A responsible approach to AI

As an industry leader, we recognize that any innovation in AI must be done responsibly. This becomes even more important with powerful, new technologies like generative models. We have taken an iterative approach to large models, working closely with our partner OpenAI and our customers to carefully assess use cases, learn, and address potential risks. Additionally, we’ve implemented our own guardrails for Azure OpenAI Service that align with our Responsible AI principles. As part of our Limited Access Framework, developers are required to apply for access, describing their intended use case or application before they are given access to the service. Content filters uniquely designed to catch abusive, hateful, and offensive content constantly monitor the input provided to the service as well as the generated content. In the event of a confirmed policy violation, we may ask the developer to take immediate action to prevent further abuse.

We are confident in the quality of the AI models we are using and offering customers today, and we strongly believe they will empower businesses and people to innovate in entirely new and exciting ways.

The pace of innovation in the AI community is moving at lightning speed. We’re tremendously excited to be at the forefront of these advancements with our customers, and look forward to helping more people benefit from them in 2023 and beyond.

Getting started with Azure OpenAI Service

Learn more about Azure OpenAI Service and more about all the latest enhancements.
Apply for access to Azure OpenAI Service. Once approved for use, customers can log in to the Azure portal to create an Azure OpenAI Service resource and then get started either in our Studio website or via code:

How to create an Azure OpenAI Service resource
Quickstart: how to get started generating text

Read the blog: AI and the need for purpose-built cloud infrastructure.
Watch a video with tips on how to get started with Azure OpenAI Service:

Quelle: Azure

Microsoft named a Leader in 2022 Gartner® Magic Quadrant™ for Insight Engines

How your organization can benefit, no matter the industry.

As the amount of data being generated continues to grow at an exponential rate, it's becoming increasingly important for organizations to have a rich set of tools that can help them make sense of it all. That's where insight engines come in. These powerful solutions apply relevancy methods to data of all types, from structured to highly unstructured, allowing users to describe, discover, organize, and analyze it to deliver information proactively or interactively at the right time, in the right context.

Microsoft has recently been named a Leader in the 2022 Gartner Magic Quadrant for Insight Engines, a report that evaluates the capabilities of various vendors in the market.

Microsoft offers two integrated solutions in this space: Microsoft Search, which is available with Microsoft 365, and Azure Cognitive Search, which is available as a platform as-a-service (PaaS) with Microsoft Azure. These solutions are designed to help professionals and developers build impactful AI-powered search solutions that can solve complex problems and enhance the customer experience by enabling information discovery across the spectrum from unstructured to structured data. Whether you need a turnkey solution to reason over enterprise data or the flexibility to tailor search to specific scenarios, Microsoft has you covered.

Azure Cognitive Search can be used in a variety of industries to improve efficiency and decision-making. Some specific examples of how it can be used include:

Manufacturing: Cognitive Search can be used to help manufacturers quickly find information about production processes, equipment, and materials. It can be applied to structured data scenarios such as part catalogs as well as unstructured content such as equipment manuals, safety procedures, and imagery. 
Energy: Cognitive Search can be used to quickly find information related to exploration, drilling, and production. Geo-location search combined with traditional search input enables discovery experiences to get the most of past and present geological site studies, and extensibility allows incorporating energy industry-specific information.
Retail: Cognitive Search can be used to develop a powerful product catalog search experience for retail web sites and apps. Customizable ranking options, scale capability to handle peak traffic with low latency, and the ability for near-real time updates for critical data such as inventory make it a great fit for the scenario. 
Financial services: Cognitive Search can be used by financial institutions to quickly find data related to investments, market trends, and regulatory compliance. Its sophisticated semantic ranking and question-answering capabilities can enable users to answer business questions faster and more confidently.
Healthcare: Cognitive Search can be used by healthcare organizations to improve patient care, streamline operations, and make better informed decisions by quickly finding and accessing relevant information within electronic medical record systems, providing real-time access to clinical guidelines and evidence-based best practices.

Nearly every user knows what to do when they see a search box. All SaaS applications targeting audiences from consumer to enterprise can greatly benefit from a great search experience over their own data. Azure Cognitive Search can deliver an out-of-the-box solution, inclusive of various multi-tenancy strategies, support for over 50 languages, and a global presence to ensure your solution is delivered in the right location for your customers.

If you're a technical decision maker in one of these industries, or any other industry, and you're interested in learning more about how Microsoft's cognitive search solutions can help you unlock the full potential of your data, you can visit the Azure Cognitive Search website and the Microsoft Search website.

You can also download a complimentary copy of the Gartner Magic Quadrant for Insight Engines to see how Microsoft is recognized in the space.

Gartner, Magic Quadrant for Insight Engines, Stephen Emmott, Anthony Mullen, David Pidsley, Tim Nelms, 12 December 2022

Gartner is a registered trademark and service mark, and Magic Quadrant is a registered trademark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and are used herein with permission. All rights reserved.

This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from Gartner Reprint.

Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
Quelle: Azure

Microsoft named a Leader in The Forrester Wave™: Public Cloud Development and Infrastructure Platforms, 2022

Forrester recently published its report, The Forrester Wave™: Public Cloud Development and Infrastructure Platforms, Global, Q4 2022, placing Microsoft in the “Leaders” category. It’s an honor to be named as one of only two leaders in Forrester’s definitive report on the public cloud development and infrastructure platform market.

The Forrester report recognized Microsoft for its long-term focus on Kubernetes, hybrid, and multicloud capabilities and noted that it is seeking to lead in hybrid and multicloud environments with platform management tools and capabilities. Reference customers praised Microsoft’s service improvements and partnerships. With Microsoft Azure, customers have a trusted cloud partner and the most advanced, highly integrated enterprise IT infrastructure to help them navigate ever-changing environments and achieve business success today, while they build for the future.

Helping developers build any app for any platform

We recognize that developers are the driving engine of innovation. When they are empowered to set up a complete engineering system in seconds, contribute and collaborate with anyone on any device, use the right tool for the job, and integrate with the rest of the organization’s digital estate, organizations can bring innovation to market faster with greater confidence. Azure makes all that possible. For example, with Microsoft Visual Studio, developers can deploy iOS, Android, Windows, Web or embedded apps to wherever they’d like–Azure, hybrid, on-premises and multi-cloud environments. Further, Azure fully supports some of the most popular open source technologies from Linux, to open-sourced databases, to Grafana, allowing organizations to leverage existing investments when running on Azure.

In August, we introduced Microsoft Dev Box, a managed service for developers to create on-demand, high-performance, secure, ready-to-code, project-specific workstations in the cloud, so they can work and innovate anywhere. And we’ve continued to bring new Kubernetes capabilities across Azure, which I’ll cover a little later in this article.

As the range of application development tools continues to grow, we’re seeing a surge in low-code technologies to spur innovation and lower the barrier to entry. Microsoft makes it easy with PowerApps, which provides prebuilt templates, drag-and-drop simplicity, quick deployment and AI-powered assistance, helping anyone create apps using natural language, while enabling the same DevOps practices for low-code tools that customers expect when building trusted enterprise solutions.

In this new world, organizations are harnessing the cloud to create a culture where everyone feels empowered to innovate, while lowering the barrier to creating new types of apps that can take businesses to new heights.

The Microsoft Intelligent Data Platform

We’re entering the age of the “intelligent app,” where every app is AI-enabled and adapts to each organization’s modern data capabilities. However; fragmented digital estates make it difficult for organizations to harness their data to add layers of intelligence to their apps.

At our Build event in May, we announced the Microsoft Intelligent Data Platform that fully integrates databases, analytics, and governance for a unified data estate. With this integration, organizations can power applications at any scale, get actionable insights from all their data, and properly govern data where it resides. To accelerate time to value, customers can use pre-built, customizable, and production-ready AI models as the building blocks for intelligent solutions with Azure Cognitive Services and Azure Applied AI Services.

As AI becomes more mainstream across organizations, it’s essential that employees have the tools to leverage this technology responsibly. We apply Microsoft's Responsible AI Standards to our product development, and have made it a priority to help customers understand, protect, and control their AI solutions with tools and resources like the Responsible AI Dashboard, bot development guidelines, and built-in tools to help explain model behavior, test for fairness and more.

By unifying and integrating data to create more intelligent apps, customers are opening the door to new innovations never thought possible.

From cloud to edge: Innovate securely, anywhere

More and more organizations are embracing hybrid and multicloud as part of their migration and modernization journeys, and they want to continue this flexible approach in a secure, compliant, reliable, and integrated way. Forrester credits Microsoft with "seeking to lead in hybrid and multicloud environments with platform management tools and capabilities, including the Azure Arc management platform."

Azure Arc operates as a bridge extending across the Azure platform by allowing applications and services the flexibility to run across on-premises, edge, and multicloud environments. One of the key challenges organizations face is securing and managing their distributed environments consistently while building innovative applications using cloud-native technologies.

Recently, we announced new deployment options for Azure Kubernetes Services enabled by Azure Arc so customers can run containerized apps, in addition to many first-party Azure application, data, and machine learning services, anywhere regardless of their location.

They can also take advantage of Azure’s comprehensive security, governance, and management capabilities for their Windows, Linux, SQL Server, and Kubernetes deployments in their datacenters, at the edge, or multicloud.

Azure is the only cloud platform built by a security vendor and ensuring that our customers' data is safe and secure is at the forefront of everything we do. For example, our Defender for Cloud security service spans across all clouds—even AWS and Google Cloud for a seamless, consistent, and secure cloud journey where it leads.

Our deep commitment to our customers is baked into every aspect of our vision and roadmap—to be the trusted partner with the most advanced, yet flexible cloud technologies that enable anyone in any organization to innovate anywhere. It’s an honor to be recognized for that commitment and a great way to usher in the New Year.

Learn more

Read The Forrester Wave™: Public Cloud Development And Infrastructure Platforms, Global, Q4 2022.
Learn how Toyota employees used low-code to create more than 400 apps to meet business needs.
Learn how Sutherland, a professional services company, built a data-driven culture with Microsoft Azure.
Learn how the National Basketball Association delivers compelling experiences for its fans through intelligent applications. 
Learn how Royal Bank of Canada, the largest bank in Canada, is using Azure Arc–enabled data services to take advantage of always up-to-date cloud-native data services to modernize its large data estate.
Read how a study found a 228 percent ROI when modernizing apps on Azure's platform as a service.

Quelle: Azure

Microsoft Innovation in RAN Analytics and Control

Currently, Microsoft is working on RAN Analytics and Control technologies for virtualized RAN running on Microsoft Edge platforms. Our goal is to empower any virtualized RAN solution provider and operators to realize the full potential of disaggregated and programmable networks. We aim to develop platform technologies that virtualized RAN vendors can leverage to gain analytics insights in their RAN software operations, and to use these insights for operational automations, machine learning, and AI-driven optimizations.

Microsoft has recently made important progress in RAN analytics and control technology. Microsoft Azure for Operators is introducing flexible, dynamically loaded service models to both the RAN software stack and cloud/edge platforms hosting the RAN, to accelerate the pace of innovation in Open RAN.

The goal of Open RAN is to accelerate innovation in the RAN space through the disaggregation of functions and exposure of internal interfaces for interoperability, controllability, and programmability. The current standardization effort of O-RAN by O-RAN Alliance, specifies the RAN Intelligent Controller (RIC) architecture that exposes a set of telemetry and control interfaces with predefined service models (known as the E2 interface). Open RAN vendors are expected to implement all E2 service models specified in the standard. Near-real-time RAN controls are made possible with xApp applications accessing these service models.

Microsoft’s innovation extends this standard-yet-static interface. It introduces the capability of getting detailed internal states and real-time telemetric data out of the live RAN software in a dynamic fashion for new RAN control applications. With this technology, together with detailed platform telemetry, operators can achieve better network monitoring and performance optimization for their 5G networks, and enable new AI, analytics, and automation capabilities that were not possible before.

This year, Microsoft, together with contributions from Intel and Capgemini, has developed an analytics and control approach that was recognized with the Light Reading Editor’s Choice award under the category of Outstanding Use case: Service provider AI. This innovation calls for dynamic services models for Open RAN.

Dynamic service models for real-time RAN control

There are many RAN control use cases that require dynamic service models beyond those specified in O-RAN today, such as access to IQ samples, RLC and MAC queue sizes, and packet retransmission information. These high-volume real-time data need to be aggregated and compressed before being delivered to the xApp. Also, detailed data from different RAN modules across different layers like L1, L2, and L3 may need to be collected and correlated in real-time before any useful insight can be derived and shared with xApp. Further, a virtualized RAN offers so many more possibilities, that any static interface or service model may be ineffective in meeting the more advanced real-time control needs.

One such example occurs with interference detection. Today, operators typically need to do a drive test to detect external interference in a macro cell. But now, Open RAN has the potential to replace the expensive truck roll with a software program that detects interference signals at the RAN’s L1 layer. However, this will require a new data service model with direct access to raw IQ samples at the physical layer. Another example exists in dynamic power saving. If a RAN power controller can see the number of packets queued at various places in the live RAN system, then it can estimate the pending process loads and optimize the CPU frequency at a very high pace, in order to reduce the RAN server power consumption. Our study has shown that we can reduce the RAN power consumption by 30 percent through this method—even during busy periods. To support this in Open RAN, we will need a new service model that exposes packet queuing information.

These new use cases are envisioned for the time after the current E2 interface has been standardized. To achieve them, though, we need new RAN platform technologies to quickly extend this interface to support these and future advanced RAN control applications.

The Microsoft RAN analytics and control framework

The Microsoft RAN analytics and control framework extends the current RIC service models in O-RAN architecture to be both flexible and dynamic. In the process, the framework allows RAN solution providers and operators to define their own service models for dynamic RAN monitoring and control. Here, the underlying technology is a runtime system that can dynamically load and execute third-party code in a trusted and safe manner.

This system enables operators and trusted third-party developers to write their own telemetry, control, and inference pieces of code (called “codelets”) that can be deployed at runtime at various points in the RAN software stack, without disrupting the RAN operations. The codelets are executed inline in the live RAN system and on its critical paths, allowing them to get direct access to all important internal raw RAN data structures, to collect statistics, and to make real-time inference and control decisions.

To ensure security and safety, the codelets checked with static verified with verification tools before they can be loaded, and they will be automatically pre-empted if running longer than the predefined execution budgets. The dynamic code extension system is the same as the Extended Berkeley Packet Filter (eBPF), which is a proven technology that has been entrusted to run custom codes in Linux kernels on millions of mission-critical servers around the globe. The inline execution is also extremely fast, typically incurring less than one percent of overhead on the existing RAN operations.

The following image illustrates the overall framework and the dynamic service model denoted by the star circle with the letter D.

The benefit of the dynamic extension framework with low-latency control is that it can open the opportunity for third-party real-time control algorithms. Traditionally, due to the tight timing constraint, a real-time control algorithm must be tightly implemented and integrated inside the RAN system. The Microsoft RAN analytics framework allows RAN software to delegate certain real-time control to RIC, potentially leading to a future marketplace where real-time control algorithms, machine learning, and AI models for optimizations may be possible.

Microsoft, Intel, and Capgemini have jointly prototyped this technology in Intel’s FlexRAN™ reference software and Capgemini’s 5G RAN. We have also identified standard instrumentation points aligned with the standard 3GPP RAN architecture to achieve higher visibility into the RAN’s internal state. We have further developed 17 dynamic service models, and enabled many new and exciting applications that were previously not thought possible.

Examples of new applications of RAN analytics

With this new Analytics and Control Framework, applications of dynamic power savings and interference detection described earlier can now be realized.

RAN-agnostic dynamic power saving

5G RAN energy consumption is a major OPEX item for any mobile operator. As a result, it is paramount for a RAN platform provider to find any opportunity to save power when running the RAN software. One such opportunity can be found by stepping down the RAN server CPU frequency when the RAN processing load is not at full capacity. This is indeed promising because internet traffic is intrinsically “bursty”; even during peak hours, the network is rarely operated at full capacity.

However, any dynamic RAN power controller must also have accurate load prediction and fast reaction in millisecond timescale. Otherwise, if one part of RAN is in hibernation, then any instant traffic burst will cause serious performance issues, or even crashes. The Microsoft RAN analytics framework with dynamic service models and low-latency control-loop makes it possible to write a novel CPU frequency prediction algorithm based on the number of active users, and changes in different queue sizes. We have implemented this algorithm on top of Capgemini 5G RAN and Intel FlexRAN™ reference software, and we achieved up to 30 percent energy savings—even during busy periods.

Interference detection

External wireless interference has long been a source of performance issues in cellular networks. Detecting external wireless interference is difficult and often requires a truck roll with specialized equipment and experts to detect it. With dynamic service models, we can turn an O-RAN 5G base station into a software-defined radio that can detect and characterize external wireless interference without affecting the radio performance. We have developed a dynamic service model that averages the received IQ samples across frequency chunks and times inside an L1 of the FlexRAN™ reference software stack. The service model in turn reports the averages to an application that runs an AI and machine learning model for anomaly detection, in order to detect when the noise floor increases.

Virtualized and software-based RAN solution offer immense potential of programmable networks that can leverage AI, machine learning, and analytics to improve network efficiency. Dynamic service models for O-RAN interfaces further enhances the pace of innovation with added flexibility and security.

Learn more

Learn more about Microsoft Azure for Operators from our website.
Microsoft Research Technical Report.
Microsoft’s Innovation in RAN Analytics is The Editor’s Choice for “the Outstanding Use Case: Service Provider AI” in the 2022 Leading Lights Award. Leading Lights 2022: The Winners | Light Reading.
Finalist in the Fierce Innovation Award–Telecom Edition 2022: Finalists | Fierce Telecom Awards.

Quelle: Azure

Microsoft named a Leader in the 2022 Gartner® Magic Quadrant™ for Global Industrial IoT Platforms

As industrial Internet of Things (IoT) matures and transforms critical business functions, Microsoft continues to innovate and invest in this area and engage with a large ecosystem of solution partners.

The Microsoft Azure IoT platform can help industries improve their operations to become more efficient, agile, and sustainable. Industrial-focused IoT technologies from Microsoft are especially important for enterprises looking to do more with less in the current macro-economic environment.

We’re focused on enabling industrial IoT solution providers and customer operations to be successful, and those efforts haven’t gone unnoticed. For the third year in a row, Gartner has positioned Microsoft as a leader in the 2022 Gartner Magic Quadrant for Global Industrial IoT Platforms.

Leading the way in industrial IoT

In naming Microsoft as an IoT leader, Gartner cites our customer success, our technical strengths in security and manageability, and our focus on supporting end-to-end solutions, as well as our support for our ecosystem of partners. With a long history stretching to the early days of IoT technology, Microsoft remains committed to providing the evolving infrastructure that companies need to excel with IoT deployments. Our IoT technology is embedded in everything from inspecting vehicle build quality, to monitoring and shifting energy across utility grids, to recycling surplus manufacturing materials.

To continue leading on IoT technology and applications, we’re especially focused on supporting key areas that customers are prioritizing:

IT/OT convergence: Digital transformation in the industrial sector is increasingly bringing together IT—systems to collect and analyze data to manage processes—with operational technology (OT), which is dedicated to detecting and controlling physical processes. This IT/OT convergence allows for more direct and real-time monitoring, analysis, and control of industrial processes and enables increased automation, faster responses to challenges, and shifts in manufacturing or production rates. With Microsoft Azure IoT, operators can move toward this convergence with system openness and visibility, as well as security.

Cloud and on-site innovations: Microsoft Azure IoT provides a holistic approach to maintaining and securing digital infrastructure, handling and controlling data, and managing apps and databases no matter where they are. From high-performance computing in the cloud to edge and on-premises equipment, Azure can govern and help to secure servers, Kubernetes clusters, and apps with tools such as Azure Arc, Azure private multi-access edge compute (MEC), and Azure Stack HCI. They can provide consistent, fast, and seamless performance for scalable IoT systems spread across multi-cloud and on-premises locations.

Using digital twins and the metaverse: As IT/OT convergence continues, the ability to use digital replicas and virtual environments to evaluate or control machinery or simulate factory floor environments becomes more useful. Azure Digital Twins uses IoT spatial intelligence to create accurate models of processes or physical things. This lets operators test the effects of new production line configurations, new processes, and modifications to machinery without disrupting physical world operations. Immersive metaverse technology allows employees to virtually perform maintenance procedures or train for operating new industrial equipment before touching any physical assets. This is safer for employees and creates fewer production disruptions.

Security advancements: With IoT workloads moving between multiple clouds and on-premises environments with more flexibility than ever before, security is also more important than ever. This is especially critical with industrial IoT, where compromising critical systems could have serious consequences. The zero-trust security measures built into Azure are extensive and robust to secure cloud-based applications and data. With Azure Arc, customers can extend the familiar security controls of Azure to companies’ on-premises and edge infrastructures. Additionally, many of our solutions partners offer additional security as part of their offerings.

Collaborating with partners: The strength of Microsoft Azure IoT offerings lies in our partner ecosystem, which includes hundreds of systems integrators, independent software vendors, and device partners. These partners offer solution choices for a wide range of industries, including many industrial-related solutions. We work to give their solutions visibility to our customers to help match solutions with needs to address emerging challenges.

Shaping the future of IoT

We’re pleased that Gartner once again has recognized us as a Leader in Global IoT platforms with their Magic Quadrant recognition. As IoT applications continue to grow, more organizations are connecting their physical operations to the digital world to gain insights, optimize performance, and work toward sustainability. We continue to invest and evolve our broad Azure IoT platform, including our industrial IoT technologies, to help customers to accelerate their time to value on IoT investments and enable even more capabilities.

With our partners, we take our role as a Leader seriously in IoT platforms and products, and we plan to keep providing the products and support our customers need to move ahead with digital transformations.

Learn more

We invite you to learn more about the Azure IoT platform and products and explore the Azure Marketplace. You can also read the full complimentary Gartner Report.

Gartner, Magic Quadrant for Global Industrial IoT Platforms, Al Velosa, Eric Goodness, et. al, December 12, 2022.

Gartner is a registered trademark and service mark and Magic Quadrant is a registered trademark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and are used herein with permission. All rights reserved.

This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from Magic Quadrant for Global Industrial IoT Platforms.

Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
Quelle: Azure