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New Azure for Operators solution accelerator offers fast path to network insights

5G marks an inflection point for operators. The disaggregation of software and hardware in 5G enables operators to move telecommunication workloads to public or hybrid public/private cloud infrastructures, giving them unprecedented agility and flexibility to deliver exceptional customer experiences and realize cost efficiencies. However, the full benefit of running large-scale telecommunication services in the cloud can only be achieved if cloud adoption is accompanied by a comprehensive approach to network analysis and automation supported by cloud-based big data and AI.

Today, Azure for Operators is introducing a network analytics solution accelerator program, providing a standardized approach to data acquisition and visualization that aids operators on their journey toward complete end-to-end AI Operations (AIOps). The solution employs the same operational techniques and capabilities that Microsoft uses to manage Azure, packaged specifically for operator analytics. Our network analytics solution comprises existing Azure services combined with unique capabilities developed specifically for communications service providers, which allows network planners and engineers to visualize performance and troubleshoot service anomalies.

Disaggregated cloud native 5G networks add many new individual elements that must interwork effortlessly. These increasing interdependencies mean management and analytics tools can no longer run in relative isolation. Successfully deploying and managing end-to-end services in such environments requires the ability to analyze network and host platform data simultaneously from numerous sources. Only then can operators reactively and proactively diagnose issues, while ensuring operational costs are kept in check and that customers are always presented with the best user experiences.

With the scale and complexity of such services, network management needs to operate autonomously in a closed loop manner—taking operational insights on the health of network elements and the underlying distributed cloud infrastructure and ensuring a service is configured optimally.

At Microsoft, we understand this journey because Azure went through a similar evolution. In the early days, we recognized the challenges of troubleshooting across disparate services. To solve this, we established a common data analytics infrastructure that gave us a comprehensive view of how our services performed, which resulted in lower engineering overheads and better service quality.

Control starts with network insights

Large operators generate petabytes of data every day—complicating the challenges associated with quickly ingesting, cost-effectively storing, and concisely analyzing the information to gain meaningful insights. Public clouds are ideal for solving these problems because they simplify the ability to aggregate and analyze data, thereby allowing operators to rapidly identify and act on any irregularities or opportunities. Azure excels in this area with a portfolio of trusted storage, machine learning, business intelligence, and automation tools.

Azure Data Lake, for example, can capture and store a wealth of disparate log data generated by communications services. Data lakes are more adept than classic data warehouses at handling the sheer velocity, volume, and variety of information operators will need to store. Lakehouses, such as those enabled using Azure Databricks, provide a mediation layer to enforce data quality and consistency.

Once ingested, Azure has several standardized services for aggregating and analyzing otherwise distinct data streams such as logs, traces, telemetry information, and alerts, from inherently different platforms, network functions, and devices. Azure Data Explorer (ADX) rapidly ingests and analyzes petabytes of unstructured, structured, and semi-structured data formats. Similarly, Power BI provides real-time analytical intelligence through a combination of dynamic visualizations and AI-driven insights.

Azure network analytics empowers operations teams to accelerate root cause analysis, enables capacity planners to understand where to deploy new resources, and allows engineers to improve customer experiences by enhancing network performance and quality of service. Our analytics offerings can also assist business teams in tuning marketing strategies toward reducing customer churn and increasing monetization opportunities.

Ingest and analyze data at scale with existing Azure services.

Naturally, with large companies and many users handing enormous amounts of potentially sensitive information, we must guarantee the governance, integrity, and security of this data, providing role-based access while ensuring relevant compliance standards and policies are followed. Microsoft’s Purview provides a fully managed and centralized unified data governance service that delivers the tools such organizations demand. Purview can even prevent the duplication of analytics dashboards, providing a quick and easy way to search for existing interfaces that meet their immediate needs.

Intent-based management and closing the loop

A critical step towards a fully automated network is the ability to identify anomalies and predict issues before they become catastrophic failures. Existing rules-based systems rely on heuristic approaches that will struggle to scale to the quantity and complexity of data they must ingest to pinpoint potential problems within modern network infrastructures. Instead, big data and machine learning–driven inferencing approaches are needed to predict problems hidden within terabytes of disparate logs, error messages, and security alerts with lower severity levels.

Closing the loop from detection to resolution requires a comprehensive vendor and platform-agnostic approach to provisioning standalone network functions and end-to-end services. This evolves to solutions working at the application layer that make choices about how and where to instantiate elements that enable a complete end-to-end service. Such solutions operate across multiple access, edge, core compute, and cloud platforms and are responsible for assigning appropriate resources and tuning configurations within each component to meet the requirements of the service. Underpinning this is multi-cloud and edge lifecycle management systems such as Azure Arc, which provides ongoing governance and management of virtual machines, Kubernetes clusters, and databases.

A closed loop AIOps architectural blueprint.

Ultimately, the goal is that the network operates autonomously based on a loose set of expected outcomes rather than explicit rules defining how to react to specific requests or conditions. Such intent-based management systems will require the application of artificial neural networks which employ deep learning on the vast amounts of real-time data streams that will enable them to train themselves to carry out tasks and perform actions.

There are many scenarios where our network analytics capabilities are needed today. Operators can use the solution to proactively analyze the quality of service in mobile and fixed voice networks, detect issues, prevent outages, and gain insight into infrastructure utilization for capacity planning. The network analytics solution also monitors mobile core performance, looking for underlying platform issues and reporting poor quality of service to accelerate root cause analysis. Furthermore, the solution performs deep packet analysis of end-to-end services, which accelerates deployments and reduces the mean time to repair.

Partner with Microsoft on the AIOps journey

The network management and automation journey can look daunting but, with our network analytics solution accelerator program we offer operators an easier path. With the right technology and the flexibility to handle data from many systems, operators can adopt automation incrementally and at their own pace, meeting business objectives along the way. Azure network analytics allows operations teams to build trust in big data and AI and provides the foundation for closed loop automation.

As part of the Azure for Operators program, Microsoft is making it easy to start discovering the power of Azure’s network analytics offerings. Our solution accelerator enables service providers and systems integrators to take advantage of the Azure tools and services available today as they evolve their longer-term AIOps analytics strategies. Our experts are on hand to guide you through the process of importing, analyzing, and visualizing the massive amounts of data produced by the networks you maintain. Plus, we have resources available to help solve any network issues you are experiencing today or simply understand how your infrastructure is performing. To learn more about participating in our solution accelerator program, contact us here.

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Elevate your visualizations with Azure Managed Grafana, now generally available

As part of our continued commitment to open source solutions, we are announcing the general availability of Azure Managed Grafana, a managed service that enables you to run Grafana natively within the Azure cloud platform. With Azure Managed Grafana, you can seamlessly and securely connect with and scale to businesses’ existing Azure services, enhancing observability and cloud management.

In addition to the features announced during preview, with general availability, we’re introducing new capabilities that include the latest Grafana v9.0 features with its improved alerting experience as well as zone redundancy (in preview) and API key support.

New connections and integrations with Azure services

With general availability, we are adding new integrations with Azure services, allowing you to realize the benefits of Grafana as efficiently and effectively as possible.

We have introduced several new out-of-the-box dashboards for Azure Monitor. For example, with Availability Tests Geo Map dashboard for Azure Monitor application insights, you can view the results and responsiveness of your application availability tests based on geographic location. Additionally, with the new out-of-the-box Load Balancing dashboard for Azure Monitor network insights, you can monitor key performance metrics for all your Azure load balancing resources, including Load Balancers, Application Gateway, Front Door, and Traffic Manager.

A dashboard on a black background. In the center-left is a world map with translucent red and green dots on it. On the far right are 2 graphs, one line graph and another semi circular one.

A dashboard on a black background. There are 4 line graphs (in green) across the center of the page.

The new “pin to Grafana” feature for Azure Monitor Logs allows you to seamlessly add charts and queries from Azure Monitor Logs to Grafana dashboards with just one click. In the illustration below, you can see how the Azure Monitor Logs query on the left is replicated in the Grafana interface on the right.

179391_image 4a179391_image 4b

Similarly, we have introduced new out-of-the-box dashboards for Azure Container Apps as well. The new Aggregate View dashboard for Azure Container Apps depicts a geographic map of your container apps filtered by resource group, environment, and region with drill-down links to a detailed dashboard for each app. The new App View dashboard for Azure Container Apps monitors the performance of Azure Container Apps by viewing the key metrics of CPU, memory, restarts, and network traffic or by revision, replica, and status code.

A dashboard on a black background. There are 6 line graphs in this view, all capturing different metrics of container app.

Read the Azure Managed Grafana technical community blog to learn more about the latest enhancements.

Get started with Azure Managed Grafana

Try it free for the first 30 days from the Azure portal today.

Go to the Azure Managed Grafana product page.

Read the technical documentation.

Share feedback on Microsoft Q&A.

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New enhancements announced for Azure VMware Solution

I’m thrilled to be writing to you today from VMware Explore in San Francisco, where my team and I will be presenting and meeting with customers and partners in person! When we launched Azure VMware Solution two years ago amid a pandemic, IT agility became a top priority as organizations scrambled to enable remote work and ensure business resilience via cloud solutions. Fast forward to today, and most organizations recognize that by running workloads in the cloud, they can respond more rapidly, no matter what the challenge or opportunity.

“It’s much easier for us to take on smaller acquisitions and bring them onboard … by using Azure VMware Solution, we’re always ready and able to add a node and start folding in the new acquisition’s applications and data with the extra capacity.”—Dean Hughes, Infrastructure Manager, Carpetright

“Ordering and installing on-premises networking hosts can take six months. But using Azure VMware Solution, it’s a simple process to run up new hosts that we can have working in a few days.”—Harry Sturgess, Manager of Technology and Operations, Metro South Health

Because every customer starts their cloud journey at a different place, we help enable customers to migrate to the cloud on their terms and maintain support for the business platforms and investments they have today. Azure VMware Solution is an easy way to extend and migrate existing VMware Private Clouds to run them natively on Azure. Azure VMware Solution offers symmetry with on-premises environments, which helps to accelerate datacenter migrations, so customers recognize the benefits of the cloud sooner. This symmetry also allows IT teams to leverage the same VMware skills, processes, and investments from their on-premises VMware environments.

“What a game-changer for us. As a VMware house, we saw how easy it would be to move applications from VMware to Azure VMware Solution because it’s bolted onto the back of Azure.”—Rob Wilde, Platforms Manager, Nottinghamshire County Council

Thanks to Microsoft’s unique Azure Hybrid Benefit and Extended Security Updates for Windows Server and SQL Server, Azure VMware Solution is one of the fastest and most cost-effective ways to seamlessly migrate and run VMware in the cloud.

Option coming for VMware Cloud Universal Program

Today we extended our partnership with VMware to add support for the VMware Cloud Universal program. This will allow customers to purchase Azure VMware Solution as part of VMware Cloud Universal program, a flexible purchasing and consumption program for executing hybrid and multi-cloud strategies. With VMware Cloud Universal, customers may purchase credits for VMware’s multi-cloud infrastructure and management and apply these credits to deployments of Azure VMware Solution. Learn more.

Check out what’s new in Azure VMware Solution

Today I am excited to share some of the recent updates we’ve made to Azure VMware Solution.

  • Global expansion to 24 regions: Since the launch of Azure VMware Solution two years ago, we’ve been working to support customers globally with geographic expansion to 24 Azure regions, more than any other cloud provider. Check out the Azure products by region web page to find a region near you.

A world map showing Azure product region locations such as Central US, East US, North Europe and so on.

  • Azure NetApp Files datastores for Azure VMware Solution is now in public preview. For your storage-intensive workloads running on Azure VMware Solution, the integration with Azure NetApp Files helps to easily scale storage capacity beyond the limits of the local instance storage provided by vSAN and lower your overall total cost of ownership for storage-intensive workloads. Learn more.
  • Public IP to NSX Edge capability for Azure VMware Solution is now generally available in 17 Azure regions. Most customer applications running on Azure VMware Solution require internet access requiring both outbound and inbound internet connectivity. With this new capability, there are now three primary patterns for creating inbound and outbound internet access to resources on your Azure VMware Solution private cloud. Learn more.
  • Enterprise VMware Cloud Director Services for Azure VMware Solution is now in Public Preview. Customers who have Azure VMware Solution deployed under their Microsoft Enterprise agreement can purchase the VMware Cloud Director Service from VMware and connect their Azure VMware Solution private cloud to create and manage private virtual datacenters and leverage vCloud availability for migrating on-premises VMware workloads to Azure VMware Solution private clouds. Learn more.
  • Jetstream DR for Azure VMware Solution is now generally available, providing customers with disaster recovery protection needed for business and mission-critical applications while leveraging cost-effective cloud storage such as Azure Blob Storage. JetStream DR can also replicate and automate recovery to Azure NetApp Files datastores. Learn more.
  • VMware vRealize Log Insight Cloud for Azure VMware Solution is now generally available. This service provides centralized log management, deep operational visibility, intelligent analytics, and improved troubleshooting and security. This boosts IT organizations’ operational efficiency, mitigates costs arising from unplanned downtime, and reduces organizational risk by providing visibility into security-related events. Learn more.
  • VMware vSphere 7.0 is now available globally for all cloud deployments in Azure VMware Solution.

If you would like to stay up to date with the latest releases from Azure VMware Solution, please follow Azure updates.

Learn more

This week we are offering a special opportunity to take the Azure VMware Solution Cloud Skills Challenge. Compete in this free, self-paced, Microsoft learning path and advance your technical skills at the same time! Register for the Challenge.

As always, you can visit the Azure VMware Solution website or documentation for more information.

And if you are here at VMware Explore, stop by the Microsoft booth and say hello. We are excited to see you in person! Booth #1101.


VMware vCloud, vRealize, and vSphere are registered trademarks of VMware, Inc. or its subsidiaries in the United States and other jurisdictions.

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Microsoft is a Leader in 2022 Gartner Magic Quadrant for Cloud AI Developer Services

Gartner has recognized Microsoft as a Leader in the 2022 Gartner® Magic Quadrant™ for Cloud AI Developer Services, with Microsoft placed furthest in “Completeness of Vision”.

Gartner defines the market as “cloud-hosted or containerized services that enable development teams and business users who are not data science experts to use AI models via APIs, software development kits (SDKs), or applications.”

A square chart split into four quadrants that compares Cloud AI Developer Services on a vertical axis for Ability to Execute and horizontal axis for Completeness of Vision. Microsoft is shown in the top right quadrant as a Leader on both axes.

We are proud to be recognized for our Azure AI Platform. In this post, we’ll dig into the Gartner evaluation, what it means for developers, and provide access to the full reprint of the Gartner Magic Quadrant to learn more.

Scale intelligent apps with production-ready AI

“Although ModelOps practices are maturing, most software engineering teams still need AI capabilities that do not demand advanced machine learning skills. For this reason, cloud AI developer services (CAIDS) are essential tools for software engineering teams.”—Gartner

A staggering 87 percent of AI projects never make it into production.¹ Beyond the complexity of data preprocessing and building AI models, organizations wrestle with scalability, security, governance, and more to make their model’s production ready. That’s why over 85 percent of Fortune 100 companies use Azure AI today, spanning industries and use cases.

More and more, we see developers accelerate time to value by using pre-built and customizable AI models as building blocks for intelligent solutions. Microsoft Research has made significant breakthroughs in AI over the years, being the first to achieve human parity across speech, vision, and language capabilities. Today, we’re pushing the boundaries of language model capabilities with large models like Turing, GPT-3, and Codex (the model powering GitHub Copilot) to help developers be more productive. Azure AI packages these innovations into production-ready general models known as Azure Cognitive Services and use case-specific models, Azure Applied AI Services for developers to integrate via API or an SDK, then continue to fine tune for greater accuracy.

For developers and data scientists looking to build production-ready machine learning models at scale, we support automated machine learning also known as autoML. AutoML in Azure Machine Learning is based on breakthrough Microsoft research focused on automating the time-consuming, iterative tasks of machine learning model development. This frees up data scientists, analysts, and developers to focus on value-add tasks outside operations and accelerate their time to production.

Enable productivity for AI teams across the organization

“As more developers use CAIDS to build machine learning models, the collaboration between developers and data scientists will become increasingly important.”—Gartner

As AI becomes more mainstream across organizations, it’s essential that employees have the tools they need to collaborate, build, manage, and deploy AI solutions effectively and responsibly. As Microsoft Chairman and CEO Satya Nadella shared at Microsoft Build, Microsoft is “building models as platforms in Azure” so that developers with different skills can take advantage of breakthrough AI research and embed them into their own applications. This ranges from professional developers building intelligent apps with APIs and SDKs to citizen developers using pre-built models via Microsoft Power Platform.

Azure AI empowers developers to build apps in their preferred language and deploy in the cloud, on-premises, or at the edge using containers. Recently we also announced the capability to use any Kubernetes cluster and extend machine learning to run close to where your data lives. These resources can be run through a single pane with the management, consistency, and reliability provided by Azure Arc.

Operationalize Responsible AI practices

“Vendors and customers alike are seeking more than just performance and accuracy from machine learning model. When selecting AutoML services, they should prioritize vendors that excel at providing explainable, transparent models with built-in bias detection and compensatory mechanisms.”—Gartner

At Microsoft, we apply our Responsible AI Standard to our product strategy and development lifecycle, and we’ve made it a priority to help customers do the same. We also provide tools and resources to help customers understand, protect, and control their AI solutions, including a Responsible AI Dashboard, bot development guidelines, and built-in tools to help them explain model behavior, test for fairness, and more. Providing a consistent toolset to your data science team not only supports responsible AI implementation but also helps provide greater transparency and enables more consistent, efficient model deployments.

Microsoft is proud to be recognized as a Leader in Cloud AI Developer Services, and we are excited by innovations happening at Microsoft and across the industry that empower developers to tackle real-world challenges with AI. You can read and learn from the complete Gartner Magic Quadrant now.

Learn more


References

¹Why do 87 percent of data science projects never make it into production? Venture Beat.

Gartner Inc.: “Magic Quadrant for Cloud AI Developer Services,” Van Baker, Svetlana Sicular, Erick Brethenoux, Arun Batchu, Mike Fang, May 23, 2022.

Gartner and Magic Quadrant are registered trademarks and service marks 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 Microsoft. 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.

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Microsoft and Unity partner to empower digital creators, 3D artists and game developers everywhere through the power of Azure

Unity selects Azure as its cloud partner; companies will work together to enable creators to reach their audiences on Xbox and PC

At Microsoft, we have a profound commitment to empowering creators. Throughout the history of Windows, we’ve nurtured developers and fostered their creative innovations. We do the same on our Xbox-branded platforms, supporting developers large and small in more than 90 countries around the world.  And our Azure cloud assures developers that they can unleash their imaginations and trust that their work is secure and scalable. Our commitment to creators is something we share with our longtime partner, Unity, a global leader in real-time 3D technology. We’re also committed to expanding the creation and distribution of 3D content, to bringing relevant tools and technologies to a wider range of developers, and to making it easier than ever to bring games to players.

That is why today, Unity has selected Azure as its cloud partner for building and operating real-time 3D (RT3D) experiences from the Unity engine.  In addition, we’re excited to work together to make it easier for game creators around the world to publish to Xbox consoles and PC so they can reach their communities.

The magic of 3D interactive experiences born in games is quickly moving to non-gaming worlds. Unity is building a platform-agnostic, cloud-native solution that meets the wide-ranging needs of all developers from enterprise through citizen creators. By giving creators easy access to RT3D simulation tools and the ability to create digital twins of real-world places and objects, Unity is offering creators an easy path to production of RT3D assets, whether for games or non-gaming worlds. To support this evolution, creators require a technical infrastructure that is as dynamic and innovative as they are. Azure is that solution. Built for security and global scalability, Azure already supports some of the world’s largest games and is bringing those battle-tested learnings to power RT3D experiences for all industries. As the need for real-time simulation becomes central to every industry ranging from e-commerce to energy, manufacturing to medical and more, Unity and Microsoft are building the creator cloud that empowers 3D artists to build and run those experiences on Azure.

Our ambition to democratize development of games and game-like experiences around the world and across industries depends on strong partnerships, particularly with game engines like Unity. The partnership between Microsoft and Unity will also enable Made with Unity game creators to more easily reach their players across Windows and Xbox devices and unlock new success opportunities. By engineering improved developer tools, leveraging the latest platform innovation from silicon to cloud, and simplifying the publishing experience, Unity creators will be able to realize their dreams by bringing their games to more gamers around the world.

As 3D interactive experiences continue to evolve in both the gaming and non-gaming worlds, Microsoft and Unity are empowering a wave of new creators to define the digital worlds of tomorrow. It is their talent, creativity and empathy that will not only transform the world but change it for the better.

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Oracle and Microsoft announce availability of Oracle Database Service for Microsoft Azure

Oracle partners with Microsoft to give Azure customers direct, streamlined access to Oracle databases on Oracle Cloud Infrastructure (OCI)

AUSTIN, Texas and REDMOND, Wash. July 20, 2022 — Oracle Corp and Microsoft Corp today announced the general availability of Oracle Database Service for Microsoft Azure. With this new offering, Microsoft Azure customers can easily provision, access, and monitor enterprise-grade Oracle Database services in Oracle Cloud Infrastructure (OCI) with a familiar experience. Users can migrate or build new applications on Azure and then connect to the high-performance, high-availability, managed Oracle Database services such as Autonomous Database running on OCI.

Offering Customers Choice with Azure and OCI Multicloud Capabilities

Over the last two decades, thousands of customers have relied on Microsoft and Oracle software working well together to run their business-critical applications. As customers migrate applications and data to the cloud, they continue to look for joint solutions from their trusted software partners. Since 2019, when Oracle and Microsoft partnered to deliver the Oracle Interconnect for Microsoft Azure, hundreds of organizations have used the secure and private interconnections in 11 global regions.

Microsoft and Oracle are extending this collaboration to further simplify the multicloud experience with the announcement of Oracle Database Service for Microsoft Azure. Many joint customers, including some of the world’s largest corporations such as AT&T, Marriott International, Veritas and SGS, want to choose the best services across cloud providers to optimize performance, scalability, and ability to accelerate their business modernization efforts. The Oracle Database Service for Azure builds upon the core capabilities of the Oracle Interconnect for Azure and enables any customer to more easily integrate workloads on Microsoft Azure with Oracle Database services on OCI. There are no charges for using the Oracle Database Service for Microsoft Azure, the Oracle Interconnect for Microsoft Azure or data egress or ingress when moving data between OCI and Azure. Customers will pay only for the other Azure or Oracle services they consume, such as Azure Synapse or Oracle Autonomous Database.

“Microsoft and Oracle have a long history of working together to support the needs of our joint customers, and this partnership is an example of how we offer customer choice and flexibility as they digitally transform with cloud technology,” said Corey Sanders, corporate vice president, Microsoft Cloud for Industry and Global Expansion. “Oracle’s decision to select Microsoft as its preferred partner deepens the relationship between our two companies and provides customers with the assurance of working with two industry leaders.”

“There’s a well-known myth that you can’t run real applications across two clouds. We can now dispel that myth as we give Oracle and Microsoft customers the ability to easily test and demonstrate the value of combining Oracle databases with Azure applications. There is no need for deep skills on both of our platforms or complex configurations—anyone can use the Azure Portal to get the power of our two clouds together,” said Clay Magouyrk, executive vice president, Oracle Cloud Infrastructure.

“Multicloud takes on a whole new meaning with the launch of the Oracle Database Service for Microsoft Azure. This service, designed to provide intuitive, simple access to the Exadata Database Service and Autonomous Database to Azure users in a transparent manner, responds to the critical need of Azure and Oracle customers to apply the benefits of the latest in Oracle Database technology to their Azure workloads. This combined and interactive connection of services across public clouds sets the stage for what a multicloud experience should be, and is a bold statement about where the future of cloud is heading. It should deliver huge benefits for customers, developers, and the cloud services landscape overall,” said Carl Olofson, research vice president, Data Management Software, IDC.

Familiar Experience for Azure Users Combined with an Oracle Managed Service

With the new Oracle Database Service for Microsoft Azure, in just a few clicks, users can connect their Azure subscriptions to their OCI tenancy. The service automatically configures everything required to link the two cloud environments and federates Azure Active Directory identities, making it easy for Azure customers to use the service. It also provides a familiar dashboard of your Oracle Database Services on OCI using Azure terminology and monitoring with Azure Application Insights.

“Many of our mission-critical workloads are running Oracle databases on-premises at massive scale. As we move these workloads to the cloud, Oracle Database Service for Azure enables us to modernize these Oracle databases to services such as Autonomous Database in OCI while leveraging Microsoft Azure for the application tier,” said Jeremy Legg, chief technology officer, AT&T. Watch the video.

“Multicloud architectures enable us to choose the best cloud provider for each workload based on capabilities, performance, and price. The OCI and Azure partnership integrates the capabilities of two major cloud providers, including the Oracle Database services in OCI and Azure’s application development capabilities,” said Naveen Manga, chief technology officer, Marriott International. Watch the video.

“Oracle Database Service for Microsoft Azure has simplified the use of a multicloud environment for data analytics,” said Jane Zhu, senior vice president and chief information officer, Corporate Operations, Veritas. “We were able to easily ingest large volumes of data hosted by Oracle Exadata Database Service on OCI to Azure Data Factory where we are using Azure Synapse for analysis.”

“Oracle Database Service for Microsoft Azure simplifies our multicloud approach. We’re going to be able to leverage the best of Oracle databases in Azure, and we are going to be able to keep our infrastructure in Azure. This is a great opportunity to have the best of the two worlds that eases our migration to the cloud and improves the skills of our people in IT,” said David Plaza, chief information officer, SGS. Watch the video.

Additional Resources 

About Oracle
Oracle offers integrated suites of applications plus secure, autonomous infrastructure in the Oracle Cloud. For more information about Oracle (NYSE: ORCL), please visit us at oracle.com.

About Microsoft
Microsoft (Nasdaq “MSFT” @microsoft) enables digital transformation for the era of an intelligent cloud and an intelligent edge. Its mission is to empower every person and every organization on the planet to achieve more.

Trademarks
Oracle, Java, and MySQL are registered trademarks of Oracle Corporation.

# # #

Contact Info

Carolin Bachmann
Oracle PR
+1.415.622.8466
[email protected]

Microsoft Media Relations
WE Communications for Microsoft
+1 425 638 7777
[email protected]

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Microsoft joins Jakarta EE and MicroProfile Working Groups at Eclipse Foundation

We’re excited to announce that Microsoft has joined the Eclipse Foundation Jakarta EE and MicroProfile Working Groups as an Enterprise and Corporate member, respectively. Our goal is to help advance these technologies to deliver better outcomes for our Java customers and the broader community. We’re committed to the health and well-being of the vibrant Java ecosystem, including Spring (Spring utilizes several key Jakarta EE technologies). Joining the Jakarta EE and MicroProfile groups complements our participation in the Java Community Process (JCP) to help advance Java SE.

image shows Strategic and Enterprise members of Jakarta EE Working Group

image shows members of MicroProfile Working Group

Over the past few years, Microsoft has made substantial investments in offerings for Java, Jakarta EE, MicroProfile, and Spring technologies on Azure in collaboration with our strategic partners. With Red Hat, we’ve built a managed service for JBoss EAP on Azure App Service. We’re also collaborating with Red Hat to enable robust solutions for JBoss EAP on Virtual Machines (VMs) and Azure Red Hat OpenShift (ARO). With VMware, we jointly develop and support Azure Spring Apps (formerly Azure Spring Cloud), a fully managed service for Spring Boot applications. And with Oracle and IBM, we’ve been building solutions for customers to run WebLogic and the WebSphere product family on VMs, Azure Kubernetes Service, and ARO. Other work includes a first-party managed service to run Tomcat and Java SE (App Service) and Jakarta Messaging support in Azure Service Bus. Learn more about these Java EE, Jakarta EE, and MicroProfile on Azure offerings.

image shows Java on Azure offerings for Jakarta EE and MicroProfile technologies)

Our strategic partners

Microsoft is actively improving our support for running Quarkus on Azure, including on emerging platforms such as Azure Container Apps. The expanded investment in Jakarta EE and MicroProfile is a natural progression of our work to enable Java on Azure. Our broad and deep partnerships with key Java ecosystem stakeholders such as Oracle, IBM, Red Hat, and VMware power our Java on Azure work. These strategic partners share our enthusiasm for the Jakarta EE and MicroProfile journeys that Microsoft has embarked upon.

“We’re thrilled to have an organization with the influence and reach of Microsoft joining the Jakarta EE Working Group. Microsoft has warmly embraced all things Java across its product and service portfolio, particularly Azure. Its enterprise customers can be confident that they will be actively participating in the further evolution of the Jakarta EE specifications which are defining enterprise Java for today’s cloud-native world.”—Mike Milinkovich, Executive Director, Eclipse Foundation.

“We welcome Microsoft to the Jakarta EE and MicroProfile Working Groups. We are pleased with our collaboration with Microsoft in delivering Oracle WebLogic Server solutions in Azure, which are helping customers to use Jakarta EE in the cloud. We look forward to more collaboration in the Jakarta EE and MicroProfile Working Groups.”—Tom Snyder, Vice President, Oracle Enterprise Cloud Native Java.

“IBM’s collaboration with Microsoft has shown Jakarta EE and MicoProfile running well in a number of Azure environments on the Liberty runtime, so it’s exciting to see Microsoft now joining the Jakarta EE and MicroProfile Working Groups. I look forward to seeing Microsoft bringing another perspective to the Working Groups based on their experience and needs for Azure customers.”—Ian Robinson, Chief Technology Officer, IBM Application Platform.

“It is great to see Microsoft officially join both MicroProfile and Jakarta EE as they’d been informally involved in these efforts for a long time. I hope to see Microsoft’s participation bring experience from their many users and partners who have developed and deployed enterprise Java applications on Azure for several years.”—Mark Little, Vice President, Software Engineering, Red Hat.

“We are excited to see Microsoft supporting the Jakarta EE Working Group. Jakarta EE serves as a key integration point for Spring applications and we look forward to the future evolution of common specifications like Servlet, JPA, and others. Microsoft delights developers with their continued support of the Java ecosystem along with their work with VMware on bringing a fully managed Spring service to Azure.”—Ryan Morgan, Vice President, Software Engineering, VMware.

Looking to the future

As part of the Jakarta EE and MicroProfile working groups, we’ll continue to work closely with our long-standing partners. We believe our experience with running Java workloads in the cloud will be valuable to the working groups, and we look forward to building a strong future for Java together with our customers, partners, and the community.

Learn more about Java on Azure offerings for Jakarta EE and MicroProfile.

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Realizing Machine Learning anywhere with Azure Kubernetes Service and Arc-enabled Machine Learning, now generally available

We are thrilled to announce the general availability of Azure Machine Learning (Azure ML) Kubernetes compute, including support of seamless Azure Kubernetes Service (AKS) integration and Azure Arc-enabled Machine Learning.

With a simple cluster extension deployment on AKS or Azure Arc-enabled Kubernetes (Arc Kubernetes) cluster, Kubernetes cluster is seamlessly supported in Azure ML to run training or inference workload. In addition, Azure ML service capabilities for streamlining full ML lifecycle and automation with MLOps become instantly available to enterprise teams of professionals. Azure ML Kubernetes compute empowers enterprises ML operationalization at scale across different infrastructures and addresses different needs with seamless experience of Azure ML CLI v2, Python SDK v2 (preview), and Studio UI. Here are some of the capabilities that customers can benefit

  • Deploy ML workload on customer managed AKS cluster and gain more security and controls to meet compliance requirements.
  • Run Azure ML workload on Arc Kubernetes cluster right where data lives and meets data residency, security, and privacy compliance, or harness existing IT investment.
  • Use Arc Kubernetes cluster to deploy ML workload or aspect of ML lifecycle across multiple public clouds.
  • Fully automated hybrid workload in cloud and on-premises to leverage different infrastructure advantages and IT investments.

The IT-operations team and data-science team are both integral parts of the broader ML team. By letting the IT-operations team manage Kubernetes compute setup, Azure ML creates a seamless compute experience for data-science team who does not need to learn or use Kubernetes directly. The design for Azure ML Kubernetes compute also helps IT-operations team leverage native Kubernetes concepts such as namespace, node selector, and resource requests/limits for ML compute utilization and optimization. Data-science team now can focus on models and work with productivity tools such as Azure ML CLI v2, Python SDK v2, Studio UI, and Jupyter notebook.

It is easy to enable and use an existing Kubernetes cluster for Azure ML workload with the following simple steps:

easy-k8s-setup.png

IT-operation team. The IT-operation team is responsible for the first 3 steps above: prepare an AKS or Arc Kubernetes cluster, deploy Azure ML cluster extension, and attach Kubernetes cluster to Azure ML workspace. In addition to these essential compute setup steps, IT-operation team also uses familiar tools such as Azure CLI or kubectl to take care of the following tasks for the data-science team:

  • Network and security configurations, such as outbound proxy server connection or Azure firewall configuration, Azure ML inference router (azureml-fe) setup, SSL/TLS termination, and no-public IP with VNET.
  • Create and manage instance types for different ML workload scenarios and gain efficient compute resource utilization.
  • Trouble shooting workload issues related to Kubernetes cluster.

Data-science team. Once the IT-operations team finishes compute setup and compute target(s) creation, data-science team can discover list of available compute targets and instance types in Azure ML workspace to be used for training or inference workload. Data science specifies compute target name and instance type name using their preferred tools or APIs such as Azure ML CLI v2, Python SDK v2, or Studio UI.

k8s-compute list.png

Separation of responsibilities between the IT-operations team and data-science team. As we mentioned above, managing your own compute and infrastructure for ML workload is a complicated task and it is best to be done by IT-operations team so data-science team can focus on ML models for organizational efficiency.

Create and manage instance types for different ML workload scenarios. Each ML workload uses different amounts of compute resources such as CPU/GPU and memory. Azure ML implements instance type as Kubernetes custom resource definition (CRD) with properties of nodeSelector and resource request/limit. With a carefully curated list of instance types, IT-operations can target ML workload on specific node(s) and manage compute resource utilization efficiently.

Multiple Azure ML workspaces share the same Kubernetes cluster. You can attach Kubernetes cluster multiple times to the same Azure ML workspace or different Azure ML workspaces, creating multiple compute targets in one workspace or multiple workspaces. Since many customers organize data science projects around Azure ML workspace, multiple data science projects can now share the same Kubernetes cluster. This significantly reduces ML infrastructure management overheads as well as IT cost saving.

Team/project workload isolation using Kubernetes namespace. When you attach Kubernetes cluster to Azure ML workspace, you can specify a Kubernetes namespace for the compute target and all workloads run by the compute target will be placed under the specified namespace.

Azure Arc-enabled ML enables teams of ML professionals to build, train, and deploy models in any infrastructure on-premises and across multi-cloud using Kubernetes. This opens a variety of new use patterns previously unthinkable in cloud setting environment. Below table provides a summary of the new use patterns enabled by Azure ML Kubernetes compute, including where the training data resides in each use pattern, the motivation driving each use pattern, and how the use pattern is realized using Azure ML and infrastructure setup.

use patterns.png

To get started with Azure Machine Learning Kubernetes compute, please visit Azure ML documentation and GitHub repo, where you can find detailed instructions to setup Kubernetes cluster for Azure Machine Learning, and train or deploy models with a variety of Azure ML examples. Lastly, visit Azure Hybrid, Multicloud, and Edge Day and watch “Real time insights from edge to cloud” where we announced the GA.

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Top 5 reasons to attend Azure Hybrid, Multicloud and Edge Day June 15

Azure Hybrid, Multicloud, and Edge Day on June 15

Infrastructure and app development are becoming more complex as organizations span a combination of on-premises, cloud, and edge environments. Such complexities arise when:

  • Organizations want to maximize their existing on-premises investments like traditional apps and datacenters.
  • Workloads can’t be moved to public clouds due to regulatory or data sovereignty requirements.
  • Low latency is required, especially for edge workloads.
  • Organizations need innovative ways to transform their data insights into new products and services.

Operating across disparate environments presents management and security complexities. But comprehensive hybrid solutions can not only address these complexities but also offer new opportunities for innovation. For example, organizations can innovate anywhere across hybrid, multicloud, and edge environments by bringing Azure security and cloud-native services to those environments with a solution like Azure Arc.

That’s why we’re excited to present Azure Hybrid, Multicloud, and Edge Day—your chance to see how to innovate anywhere with Azure Arc. Join us at this free digital event on Wednesday, June 15, 2022, from 9:00 AM‒10:30 AM Pacific Time.

Here are five reasons to attend Azure Hybrid, Multicloud, and Edge Day:

  1. Hear real-world success stories, tips, and best practices from customers using Azure Arc. IT leaders from current customers will share how they use Azure Arc to enable IT, database, and developer teams to deliver value to their users faster, quickly mine business data for deeper insights, modernize existing on-premises apps, and easily keep environments and systems up to date.
  2. Be among the first to hear Microsoft product experts present innovations, news, and announcements for Azure Arc. Get the latest updates on the most comprehensive portfolio of hybrid solutions available.
  3. See hybrid solutions in action. Watch demos and technical deep dives—led by Microsoft engineers—on hybrid and multicloud solutions, including Azure Arc and Azure Stack HCI. You’ll also hear product leaders present demos on Azure Arc–enabled SQL Managed Instance, Business Critical—a service tier that just recently became generally available. Business Critical is built for mission-critical workloads that require the most demanding performance, high availability, and security.
  4. Get answers to your questions. Use the live Q&A chat to ask your questions and get insights on your specific scenario from Microsoft product experts and engineers.
  5. Discover new skill-building opportunities. Learn how you can expand your hybrid and multicloud skillset with the latest trainings and certifications from Microsoft, including the Windows Server Hybrid Administrator Associate certification.

And here’s a first look at one of the Azure customers sharing their perspective at this digital event: Greggs

A United Kingdom favorite for breakfast, lunch, and coffee on the go, Greggs has been modernizing their 80-year-old business through digital transformation. When they needed to consolidate their sprawl between their on-premises server estate and their virtual machines, their IT team turned to Azure Arc.

“One of the advantages of Arc was that we could use one strategy across both on-premises and off-premises architecture,” says Scott Clennell, Head of Infrastructure and Networks at Greggs. “We deployed Azure Arc on our on-premises architecture, then throughout the rest of the infrastructure very rapidly—a matter of a couple of weeks.”

Not only has Azure Arc helped the IT team manage their digital estate better—it’s transformed their team culture. By uniting their entire IT team around Azure Arc, they can work better with their developers using common systems and collaboration tools.

Hear from Greggs and more featured customers at Azure Hybrid, Multicloud, and Edge Day. We hope you can attend!

Azure Hybrid, Multicloud, and Edge Day

June 15, 2022
9:00 AM‒10:30 AM Pacific Time

Delivered in partnership with Intel.

Register now

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Meta selects Azure as strategic cloud provider to advance AI innovation and deepen PyTorch collaboration

Microsoft is committed to the responsible advancement of AI to enable every person and organization to achieve more. Over the last few months, we have talked about advancements in our Azure infrastructure, Azure Cognitive Services, and Azure Machine Learning to make Azure better at supporting the AI needs of all our customers, regardless of their scale. Meanwhile, we also work closely with some of the leading research organizations around the world to empower them to build great AI.

Today, we’re thrilled to announce an expansion of our ongoing collaboration with Meta: Meta has selected Azure as a strategic cloud provider to help accelerate AI research and development. 

As part of this deeper relationship, Meta will expand its use of Azure’s supercomputing power to accelerate AI research and development for its Meta AI group. Meta will utilize a dedicated Azure cluster of 5400 GPUs using the latest virtual machine (VM) series in Azure (NDm A100 v4 series, featuring NVIDIA A100 Tensor Core 80GB GPUs) for some of their large-scale AI research workloads. In 2021, Meta began using Microsoft Azure Virtual Machines (NVIDIA A100 80GB GPUs) for some of its large-scale AI research after experiencing Azure’s impressive performance and scale. With four times the GPU-to-GPU bandwidth between virtual machines compared to other public cloud offerings, the Azure platform enables faster distributed AI training. Meta used this, for example, to train their recent OPT-175B language model. The NDm A100 v4 VM series on Azure also gives customers the flexibility to configure clusters of any size automatically and dynamically from a few GPUs to thousands, and the ability to pause and resume during experimentation. Now, the Meta AI team is expanding their usage and bringing more cutting-edge machine learning training workloads to Azure to help further advance their leading AI research.

In addition, Meta and Microsoft will collaborate to scale PyTorch adoption on Azure and accelerate developers’ journey from experimentation to production. Azure provides a comprehensive top to bottom stack for PyTorch users with best-in-class hardware (NDv4s and Infiniband). In the coming months, Microsoft will build new PyTorch development accelerators to facilitate rapid implementation of PyTorch-based solutions on Azure. Microsoft will also continue providing enterprise-grade support for PyTorch to enable customers and partners to deploy PyTorch models in production on both cloud and edge.

We are excited to deepen our collaboration with Azure to advance Meta’s AI research, innovation, and open-source efforts in a way that benefits more developers around the world,” Jerome Pesenti, Vice President of AI, Meta. “With Azure’s compute power and 1.6 TB/s of interconnect bandwidth per VM we are able to accelerate our ever-growing training demands to better accommodate larger and more innovative AI models. Additionally, we’re happy to work with Microsoft in extending our experience to their customers using PyTorch in their journey from research to production.”

By scaling Azure’s supercomputing power to train large AI models for the world’s leading research organizations, and by expanding tools and resources for open source collaboration and experimentation, we can help unlock new opportunities for developers and the broader tech community, and further our mission to empower every person and organization around the world.