Kategorie: Microsoft Azure

Supercharge your skills with Microsoft CLX tracks for Azure

The Microsoft Azure Connected Learning Experience (CLX) program is expanding with three new tracks for Azure professionals. Enhance your Azure networking, Microsoft Sentinel in Azure, and Windows Server migration skills your way with these personalized and self-paced courses that help you learn on your own time as efficiently and effectively as possible. At the end of each course, you’ll walk away with the knowledge and skills to boost your cloud computing career.

What are the new tracks?

With data volumes growing every year, it’s never been more important to make sure that your Microsoft Azure systems are connected and secure—and that’s why our new CLX tracks are designed to strengthen your Azure Networking, Windows Server migration, and Microsoft Sentinel in Azure skills. From mitigating threats with Sentinel to managing your Windows Server workloads on Azure to uncovering new insights with a connected suite of Azure resources, our new CLX tracks can help you learn the fundamentals of cloud-native security and Azure connectivity so you can protect and connect your mission-critical systems.

New course AttendeesCourse contentAZ-700: Designing and Implementing Microsoft Azure Networking Solutions  Azure network engineersLearn how to design and implement a secure network infrastructure in Azure and how to establish hybrid connectivity, routing, private access to Azure services, and monitoring in Azure. In this course, you’ll learn the ins and outs of Azure networking. Practice designing and implementing core networking infrastructure, application delivery services, and private access to Azure services, and design, implement, and manage connectivity services. You’ll also learn to secure network connectivity to Azure resources—and though this course is meant for Azure network engineers, anyone with an interest in Azure networking can enroll.MS-Sentinel: Mitigate threats using Microsoft Sentinel in Azure (Part of SC-200)*Note: This track is not a certification course, but instead is a part of the SC-200 course. Because of this, learners are not eligible to receive a Microsoft certification exam voucher for completing this track.Security Analyst Threat Intelligence Analyst Incident Responder Security Engineer Security Operations Center (SOC) ManagerIn this course, you’ll learn to protect your organization against threats with Microsoft Sentinel, a cloud-native Security Information and Event Management (SIEM) and Security Orchestration, Automation, and Response (SOAR) solution. You’ll practice leveraging Sentinel’s capabilities to identify and respond to threats in real time by designing and configuring a Sentinel workspace, managing Sentinel analytics rules and incidents, and much more. At the end of the course, you’ll have gained the skills you need to effectively use Sentinel to mitigate threats and protect your organization’s most mission-critical resources.Migrate and manage Windows Server workloads on AzureSystem AdministratorAzure Cloud AdministratorAzure Cloud ConsultantMigrating and managing Windows Server workloads on Azure involves transferring existing applications and infrastructure from on-premises to the Azure cloud platform. Azure offers various tools and services, such as Azure Site Recovery, Azure Virtual Machines, Azure Backup, and Azure Monitor, to support this migration and management process. This allows organizations to leverage the benefits of cloud computing while still using their familiar Windows Server workloads.

What is the CLX program?

The CLX program is a comprehensive, step-by-step learning program designed for IT professionals and other aspiring learners looking to master core concepts in cloud services. It combines self-paced interactive labs and skilling content with virtual sessions led by Microsoft tech experts to help learners like you strengthen their understanding of the latest cloud topics in a way that meets your needs and fits your schedule. The program’s unique design ensures you get exactly the skills you need as efficiently as possible, and it includes four steps:

Knowledge AssessmentThe program kicks off with a 20-question Knowledge Assessment to gauge your skills. Based on your results, it will then present you with only the course content that’s relevant to your skills and knowledge gaps—making sure you use your time as efficiently as possible in a way that fits your experience.

Interactive labsYou’ll then dive into learning modules and hands-on, interactive online labs that mirror what you’ll experience in the professional world—helping you learn efficiently and effectively. The interactive labs are available on demand and can be used as many times as needed.

Virtual sessionAfter finishing the interactive labs, you can choose to attend a virtual session led by Microsoft-certified trainers that dive deeply into the course content. Led by Microsoft-certified trainers (MCTs), these group sessions feature live discussions, insights, and practical guidance, and you can ask follow-up questions to get real-time help alongside peers and pros. To make sure you get the skills you need wherever you’re located, the two-to-four-hour sessions are held regularly in three time zones—Australian Easter Daylight Time (AEST), Greenwich Mean Time (GMT), and Pacific Daylight Time (PDT).

Practice testAt the end of your CLX journey, you’ll take an 80-question practice test that helps you assess your learning and prepare you for your final Microsoft certification exam. This two-hour test is very similar to the final exam, helping you accurately test your understanding and target areas for improvement.Once you’ve finished the program’s four steps, you’ll walk away with the knowledge and skills to help you excel in the world of Azure. You’ll also receive a 50% discount voucher for the Microsoft Azure Certification exam (this is a voucher only available with certain courses), so you can prove your skills and advance your cloud computing career.

How can I sign up?

Check out our Microsoft CloudEvents Portal and our Microsoft Azure CLX introductory video to learn more and sign up for the CLX program. You can also read about many other courses in CLX that are designed to boost your Azure skills in our previous blog, and you can check out our CLX AI in Azure skilling content here.
The post Supercharge your skills with Microsoft CLX tracks for Azure appeared first on Azure Blog.
Quelle: Azure

Develop Microsoft Azure skills with 30 Days to Learn It

In today’s rapidly evolving job market, having a competitive edge is essential. With technology advancing at an unprecedented pace, it’s becoming increasingly important to keep up with the latest trends and tools. The Microsoft Cloud Skills Challenge 30 Days to Learn It program is aimed at helping individuals develop proficiency in the most in-demand skills in the tech industry, such as learning the Microsoft Azure platform. The program offers various learning journeys designed for participants with different levels of experience and technical backgrounds.

The challenge is open to IT professionals and developers of all skill levels and is designed to provide a flexible and accessible way to learn new skills and advance their careers. To participate, individuals simply need to sign up for the challenge on the Microsoft Learn platform and begin completing the available learning modules.

Completing any challenge within 30 days can make individuals eligible for a 50 percent discount on a Microsoft Certification exam. These certifications can boost a participant’s career prospects and earning potential and are widely recognized in the tech industry.

Our results speak for themselves: Upon completion of the program, 77 percent of professionals get a promotion, land a new role, or enter technical programs after becoming certified. Additionally, 74 percent of surveyed professionals got more autonomy in their jobs, and 35 percent of candidates who completed a certification received a salary increase of 30 percent or more.

Microsoft Azure 30 Days to Learn It program

In this blog, we will focus on Microsoft Azure-based 30 Days to Learn It challenges, though a variety of learning paths exist, including Microsoft 365, Dynamics 365, and Microsoft Power Platform. Microsoft Azure is a cloud computing platform that offers a wide range of services, including compute, storage, networking, and AI. It is a popular choice for developers because it is scalable, reliable, and secure. Azure can help developers build and deploy applications faster and more easily, and it can help them save money on infrastructure costs.

Check out our full lineup of challenges to get started on your career advancement today:

ToolTraining DescriptionAzure Network EngineerGain expertise in planning, implementing, and maintaining Azure networking solutions, including hybrid networking, connectivity, routing, security, and private access to Azure services. This learning journey is designed for participants who have experience with networking concepts and connectivity methods.Azure Database AdministratorBegin learning how to manage the operational aspects of cloud-native and hybrid data platform solutions built with Microsoft SQL Server and Microsoft Azure Data Services. This learning journey is designed to equip participants with a variety of methods and tools to perform day-to-day operations at an introductory level.Windows Server Hybrid AdministratorGain expertise in configuring and managing Windows Server on-premises, hybrid, and infrastructure as a service (IaaS) platform workloads. This learning journey is designed for participants who administer core and advanced Windows Server workloads and services using on-premises, hybrid, and cloud technologies.Azure Virtual Desktop FundamentalsGain the ability to plan the architecture for an Azure Virtual Desktop deployment, manage access and security, manage user environments and apps, and monitor and maintain an Azure Virtual Desktop environment.Azure AI FundamentalsGet a solid foundation in machine learning and AI concepts including computer vision, natural language processing, and conversational AI. This learning journey is designed for participants with both technical and non-technical backgrounds.Azure DeveloperParticipate in all phases of cloud development to create end-to-end solutions. Design, build, test, and maintain cloud applications using compute, storage, management, and security services on Azure.Azure Data ScientistDesign and implement a data science solution on Azure. Learn how to build machine learning models, no-code predictive models, and machine learning solutions, and run data science workloads in the cloud.Azure Data FundamentalsGain a foundation in core database concepts in cloud environments and data services including relational data, non-relational data, big data, and analytics. This learning journey is designed for participants with both technical and non-technical backgrounds.Azure Cosmos DB DeveloperStart developing modern applications in the cloud with a fully managed, NoSQL database. This learning journey is designed for participants with experience designing, implementing, and monitoring cloud-native applications that store and manage data.Designing Azure Infrastructure SolutionsDesign cloud and hybrid solutions that run on Microsoft Azure, including compute, network, storage, monitoring, and security.Java on Azure DeveloperStart developing modern Java applications in the cloud with managed compute, databases, and DevOps services. This learning journey is designed for participants with familiarity developing and running Java applications and beginner-level experience with cloud infrastructure.DevOps EngineerDesign and implement DevOps processes and practices. Develop an instrumentation strategy with logging, telemetry, and monitoring. Manage source control with GitHub to foster collaboration and automate build and deployment processes.Azure Synapse AnalyticsTake your data analytics skills to the next level with Azure Synapse Analytics. Learn how to integrate, transform, and consolidate data from various structured and unstructured data systems into structures that are suitable for building analytics solutions.

The Microsoft Cloud Skills Challenge 30 Days to Learn It is a free, self-paced learning program that can help developers learn Microsft Azure, earn a Microsoft certification, get hands-on experience, and connect with other developers. The program covers a wide range of Azure topics, including Azure App Service, Azure Data Factory, and Azure Machine Learning. It also includes hands-on labs and a community forum, which can help developers learn the skills they need to build and deploy cloud-based applications, gain confidence, and build relationships.

Learn more at our 30 Days to Learn It website.
The post Develop Microsoft Azure skills with 30 Days to Learn It appeared first on Azure Blog.
Quelle: Azure

How Microsoft Cloud is embracing FinOps practitioners

In February 2023, I announced that Microsoft joined the FinOps Foundation as a premier member and outlined five areas we planned to explore and invest in:

Defining specifications and evolving best practices.

Aligning our collective guidance.

Improving our products and services.

Advancing training and certification programs.

Engaging with the community.

We’ve been busy over the past four months and with FinOps being top of mind as several of us land in San Diego for the second annual FinOps X conference that’s kicking off later today, I wanted to share some of that progress with you.

Helping FinOps practitioners learn and grow

While we’ve been dedicated to helping people manage and optimize their costs for years, this month is especially pivotal for FinOps practitioners managing costs in Microsoft Cloud.

First up is a new FinOps solutions page to help centralize the various resources available today and in the future. Whether you’re new to FinOps or you have years of experience, this page will connect you to Microsoft solutions that can empower your organization to efficiently adopt FinOps best practices.

One of the resources you’ll find on the FinOps solutions page is a new FinOps with Azure e-book. This 20-page e-book is a great resource for those new to FinOps in Azure. The e-book will guide you through the FinOps principles to highlight Microsoft solutions that can support your cloud journey and help your organization maximize the cloud business value.

When you’re ready to dig into the next level of detail and start your FinOps journey, check out the new FinOps documentation. If you’re new, you’ll get an introduction to FinOps and the FinOps Framework with a guide for how to approach each iteration through the FinOps lifecycle. And whether you’re new or experienced, you’ll also find guides that help you understand and implement each capability in Azure.

You’ll also find newly updated Microsoft Cost Management documentation, which has been reorganized to help you navigate and find related guidance quicker and easier than ever. Whether you’re looking for reporting and analytics, monitoring, optimization, cost allocation, or automation and extensibility, everything you need to implement your FinOps capabilities in Microsoft Cost Management has been restructured for ease of use.

These same changes are also coming to the Azure Portal, where you’ll find a new Cost Management menu that organizes capabilities into these same groups, again making it easier than ever to navigate to the capabilities you need to drive your FinOps practice.

Enable the new streamlined menu yourself from try preview in Cost Management and let us know what you’d like to see next.

Helping FinOps practitioners get answers faster

Everyone loves new guidance that teaches you how to solve complex problems or streamline how you work, but why stop there? Just like documentation can guide your learning experience, our vision of Cost Management is to guide you through your data, helping you discover deeper insights into costs and deliver answers quicker than ever before. This starts with significant performance improvements within the Cost analysis experience. Many have already noticed considerably faster load times over the last few months. Expect to see even more improvements in the coming months.

Beyond performance, you may have also noticed some major improvements to the new Cost analysis experience. Everyone’s familiar with the customizable charts in Cost analysis, but many are still new to smart views in Cost analysis. Smart views add intelligent insights about your costs like anomaly detection, more flexible download options, and the ability to multi-task and explore multiple perspectives of your cost at the same time. You can take a quick peek into cost details by expanding any row—and now, for the first time, you can also drill down into cost details with one click.

Drill down in smart views improves the classic filtering in customizable views by allowing you to drill into the data you’re looking at without needing to manually look up values in a filter on the side of the page, which interrupts your flow. Simply click the item you’re interested in, and you’ll switch to a view that gives you the next level of detail. Or perhaps you’re interested in related costs. Select the context menu (three dots) next to the name and choose from the related attributes to find resources of the same type or in the same resource group, for instance. And if you need to manage the resource, simply select Go to > Resource from the menu. After you’ve drilled into your costs, you can select the Customize command at the top to remove filters or simply select the Back command on that view to undo the last change. Enable drill down yourself from try preview in Cost Management and let us know what you’d like to see next.

Looking forward, smart views will also provide quick access to your Cost Management AI assistant. The assistant will help you perform quick analyses, provide insights, and offer recommendations to better understand, analyze, manage, and forecast your cloud costs.

But whether you use smart views or customizable views, the new Cost analysis experience remembers what you used and offers quick access to views you used recently or pinned to the top of the list. Soon, you’ll also see support for customizable views directly within the tabbed experience, making it easier to switch between your customizable, saved, and smart views.

Helping FinOps practitioners scale their efforts

Many practitioners can meet their basic needs with the native Cost Management experiences in the Azure Portal, but there are times when you need more. Maybe you’re looking to automate onboarding and setup. Or perhaps you need more advanced reporting merged with business data. Or maybe you have a more complex cost allocation or chargeback strategy that requires integrating with other systems. Whatever your scenario is, the FinOps toolkit open-source project seeks to offer solutions that help you automate and extend native cloud capabilities to meet the common needs of the FinOps community. The toolkit is an exploratory community-driven project with contributors across the globe and includes learnings from Microsoft architects and engineers in the field to help you get off the ground quicker with:

Starter kits that help you get started with cost management and optimization.

Automation scripts to streamline cost configuration and management at scale.

Advanced solutions to facilitate building custom solutions.

As an example, many people who discover Cost Management scheduled alerts or anomaly detection are immediately interested in automating setup across all subscriptions. To streamline automation, we contributed code to the FinOps toolkit and published the bicep modules for scheduled actions in the official Bicep Registry. Whether you’re creating a scheduled alert for a resource group or a subscription cost anomaly alert, adding a reference to the Bicep Registry module is quick and easy:

Looking beyond automation, another example is when organizations want to build custom reporting or optimization solutions. Custom solutions always start with data ingestion, but most organizations don’t realize the complexities introduced by nuances within different billing systems or managing data at scale. The FinOps toolkit includes a data pipeline code sample that ingests cost data into a central data store and includes pre-built Power BI reports to get you started quickly. The solution was designed and implemented by Brett Wilson (Principal Cloud Solution Architect) and Anthony Romano (Senior Consultant) to enable faster, more reliable reporting against multiple billing accounts, subscriptions, and resource groups and normalizes cost data to the FinOps Open Cost and Usage Specification (FOCUS) schema.

If you’re not familiar with FOCUS, it’s an open specification for billing data that we’re leading with the FinOps Foundation. We’re partnering with many practitioners, vendors, and cloud providers to deliver a draft specification we can all adopt. You’ll hear more about this at FinOps X this week. There’s a lot to cover, so I’ll share more details in a future blog post.

Stay tuned for more updates about the FinOps toolkit. There are many solutions the community would like to share and we’re always eager to hear from you about what you’d like to see next.

Helping FinOps practitioners drive efficiency

We’re always looking for ways to help organizations optimize their cloud usage and rates to drive efficiencies that ultimately result in more business value. (This focus on business value might be my favorite aspect of FinOps.) And as the heart of all optimization in Azure, you’ll usually see these show up in Azure Advisor first, like the ability to customize the lookback period for right-sizing recommendations, which gives you more flexibility to improve the accuracy of cost recommendations, or the ability to automate cost savings with Resource Graph.

But also keep in mind that not all optimization and efficiency opportunities are ahead of us—some are behind us. As FinOps practitioners, you’re of course aware of commitment-based discounts, like reservations and savings plans. It’s perhaps the most discussed way to optimize your costs by committing to specific usage or spending thresholds. But one part of that story that sometimes goes untold is monitoring your reservations. You can now configure reservation utilization alerts in Cost Management to stay informed when your reservation utilization drops below an acceptable threshold. You can configure reservation utilization and anomaly alerts from the new alert rules page in Cost Management.

And last, but not least, I’d like to share a solution that saves you time as well as money! As part of the FinOps toolkit, you also have a new cost optimization workbook that centralizes some of the most used tools to help you drive your utilization and efficiency goals, like Advisor recommendations, Hybrid Benefit, and more. The cost optimization workbook was designed and implemented by Arthur Clares (Senior Cloud Solution Architect) and Seif Bassem (Senior Cloud Solution Architect) and is based on the Well-Architected Framework and feedback we’ve heard from working directly with organizations driving their own FinOps practices.

What’s Next for FinOps?

I’ve just walked you through a sampling of the things we’ve been working on since joining the FinOps Foundation earlier this year. This is only a taste of what’s to come. Looking ahead, you can expect to see:

Even more FinOps learning resources along with more comprehensive documentation that helps you drive FinOps maturity.

Our portal experiences will continue to improve as we integrate more intelligent systems that surface insights more naturally and streamline your workflow.

We’ll continue to evolve and expand the FinOps toolkit to cover more scenarios, like FOCUS adoption, in collaboration with the open-source community.

New and updated tools and services that help you save money and drive efficiency with Microsoft Cloud.

And, if you’re at FinOps X this week, please catch us in our sessions where we’ll share tips on how to manage cost data at scale on Wednesday and how to implement FinOps capabilities in the Microsoft Cloud on Thursday. We’ll also be in the FOCUS and Technical Advisory Council sessions as well as at our booth! We look forward to catching you there or in the FinOps Slack community!

And if that wasn’t enough, here’s one last tip: Stay informed with all FinOps updates with the new FinOps tag on the Azure blog!

All the best from your friendly FinOps ambassadors at Microsoft!
The post How Microsoft Cloud is embracing FinOps practitioners appeared first on Azure Blog.
Quelle: Azure

Explore the benefits of Azure OpenAI Service with Microsoft Learn

As the field of AI continues to grow, developers are constantly seeking new and innovative ways to integrate it into their work. With the launch of Azure OpenAI Service, developers now have even more tools at their disposal to take advantage of this powerful technology. Azure OpenAI Service can be used to create chatbots, generate text, translate languages, and write different kinds of creative content. As the platform continues to evolve, developers will be able to use it to build even more powerful and sophisticated applications.

In this article, we will explore the benefits of utilizing OpenAI and Azure OpenAI Service for developers, as well as the various learning paths Microsoft has established to get you started.

Introduction to OpenAI and Azure OpenAI Service

Azure OpenAI Service is a fully managed service that allows developers to easily integrate OpenAI models into their applications. With Azure OpenAI Service, developers can quickly and easily access a wide range of AI models, including natural language processing, computer vision, and more. Azure OpenAI Service provides a simple and easy-to-use API that makes it easy to get started with AI.

For developers who may not have experience with Azure OpenAI Service, here are some ways it can help:

Simplified integration: A simple and easy-to-use API offers various endpoints that can be used for different tasks, such as text generation, summarization, sentiment analysis, language translation, and more.

Pre-trained models: Already fine-tuned on vast amounts of data, these pre-trained models make it easier for developers to leverage the power of AI without having to train their own models from scratch.

Customization: Developers can also fine-tune the included pre-trained models with their own data with minimal coding, providing an opportunity to create more personalized and specialized AI applications.

Documentation and resources: Azure OpenAI Service provides comprehensive documentation and resources that can help developers get started quickly, including tutorials, guides, and code samples that cover various use cases and scenarios.

Community support: With an active community willing to help and share their experiences via forums and support channels, developers can ask questions, seek guidance, and learn from others.

Scalability and reliability: Hosted on Microsoft Azure, the service provides robust scalability and reliability that developers can leverage to deploy their AI applications with confidence, without having to worry about managing the underlying infrastructure.

Responsible AI: Azure OpenAI Service promotes responsible AI by adhering to ethical principles, providing explainability tools, governance features, diversity and inclusion support, and collaboration opportunities. These measures help ensure that AI models are unbiased, explainable, trustworthy, and used in a responsible and compliant manner.

Learning paths for developers to adopt Azure OpenAI Service

With the rapid adoption and far-reaching possibilities of the recent AI boom, there isn’t a better time to start your skilling journey and stay ahead in this competitive field of technology. Getting started with Azure OpenAI Service is easy, thanks to the newest Microsoft learning path, including a range of resources, including tutorials, documentation, and sample code, to help developers get up to speed with the platform.

Azure OpenAI Service Learning Path – Develop AI solutions with Azure OpenAI ModuleSummaryLearning objectivesGet started with Azure OpenAI ServiceThis module provides engineers with the skills to begin building an Azure OpenAI Service solution.Create an Azure OpenAI Service resource and understand types of Azure OpenAI base models.Use the Azure OpenAI Studio, console, or REST API to deploy a base model and test it in the Studio’s playgrounds.Generate completions to prompts and begin to manage model parameters.Build natural language solutions with Azure OpenAI ServiceThis module provides engineers with the skills to begin building apps that integrate with the Azure OpenAI Service.Integrate Azure OpenAI into your application.Differentiate between different endpoints available to your application.Generate completions to prompts using the REST API and language specific SDKs.Apply prompt engineering with Azure OpenAI servicePrompt engineering in Azure OpenAI is a technique that involves designing prompts for natural language processing models. This process improves accuracy and relevancy in responses, optimizing the performance of the model.Understand the concept of prompt engineering and its role in optimizing Azure OpenAI models’ performance.Know how to design and optimize prompts to better utilize AI models.Include clear instructions, request output composition, and use contextual content to improve the quality of the model’s responses.Generate images with Azure OpenAI ServiceAzure OpenAI Service includes the DALL-E model, which you can use to generate original images based on natural language prompts.Describe the capabilities of DALL-E in the Azure OpenAI Service.Use the DALL-E playground in Azure OpenAI Studio.Use the Azure OpenAI REST interface to integrate DALL-E image generation into your apps.Generate code with Azure OpenAI ServiceThis module shows engineers how to use the Azure OpenAI Service to generate and improve code.Use natural language prompts to write code.Build unit tests and understand complex code with AI models.Generate comments and documentation for existing code.

The future of AI for developers

OpenAI and Azure OpenAI Service have the potential to revolutionize the developer experience, and with the various learning paths available developers can quickly and easily get started. With the constant development and updates being made to the platform, developers can continue to explore the capabilities of Azure OpenAI Service to see even more groundbreaking applications and innovations in the years to come.

Ready to get started with Azure OpenAI Service? Check out the official Microsoft Learn path to discover more about the platform and get hands-on experience with AI. You can also learn and develop essential AI skills with the Microsoft Learn AI Cloud Skills Challenge, which begins on July 17, 2023. Preview the topics and sign up now. With Azure OpenAI Service, the possibilities are endless!
The post Explore the benefits of Azure OpenAI Service with Microsoft Learn appeared first on Azure Blog.
Quelle: Azure

Azure HBv4 and HX Series VMs for HPC now generally available

We are excited to announce Azure HBv4 and HX-series Virtual Machines (VMs) are now generally available. With the general availability, Microsoft is offering customers the first VMs featuring the latest 4th Gen AMD EPYC™ processors with AMD 3D V-Cache™ technology (codename ‘Genoa-X’), paired with 400 Gigabit NVIDIA Quantum-2 InfiniBand. Azure HBv4 and HX-series VMs offer leadership levels of performance, scaling efficiency, and cost-effectiveness for a variety of HPC workloads such as computational fluid dynamics (CFD), financial services calculations, finite element analysis (FEA), geoscience simulations, weather simulation, rendering, quantum chemistry, and silicon design.

Compared to Azure HBv3-series VMs using 3rd Gen AMD EPYC™ processors (codename ‘Milan-X’), already the highest performance VMs for HPC workloads on the public cloud, customers will see up to:

1.6 times higher performance for rendering

2.4 times higher performance for weather simulation

2.7 times higher performance for CFD

4.2 times higher performance for molecular dynamics

5.7 times higher performance for structural analysis

Visit our technical blog for more detailed performance and scalability information and see below for a summary of performance across a diverse selection of widely used high performance computing (HPC) workloads.

Figure 1: Performance comparison summary of Azure HBv4/HX-series VMs to HBv3-series across diverse engineering and scientific computing workloads.

Azure HBv4 and HX-series VMs are available today in the Azure East United States region, and will soon come to the Azure Korea Central, South Central US, Sweden Central, and Southeast Asia regions.

Faster, more cost effective, and more power efficient technologies for HPC

Azure HBv4 and HX series VMs feature 4th Gen AMD EPYC™ processors with AMD 3D V-cache™ because they deliver the fastest levels of performance to a variety of memory performance-bound HPC workloads. The 2.3 GB L3 cache per VM can deliver up to 5.7 terabytes per second of bandwidth to amplify up to 780 gigabytes per second of bandwidth from main memory, for a market leading blended average of 1.2 terabytes per second of effective memory bandwidth across a broad range of customer workloads. For widely-used memory bandwidth-bound workloads like OpenFOAM, HBv4-series VMs with 4th Gen AMD EPYC CPUs with 3D V-Cache technology are already yielding up to 1.49 times higher performance than standard 4th Gen EPYC processors in Azure’s internal testing.

Figure 2: Performance comparison of HBv4/HX during Preview (no 3D V-Cache) versus General Availability (includes 3D V-Cache) from 1-8 VMs on CFD workload OpenFOAM.

Azure HBv4 and HX series VMs deliver these significant performance enhancements at lower cost and energy consumed per job directly proportional to the rate of workload speedup (such as 25 percent faster performance on a given HPC workload with AMD 3D V-Cache compared to standard 4th Gen AMD EPYC CPUs translates to the customer incurring 25 percent lower cost and power consumed per job).

Learn more about performance and scalability across a range of applications, models, and configurations, and visit Azure Docs for full technical specifications of HBv4 and HX series VMs.

Continuous improvement for even more HPC customers

Microsoft is delivering a new era of high-performance computing in the cloud; one defined by continuous improvements to the critical research and business workloads that matter most to our customers. Through our partnership with AMD, we’re making this vision a reality by raising the bar on the performance, scalability, and value we deliver with every release of Azure H-series family VMs for our HPC customers.

With the release of Azure HX series VMs, a new class within the Azure H-series family, we are extending our commitment to customers running large memory workloads like structural analysis and semiconductor design. The 1.4 terabytes of memory in every HX-series VM enables customers to run more of a data intensive workload out of memory for significant speedups and cost reductions. For widely used automotive simulators like MSC Nastran, Azure’s internal testing shows the new HX series VMs yield up to 5.7 times higher performance than HBv3-series VMs, and 9.2 times higher performance than HC-series VMs released 4 years ago featuring technology still widely utilized in on-premises HPC environments today.

Figure 3: Performance uplift from 2019–2023 on Azure H-series family Virtual Machines for structural analysis application MSC NASTRAN.

Customer Momentum

“Materials sciences researchers, including those working with Azure Quantum, stand to benefit greatly from the introduction of Azure HBv4 virtual machines featuring powerful new processors and networking technologies. The 4x performance increase on NAMD shows once again Microsoft’s commitment to continuously making the most advanced computing resources available through Azure cloud services.”—Nathan Baker, Senior Director, Partnerships for Chemistry and Materials, Azure Quantum.

“AMD EPYC™ processors, available through the Azure HB-series family of Virtual Machines via Ansys Cloud, have been instrumental in advancing our ability to deliver more CFD simulations in support of our Motorsports efforts in North America. We firmly believe that accelerating our simulation capabilities and the engineering insights gained from this work have been key to our recent string of successes in both IndyCar and IMSA prototypes. We are looking forward to evaluating the performance of Azure HBv4 and HX-series VMs powered by the 4th Generation of AMD EPYC™ processors with AMD 3D V-Cache™ technology in the very near future. We are confident that AMD and Azure will continue to deliver on their promise of sustainable performance to be realized in time-to and cost-of solution for our very complex CFD models with these processors.”—Kelvin Fu, Vice President at Honda Performance Development.

“With Azure high-performance computing, we can run more jobs and tasks in parallel.  We reduce the time to market by increasing the efficiency and the quality of the product that we release. This solution helps us to improve the product quality and reduce the risk of a delivery delay.”—Anna Palo, Digital Design Architect, STMicroelectronics.

Learn more

Azure Docs – HBv4 series Virtual Machines.

Azure Docs – HX series Virtual Machines.

Performance and Scalability of Azure HBv4 and HX VMs for HPC (Public Preview).

Find more Azure HPC resources.

Learn more about Azure HPC.

The post Azure HBv4 and HX Series VMs for HPC now generally available appeared first on Azure Blog.
Quelle: Azure

Deploy a holistic view of your workload with Azure Native Dynatrace Service

Microsoft and Dynatrace announced the general availability of Azure Native Dynatrace Service in August 2022. The native integration enables organizations to leverage Dynatrace as a part of their overall Microsoft Azure solution. Users can onboard easily to start monitoring their workloads by deploying and managing a Dynatrace resource on Azure.  

Azure Native integration enables you to create a Dynatrace environment like you would create any other Azure resource. One of the key advantages of this integration is the ability to seamlessly ship logs and metrics to Dynatrace. By leveraging Dynatrace OneAgent, users can also gather deeper observability data from compute resources such as virtual machines and Azure App Services. This comprehensive data collection ensures that organizations have a holistic view of their Azure workloads and can proactively identify and resolve issues. 

Furthermore, the integration unifies billing for Azure services, including Dynatrace. Users receive a single Azure bill that encompasses all the services consumed on the platform, providing a unified and convenient billing experience. 

Since its release, Dynatrace Service has seen continuous enhancements. In the following sections, we will explore some of the newer capabilities that have been added to further empower organizations in their monitoring and observability efforts. 

Automatic shipping of Azure Monitor platform metrics 

One of the significant advancements during the general availability of Azure Native Dynatrace Service was the automatic forwarding of logs from Azure Monitor to Dynatrace. The log forwarding capability allows you to configure and send Azure Monitor logs to Dynatrace. Logs start to flow to your Dynatrace environment as soon as the Dynatrace resource on Azure is deployed. The Azure experience allows you to view the summary of all the resources being monitored in your subscription. 

Building further, we have now added another key improvement and that is the ability to automatically obtain metrics from the Azure Monitor platform. This enhancement enables users to effectively view the metrics of various services within Azure on the Dynatrace portal. 

To enable metrics collection, customers can simply check a single checkbox on the Azure portal. This streamlined process makes it easy for organizations to start gathering valuable insights. For further customization, users have the option to specify tags to include or exclude specific resources for metric collection. This allows for a more targeted monitoring approach based on specific criteria.  

The setup of credentials required for the interaction between Dynatrace and Azure is automated, eliminating the need for manual configuration. Once the metrics are collected, users can conveniently view and analyze them on the Dynatrace portal, providing a comprehensive and centralized platform for monitoring and observability. 

Together with logs and metrics monitoring capabilities, Azure Native Dynatrace Service provides holistic monitoring of your Azure workloads. 

Native integration availability in new Azure regions 

During general availability, Azure Native Dynatrace Service was available in two regions, the Eastern United States and Western Europe. However, to cater to the growing demand, native integration is now available in additional regions. You can now create a Dynatrace resource in—The United Arab Emirates North (Middle East), Canada Central, and the Western United States—bringing the total number of supported regions to five. You can select the region in the resource creation experience. When selecting a region to provision a Dynatrace resource, the corresponding Dynatrace environment is provisioned in the same Azure region. This ensures that your data remains within the specified region. Hence, it gives you the power to leverage the power of Dynatrace within the Azure region while complying with the specific data residency regulations and preferences of your organization. 

Monitor activity with Azure Active Directory logs

In the realm of cloud business, early detection of security threats is crucial to safeguarding business operations. Azure Active Directory (Azure AD) activity logs—encompassing audit, sign-in, and provisioning logs—offer organizations essential visibility into the activities taking place within their Azure AD tenant. By monitoring these logs, organizations can gain insights into user and application activities, including user sign-in patterns, application changes, and risk activity detection. This level of visibility empowers organizations to respond swiftly and effectively to potential threats, enabling proactive security measures and minimizing the impact of security incidents on their operations. 

With Azure Native Dynatrace Service, you can route your Azure AD logs to Dynatrace by setting Dynatrace as a destination in Azure AD diagnostic settings.  

Committed to collaboration and integration 

The Azure Native integration for Dynatrace has simplified the process of gaining deep insights into workloads. This integration empowers organizations to optimize their resources, enhance application performance, and deliver high availability to their users. Microsoft and Dynatrace remain committed to collaborating and improving the integration to provide a seamless experience for their joint customers. By working together, both companies strive to continually enhance the monitoring and observability capabilities within the Azure ecosystem. 

The product is constantly evolving to deepen the integration, aiming to monitor a wide range of Azure workloads and uplift user convenience throughout the experience. 

Next steps 

Learn more about how to create, deploy, and manage a Dynatrace resource on Azure:

Subscribe to Azure Native Dynatrace Service from the Azure Marketplace. 

Learn more about how to deploy Dynatrace monitoring resources on Azure with documentation on Dynatrace and Azure integration. 

To discover more about Dynatrace on Azure, visit the Dynatrace documentation. 

Watch Innovate Faster with Azure Native Dynatrace Service to know more about the integration.  

Share additional information about how you use resource and subscription logs to monitor and manage your cloud infrastructure and applications by responding to this survey. 

The post Deploy a holistic view of your workload with Azure Native Dynatrace Service appeared first on Azure Blog.
Quelle: Azure

Removing barriers to autonomous vehicle adoption with Microsoft Azure

Autonomous vehicles, also known as self-driving cars, have the potential to truly revolutionize the transportation industry, with its impact anticipated across many industries. Several stubborn obstacles, however, stand in the way of mass adoption.

In the over 150 years since the automotive industry was founded, it has never experienced such rapid innovation and transformational change as it is currently experiencing. Since the advent of the horseless carriage in the 1860s, vehicle manufacturers have continued to improve the quality, safety, speed, and comfort of millions of automotive models sold around the world, each year.

Today, however, all eyes are on autonomous vehicles as a cornerstone of future human mobility.

Exponential market growth expected

Over the past decade, the impact of emerging technologies such as AI, machine vision, and high-performance computing (HPC) has changed the face of the automotive industry. Today, nearly every car manufacturer in the world is exploring the potential and power of these technologies to usher in a new age of self-driving vehicles. Microsoft Azure HPC and Azure AI infrastructure are tools to help accomplish that.

Data suggests that the global autonomous vehicle market, with level two autonomous features present in cars, was worth USD76 billion in 2020, but is expected to grow exponentially over the coming years to reach over USD2.1 trillion by 2030, as levels of autonomy features in cars continue to increase.1

The platformization of autonomous taxis also holds enormous potential for the broader adoption and usage of autonomous vehicles. Companies like Tesla, Waymo, NVIDIA, and Zoox are all investing in the emerging category of driverless transportation that leverages powerful AI and HPC capabilities to transform the concept of human mobility. However, several challenges still need to be overcome for autonomous vehicles to reach their potential and become the de facto option for car buyers, passengers, and commuters.

Common challenges persist

One of the most important challenges with autonomous vehicles is ethics. If the vehicle determines what action to take during a trip, how does it decide what holds the most value during an emergency? To illustrate, if an autonomous vehicle is traveling down a road and two pedestrians suddenly run across the road from opposite directions, what are the ethics underpinning whether the vehicle swerves to collide with one pedestrian instead of another?

Another of the top challenges with autonomous vehicles is that the AI algorithms underpinning the technology are continuously learning and evolving. Autonomous vehicle AI software relies heavily on deep neural networks, with a machine learning algorithm tracking on-road objects as well as road signs and traffic signals, allowing the vehicle to ‘see’ and respond to—for example, a red traffic light.

Where the tech still needs some refinement is with the more subtle cues that motorists are instinctually aware of. For example, a slightly raised hand by a pedestrian may indicate they are about to cross the road. A human will see and understand the cue far better than an AI algorithm does, at least for now.

Another challenge is whether there is sufficient technology and connectivity infrastructure for autonomous vehicles to offer the optimal benefit of their value proposition to passengers, especially in developing countries. With car journeys from A to B evolving into experiences, people will likely want to interact with their cars based on their personal technology preferences, linked to tools from leading technology providers. In addition, autonomous vehicles will also need to connect to the world around them to guarantee safety and comfort to their passengers.

As such, connectivity will be integral to the mass adoption of autonomous vehicles. And with the advent and growing adoption of 5G, it may improve connectivity and enable communication between autonomous vehicles—which could enhance autonomous vehicles’ safety and functioning.

Road safety is not the only concern with autonomous vehicles. Autonomous vehicles will be designed to be hyper-connected, almost like an ultra-high-tech network of smartphones on wheels. However, an autonomous vehicle must be precisely that—standalone autonomous. If connectivity is lost, the autonomous vehicle must still be able to operate fully autonomously.

That being said, there is still the risk that cyberattacks could pose a threat to autonomous vehicle motorists, compared to legacy vehicles currently on the road. In the wake of a successful cyberattack, threat actors may gain access to sensitive personal information or even gain control over key vehicle systems. Manufacturers and software providers will need to take every step necessary to protect their vehicles and systems from compromise.

Lastly, there are also social and cultural barriers to the mainstreaming of autonomous vehicles with many people across the globe still very uncomfortable with the idea of giving up control of their cars to a machine. Once consumers can experience autonomous drives and see how the technology continuously monitors a complete 360-degree view around the vehicle and does not get drowsy or distracted, confidence that autonomous vehicles are safe and secure will grow, and adoption rates will rise.

The future of travel is (nearly) upon us

As the world moves closer to a future where autonomous vehicles are a ubiquitous presence on our roads, the complex challenges that must be addressed to make this a safe and viable option become ever more apparent. The adoption of autonomous vehicles is not simply a matter of developing the technology, but also requires a complete overhaul of how we approach transportation systems and infrastructure.

To tackle the many challenges posed by autonomous vehicle adoption, companies and researchers are heavily investing resources into solving these complex challenges. For example, one way that researchers are addressing the ethical challenges posed by autonomous vehicles being able to make life or death decisions, is by developing ethical frameworks that guide the decision-making processes of these vehicles.

These frameworks define the principles and values that should be considered when autonomous vehicles encounter ethical dilemmas, such as deciding between protecting the safety of passengers versus that of pedestrians. Such frameworks can help ensure that autonomous vehicles make ethical decisions that are consistent with societal values and moral principles.

Significant investments are also being made into updating existing infrastructure to accommodate autonomous vehicles. Roads, highways, and parking areas must be equipped with the necessary infrastructure to support autonomous vehicles, such as sensors, cameras, and communication systems.

Companies are also working collaboratively with regulators, researchers, and OEMs to develop policies that ensure that autonomous vehicles can operate safely alongside traditional vehicles. This includes considerations such as how traffic signals, road markings, and signage need to be adapted to support autonomous vehicles.

In 2021, for example, Microsoft teamed up with a market leading self-driving car innovator to unlock the potential of cloud computing for autonomous vehicles, leveraging Microsoft Azure to commercialize autonomous vehicle solutions at scale.

Another global automotive group also recently announced a collaboration with Microsoft to build a dedicated cloud-based platform for its autonomous car systems that are currently in development. This ties in with their ambitious plans to invest more than USD32 billion in the digitalization of the car by 2025.

NVIDIA is also taking bold steps to fuel the growth of the autonomous vehicle market. The NVIDIA DRIVE platform is a full-stack AI compute solution for the automotive industry, scaling from advanced driver-assistance systems for passenger vehicles to fully autonomous robotaxis. The end-to-end solution spans from the cloud to the car, enabling AI training and simulation in the data centre, in addition to running deep neural networks in the vehicle for safe and secure operations. The platform is being utilized by hundreds of companies in the industry, from leading automakers to new energy vehicle makers.

Key takeaways

There is little doubt that the future of human mobility is built upon the ground-breaking innovation and technological capabilities of autonomous vehicles. While some challenges still exist, the underlying technology continues to mature and improve, paving the way for an increase in the adoption of self-driving cars long term.

The technology may soon proliferate and displace other, less safe modes of transport, with huge potential upsides for many aspects of our daily lives, such as saving lives and reducing the number of accidents, decreasing commute times, optimizing traffic flow and patterns, thereby lessening congestion, and extending the freedom of mobility for all.

With vehicle manufacturers and software firms continuously iterating on autonomous vehicle technology, continuing to educate the public on their benefits and continuing to work with lawmakers to overcome regulatory hurdles, we may all soon enjoy a new world, one where technology gets us safely from one destination to another, leaving us free to simply enjoy the view.

Learn more

Get started with Azure HPC and Azure AI infrastructure today or request an Azure HPC demo.

Learn more about Azure AI infrastructure for manufacturing:

AI-first infrastructure for Smart Manufacturing.

How AI and the Cloud are transforming computational engineering in manufacturing and consumer packaged goods.

Powering AI innovations with Azure AI infrastructure.

1https://www.alliedmarketresearch.com/autonomous-vehicle-market
The post Removing barriers to autonomous vehicle adoption with Microsoft Azure appeared first on Azure Blog.
Quelle: Azure