Microsoft Azure News, Entwicklungen, Updates, HowTos - Seite 3 von 243

The 2023 changeups in the VMware landscape have created uncertainty and spurred discussions about long-term strategy—your company may be wondering what the future holds for the VMware workloads running in your datacenter. Over the past 25 years, many organizations like yours have built their on-premises IT foundation on VMware—and today the cost of remaining on-premises is higher than ever.

Your competitors are likely shifting their investments to the cloud—and positioning themselves to take advantage of the increasingly mainstream adoption of AI. As you consider pivoting your strategy, it’s crucial to find a way to maximize your existing investments while also choosing a platform that can support your future business needs and applications.

How can you find a path forward for your VMWare workloads that won’t subject you to massive price increases or business disruption? Can you rehost your VMware workloads without compromising on security, control, or budget? Can you use this moment to future-proof your IT platform so you are ready to support the technology changes that will arise over the next 25 years?

You’re not alone in this dilemma. These questions are top of mind for many leaders and practitioners facing similar challenges as they try to navigate the changing landscape of VMware and the cloud. I’m excited to announce that my team will be hosting a free digital event on Tuesday, July 16, 2024 from 9:00 AM–11:00 AM PDT around Azure VMware Solution. I hope you’ll join us to get answers to your questions and learn all the options available for your VMware workloads.

Register now for The Future of VMware Is in Azure to explore strategies and solutions for VMware workloads and learn about Azure VMware Solution—a fully managed VMware environment operated and supported by Microsoft. Azure VMware Solution offers price protection and is designed to help your organization quickly migrate using existing VMware skills while learning new Azure skills.

Azure VMware Solution
Move or extend on-premises VMware environments to Azure without refactoring.

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Join me on July 16 as we discuss the top-of-mind questions that many VMware customers are asking:

How do we avoid big price increases—is there a way to get price protection? Attend the keynote to hear about limited-time offers to secure predictable pricing and cost savings with Azure VMware Solution. Learn about price protection—with lock-in pricing for up to five years with reserved instances, and why Azure is the most cost-effective destination for the Windows Server and SQL Server workloads that you may be running on VMware.

How can we migrate faster while reducing costs? Learn about tailored programs such as VMware license portability benefits, and how the VMware Rapid Migration Plan can help reduce the cost and time it takes for organizations to migrate to Azure VMware Solution.

How do we find a long-term solution for our VMware workloads? Learn how you can set your organization up for success with Azure VMware Solution—offering the fastest path to the cloud with the cost savings, flexibility, scalability, and performance of Azure.

What are our options to get to the cloud with minimal disruption? Learn how to move VMware workloads to Azure “as is” with minimal need for refactoring. Streamline your migration and equip your practitioners to continue using familiar skills and technologies while adopting new cloud competencies.

How can we give developers access to cutting-edge tools for innovation? Learn how making a strategic shift to Azure VMware Solution eliminates routine maintenance and minimizes administrative tasks, while giving developers proximity to the latest data and AI services—allowing your IT teams to redirect focus toward initiatives that directly contribute to business value.

Where can we see real-world use cases and get practical advice from companies that have successfully migrated? Join Brett Tanzer’s fireside chat with the Deputy CIO of the State of Alaska and get insights from their large-scale cloud migration project. Also, watch a demo deployment and ask product experts your specific questions in the live chat Q&A.

What if we have workloads that need to stay on-premises? Learn about hybrid cloud options for VMware workloads. For workloads that cannot be migrated, learn about solutions that function effectively at the edge, bringing Azure cloud services to your on-premises environment.

How can we empower IT practitioners to make the move to Azure? Attend technical sessions and see demos on networking configurations, business continuity plans, and integration with Azure’s extensive portfolio of over 200 services. Also, hear about the newest learning resources, including the Azure VMware Solution Microsoft Learn Challenge.

The Future of VMware Is in Azure
Join us for talks from industry experts, technical sessions, and a live Qu0026amp;A.

Here’s a preview of the sessions on July 16:

Keynote address—The Future of VMware Is in Azure

Join Microsoft Vice President of Azure Solutions and Ecosystem, Brett Tanzer, and myself for an overview of all the options for your VMware workloads. Learn migration strategies, hear insights and advice from a Microsoft customer, watch an Azure VMware Solution deployment demo, and ask your questions at the live Q&A. Stay for deep-dive technical sessions with topics tailored for VMware administrators.

Speakers: Brent Tanzer and Liam Sosinsky

Technical sessions—After the keynote, fireside chat, and demo, stay for sessions with detailed technical aspects of migrating VMware workloads, networking configurations, business continuity plans, and integration with an extensive portfolio of over 200 cloud services from Azure.

Securing your future: Migrate applications and data to Azure VMware Solution. Learn the strategic benefits of moving apps and data to Azure VMware Solution. See a migration demo and hear customer evidence and details on implementing a Zero Trust security model and role-based access control (RBAC) within Azure VMware Solution.

Speakers: Scott Gruenemeier and Joe Sarabia

Building end-to-end networking with Azure VMware Solution. Get an understanding of the Azure VMware Solution networking architecture and see a demo of key connectivity patterns from your software-defined data center (SDDC) in Azure VMware Solution to your on-premises environment. This session also covers default NSX-T topology, native security capabilities offered by Azure VMware Solution, integrations with other services, and design best practices for workload security.

Speaker: Kenyon Hensler

Implementing a robust business continuity and disaster recovery plan. In this session, you’ll learn how to implement your business continuity and disaster recovery (BCDR) strategy with Azure VMware Solution. Get tips and best practices for business continuity and disaster recovery and take a deeper dive into common scenarios, such as BCDR strategies when moving to Azure as well as strategies for BCDR within Azure.

Speaker: Melissa Palmer

Unlocking Azure cloud services with Azure VMware solution. See demos of how to use services on the Azure platform to expand the capabilities of your applications on Azure VMware Solution—without changes to your existing app architecture. Learn about your options for Azure platform as a service (PaaS), as well as options to access to AI capabilities and a wide variety of cloud services using Azure VMware Solution.

Speaker: Joe Sarabia

Hybrid cloud options for VMware workloads. Explore hybrid cloud solutions as a complement to the public cloud. This session will show you how to combine Azure Arc, Azure Stack HCI, and Arc-enabled vSphere with Azure VMware Solution to create a seamless, adaptive cloud experience. Learn when and how to implement these innovative technologies to optimize your cloud strategy and stay ahead of the curve.

Speaker: Shriram Natarajan

The Future of VMware Is in Azure

Tuesday, July 16, 2024

9:00 AM–11:00 AM PDT

The post 8 key VMware questions answered at the Azure VMware Solution digital event appeared first on Azure Blog.
Quelle: Azure

26. Juni 2024

da Agency

How hollow core fiber is accelerating AI

This blog is part of the ‘Infrastructure for the era of AI’ series that focuses on emerging technology and trends in large-scale computing. This piece dives deeper into one of our newest technologies, hollow core fiber (HCF).

AI is at the forefront of people’s minds, and innovations are happening at lightning speed. But to continue the pace of AI innovation, companies need the right infrastructure for the compute-intensive AI workloads they are trying to run. This is what we call ‘purpose-built infrastructure’ for AI, and it’s a commitment Microsoft has made to its customers. This commitment doesn’t just mean taking hardware that was developed by partners and placing it in its’ datacenters; Microsoft is dedicated to working with partners, and occasionally on its own, to develop the newest and greatest technology to power scientific breakthroughs and AI solutions.

Infrastructure for the era of AI

Explore how you can integrate into the world of AI

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One of these technologies that was highlighted at Microsoft Ignite in November was hollow core fiber (HCF), an innovative optical fiber that is set to optimize Microsoft Azure’s global cloud infrastructure, offering superior network quality, improved latency and secure data transmission.

Transmission by air

HCF technology was developed to meet the heavy demands of workloads like AI and improve global latency and connectivity. It uses a proprietary design where light propagates in an air core, which has significant advantages over traditional fiber built with a solid core of glass. An interesting piece here is that the HCF structure has nested tubes which help reduce any unwanted light leakage and keep the light going in a straight path through the core.

As light travels faster through air than glass, HCF is 47% faster than standard silica glass, delivering increased overall speed and lower latency. It also has a higher bandwidth per fiber, but what is the difference between speed, latency and bandwidth? While speed is how quickly data travels over the fiber medium, network latency is the amount of time it takes for data to travel between two end points across the network. The lower the latency, the faster the response time. Additionally, bandwidth is the amount of data that is sent and received in the network. Imagine there are two vehicles travelling from point A to point B setting off at the same time. The first vehicle is a car (representing single mode fiber (SMF)) and the second is a van (HCF). Both vehicles are carrying passengers (which is the data); the car can take four passengers, whereas the van can take 16. The vehicles can reach different speeds, with the van travelling faster than the car. This means it will take the van less time to travel to point B, therefore arriving at its destination first (demonstrating lower latency).

For over half a century, the industry has been dedicated to making steady, yet small, advancements in silica fiber technology. Despite the progress, the gains have been modest due to the limitations of silica loss. A significant milestone with HCF technology was reached in early 2024, attaining the lowest optical fiber loss (attenuation) ever recorded at a 1550nm wavelength, even lower than pure silica core single mode fiber (SMF). 1 Along with low attenuation, HCF offers higher launch power handling, broader spectral bandwidth, and improved signal integrity and data security compared to SMF.

The need for speed

Imagine you’re playing an online video game. The game requires quick reactions and split-second decisions. If you have a high-speed connection with low latency, your actions in the game will be transmitted quickly to the game server and to your friends, allowing you to react in real time and enjoy a smooth gaming experience. On the other hand, if you have a slow connection with high latency, there will be a delay between your actions and what happens in the game, making it difficult to keep up with the fast-paced gameplay. Whether you’re missing key action times or lagging behind others, lagging is highly annoying and can seriously disrupt gameplay. Similarly, in AI models, having lower latency and high-speed connections can help the models process data and make decisions faster, improving their performance.

Reducing latency for AI workloads

So how can HCF help the performance of AI infrastructure? AI workloads are tasks that involve processing large amounts of data using machine learning algorithms and neural networks. These tasks can range from image recognition, natural language processing, computer vision, speech synthesis, and more. AI workloads require fast networking and low latency because they often involve multiple steps of data processing, such as data ingestion, preprocessing, training, inference, and evaluation. Each step can involve sending and receiving data from different sources, such as cloud servers, edge devices, or other nodes in a distributed system. The speed and quality of the network connection affect how quickly and accurately the data can be transferred and processed. If the network is slow or unreliable, it can cause delays, errors, or failures in the AI workflow. This can result in poor performance, wasted resources, or inaccurate outcomes. These models often need huge amounts of processing power and ultra-fast networking and storage to handle increasingly sophisticated workloads with billions of parameters, so ultimately low latency and high-speed networking can help speed up model training and inference, improve performance and accuracy, and foster AI innovation.

Helping AI workloads everywhere

Fast networking and low latency are especially important for AI workloads that require real-time or near-real-time responses, such as autonomous vehicles, video streaming, online gaming, or smart devices. These workloads need to process data and make decisions in milliseconds or seconds, which means they cannot afford any lag or interruption in the network. Low latency and high-speed connections help ensure that the data is delivered and processed in time, allowing the AI models to provide timely and accurate results. Autonomous vehicles exemplify AI’s real-world application, relying on AI models to swiftly identify objects, predict movements, and plan routes amid unpredictable surroundings. Rapid data processing and transmission, facilitated by low latency and high-speed connections, enable near real-time decision-making, enhancing safety and performance. HCF technology can accelerate AI performance, providing faster, more reliable, and more secure networking for AI models and applications.

Regional implications

Beyond the direct hardware that runs your AI models, there are more implications. Datacenter regions are expensive, and both the distance between regions, and between regions and the customer, make a world of difference to both the customer and Azure as it decides where to build these datacenters. When a region is located too far from a customer, it results in higher latency because the model is waiting for the data to go to and from a center that is further away.

If we think about the car versus van example and how that relates to a network, with the combination of higher bandwidth and faster transmission speed, more data can be transmitted between two points in a network, in two thirds of the time. Alternatively, HCF offers longer reach by extending the transmission distance in an existing network by up to 1.5x with no impact on network performance. Ultimately, you can go a further distance at the same latency envelope as traditional SMF and with more data. This has huge implications for Azure customers, minimizing the need for datacenter proximity without increasing latency and reducing performance.

The infrastructure for the era of AI

HCF technology was developed to improve Azure’s global connectivity and meet the demands of AI and future workloads. It offers several benefits to end users, including higher bandwidth, improved signal integrity, and increased security. In the context of AI infrastructure, HCF technology can enable fast, reliable, and secure networking, helping to improve the performance of AI workloads.

As AI continues to evolve, infrastructure technology remains a critical piece of the puzzle, ensuring efficient and secure connectivity for the digital era. As AI advancements continue to place additional strain on existing infrastructure, AI users are increasingly seeking to benefit from new technologies like HCF, virtual machines like the recently announced ND H100 v5, and silicon like Azure’s own first partner AI accelerator, Azure Maia 100. These advancements collectively enable more efficient processing, faster data transfer, and ultimately, more powerful and responsive AI applications.

Keep up on our “Infrastructure for the Era of AI” series to get a better understanding of these new technologies, why we are investing where we are, what these advancements mean for you, and how they enable AI workloads.

Microsoft is a Leader in the 2024 Gartner® Magic Quadrant™ for Data Science and Machine Learning Platforms

Microsoft is a Leader in this year’s Gartner® Magic Quadrant™ for Data Science and Machine Learning Platforms. Azure AI provides a powerful, flexible end-to-end platform for accelerating data science and machine learning innovation while providing the enterprise governance that every organization needs in the era of AI.

In May 2024, Microsoft was also named a Leader for the fifth year in a row in the Gartner® Magic Quadrant™ for Cloud AI Developer Services, where we placed furthest for our Completeness of Vision. We’re pleased by these recognitions from Gartner as we continue helping customers, from large enterprises to agile startups, bring their AI and machine learning models and applications into production securely and at scale.

Azure AI is at the forefront of purpose-built AI infrastructure, responsible AI tooling, and helping cross-functional teams collaborate effectively using Machine Learning Operations (MLOps) for generative AI and traditional machine learning projects. Azure Machine Learning provides access to a broad selection of foundation models in the Azure AI model catalog—including the recent releases of Phi-3, JAIS, and GPT-4o—and tools to fine-tune or build your own machine learning models. Additionally, the platform supports a rich library of open-source frameworks, tools, and algorithms so that data science and machine learning teams can innovate in their own way, all on a trusted foundation.

Azure AI

Microsoft is named a Leader in the 2024 Gartner® Magic Quadrant™ for Data Science and Machine Learning Platforms

Read the report

Accelerate time to value with Azure AI infrastructure

“We’re now able to get a functioning model with relevant insights up and running in just a couple of weeks thanks to Azure Machine Learning. We’ve even managed to produce verified models in just four to six weeks.”
—Dr. Nico Wintergerst, Staff AI Research Engineer at relayr GmbH

Azure Machine Learning helps organizations build, deploy, and manage high-quality AI solutions quickly and efficiently, whether building large models from scratch, running inference on pre-trained models, consuming models as a service, or fine-tuning models for specific domains. Azure Machine Learning runs on the same powerful AI infrastructure that powers some of the world’s most popular AI services, such as ChatGPT, Bing, and Azure OpenAI Service. Additionally, Azure Machine Learning’s compatibility with ONNX Runtime and DeepSpeed can help customers further optimize training and inference time for performance, scalability, and power efficiency.

Whether your organization is training a deep learning model from scratch using open source frameworks or bringing an existing model into the cloud, Azure Machine Learning enables data science teams to scale out training jobs using elastic cloud compute resources and seamlessly transition from training to deployment. With managed online endpoints, customers can deploy models across powerful CPU and graphics processing unit (GPU) machines without needing to manage the underlying infrastructure—saving time and effort. Similarly, customers do not need to provision or manage infrastructure when deploying foundation models as a service from the Azure AI model catalog. This means customers can easily deploy and manage thousands of models across production environments—from on-premises to the edge—for batch and real-time predictions.

Streamline operations with flexible MLOps and LLMOps

“Prompt flow helped streamline our development and testing cycles, which established the groundedness we required for making sure the customer and the solution were interacting in a realistic way.”
—Fabon Dzogang, Senior Machine Learning Scientist at ASOS

Machine learning operations (MLOps) and large language model operations (LLMOps) sit at the intersection of people, processes, and platforms. As data science projects scale and applications become more complex, effective automation and collaboration tools become essential for achieving high-quality, repeatable outcomes.

Azure Machine Learning is a flexible MLOps platform, built to support data science teams of any size. The platform makes it easy for teams to share and govern machine learning assets, build repeatable pipelines using built-in interoperability with Azure DevOps and GitHub Actions, and continuously monitor model performance in production. Data connectors with Microsoft sources such as Microsoft Fabric and external sources such as Snowflake and Amazon S3, further simplify MLOps. Interoperability with MLflow also makes it seamless for data scientists to scale existing workloads from local execution to the cloud and edge, while storing all MLflow experiments, run metrics, parameters, and model artifacts in a centralized workspace.

Azure Machine Learning prompt flow helps streamline the entire development cycle for generative AI applications with its LLMOps capabilities, orchestrating executable flows comprised of models, prompts, APIs, Python code, and tools for vector database lookup and content filtering. Azure AI prompt flow can be used together with popular open-source frameworks like LangChain and Semantic Kernel, enabling developers to bring experimental flows into prompt flow to scale those experiments and run comprehensive evaluations. Developers can debug, share, and iterate on applications collaboratively, integrating built-in testing, tracing, and evaluation tools into their CI/CD system to continually reassess the quality and safety of their application. Then, developers can deploy applications when ready with one click and monitor flows for key metrics such as latency, token usage, and generation quality in production. The result is end-to-end observability and continuous improvement.

Develop more trustworthy models and apps

“The responsible AI dashboard provides valuable insights into the performance and behavior of computer vision models, providing a better level of understanding into why some models perform differently than others, and insights into how various underlying algorithms or parameters influence performance. The benefit is better-performing models, enabled and optimized with less time and effort.”
—Teague Maxfield, Senior Manager at Constellation Clearsight

AI principles such as fairness, safety, and transparency are not self-executing. That’s why Azure Machine Learning provides data scientists and developers with practical tools to operationalize responsible AI right in their flow of work, whether they need to assess and debug a traditional machine learning model for bias, protect a foundation model from prompt injection attacks, or monitor model accuracy, quality, and safety in production.

The Responsible AI dashboard helps data scientists assess and debug traditional machine learning models for fairness, accuracy, and explainability throughout the machine learning lifecycle. Users can also generate a Responsible AI scorecard to document and share model performance details with business stakeholders, for more informed decision-making. Similarly, developers in Azure Machine Learning can review model cards and benchmarks and perform their own evaluations to select the best foundation model for their use case from the Azure AI model catalog. Then they can apply a defense-in-depth approach to mitigating AI risks using built-in capabilities for content filtering, grounding on fresh data, and prompt engineering with safety system messages. Evaluation tools in prompt flow enable developers to iteratively measure, improve, and document the impact of their mitigations at scale, using built-in metrics and custom metrics. That way, data science teams can deploy solutions with confidence while providing transparency for business stakeholders.

Build exciting career opportunities with new Azure skilling options

Microsoft Build is more than just a tech conference—it’s a celebration of innovation, a catalyst for growth, and a gateway to unlocking your professional potential through skilling opportunities on Microsoft Learn. In this blog, we’ll look back at some of the most exciting Microsoft Azure tools that were featured at Build 2024 and put you on the path to attain proficiency.

Start your skilling journey today on Microsoft Learn

Build intelligent apps with AI and cloud-native technologies

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Jump to a section:

Unleash the power of AI by mastering intelligent app development

Empower your developers to achieve unprecedented productivity

Accelerate your cloud journey with seamless Azure migration

Master cloud-scale data analysis for powerful business insights

Unlock maximum cloud efficiency and savings with Azure

Unleash the power of AI by mastering intelligent app development

Azure provides a comprehensive ecosystem of services, tools, and infrastructure tailored for the entire AI lifecycle. At Build we highlighted how your team can efficiently develop, scale, and optimize intelligent solutions that use cutting-edge technologies.

This year at Build, Microsoft announced the general availability for developers to build and customize models in Microsoft Azure AI Studio. We recently dropped an Azure Enablement Show episode that guides viewers through building their own Copilot using Studio. Watch a demonstration of how to use prompt flow to create a custom Copilot, how to chat with the AI model, and then deploy it as an endpoint.

Another episode focuses on new Microsoft Azure Cosmos DB developer guides for Node.js and Python, as well as a learning path for building AI chatbots using Azure Cosmos DB and Microsoft Azure Open AI. You’ll learn how to set up, migrate, manage, and utilize V Core-based Azure Cosmos DB for MongoDB to create generative AI apps, culminating in a live demo of an AI chatbot.

If that Azure Enablement Show episode piques your interest to learn more about Azure Cosmos DB, check out the Microsoft Developers AI Learning Hackathon, where you’ll further explore the world of AI and how to build innovative apps using Azure Cosmos DB, plus get the chance to win prizes! To help you prepare for the hackathon, we have a two-part series to guide you through building AI apps with Azure Cosmos DB, which includes deep-dives into AI fundamentals, Azure Open AI API, vector search, and more.

You can also review our official collection of Azure Cosmos DB learning resources, which includes lessons, technical documentation, and reference sample codes.

Looking for a more structured lesson plan? Our newly launched Plans on Microsoft Learn now provides guided learning for top Azure tools and solutions, including Azure Cosmos DB. Think of it as a structured roadmap for you or your team to acquire new skills, offering focused content, clear milestones, and support to speed up the learning process. Watch for more official Plans on Microsoft Learn over the coming months!

There’s even more to learn about building intelligent AI apps with other exciting Azure tools, with two official collections on Azure Kubernetes Service—Build Intelligent Apps with AI and cloud-native technologies and Taking Azure Kubernetes Service out of the Cloud and into your World—and Build AI Apps with Azure Database for PostgreSQL.

Empower your developers to achieve improved productivity

Accelerating developer productivity isn’t just about coding faster; it’s about unlocking innovation, reducing costs, and delivering high-quality software that drives business growth. Azure developer tools and services empowers you to streamline processes, automate workflows, and use advanced technologies like AI and machine learning.

Join another fun episode of the Azure Enablement Show to discover Microsoft’s skilling resources and tools to help make Python coding more efficient. Learn how to build intelligent apps with Azure’s cloud, AI, and data capabilities and follow along with hands-on modules covering Python web app deployment and machine learning model building on Azure.

We also have three official collections of learning resources that tackle different aspects of developer productivity:

Microsoft Developer Tools @ Build 2024: With cutting-edge developer tools and insights, we’ll show you how to create the next generation of modern, intelligent apps. Learn how you can build, test, and deploy apps from the cloud with Microsoft Dev Box, Microsoft Visual Studio, and how Microsoft Azure Load Testing and Microsoft Playwright Testing make it easy to test modern apps.

Accelerate Developer Productivity with GitHub and Azure for Developers: Continue unlocking the full coding potential in the cloud with GitHub Copilot. Through a series of videos, articles, and activities, you’ll see how GitHub Copilot can assist you and speed up your productivity across a variety of programming languages and projects.

Secure Developer Platforms with GitHub and Azure: Learn how to elevate your code security with GitHub Advanced Security, an add-on to GitHub Enterprise. Safeguard your private repositories at every development stage with advanced features like secret scanning, code scanning, and dependency management.

Accelerate your cloud journey with seamless Azure migration

Migrating to Azure empowers organizations to unlock a world of opportunities. At Build we demonstrated how, by using the robust and scalable Azure cloud platform, businesses can modernize their legacy systems, enhance security and compliance, and integrate with AI.

Looking to get more hands-on with Azure migration tools? Check out our lineup of Microsoft Azure Virtual Training Days. These free, two-day, four-hour sessions are packed with practical knowledge and hands-on exercises for in-demand skills.

Data Fundamentals: In this foundational-level course, you’ll learn core data concepts and skills in Azure cloud data services. Find out the difference between relational and non-relational databases, explore Azure offerings like Azure Cosmos DB, Microsoft Azure Storage, and gain insights into large-scale analytics solutions such as Microsoft Azure Synapse Analytics and Microsoft Azure Databricks.

Migrate and Secure Windows Server and SQL Server Workloads: This comprehensive look at migrating and securing on-premises Windows Server and SQL Server workloads to Azure offers insights into assessing workloads, selecting appropriate migration options, and using Azure flexibility, scalability, and cost-saving features.

Microsoft Azure SQL is an intelligent, scalable, and secure cloud database service that simplifies your operations and unlocks valuable insights for your business. The curated learning paths in our official Azure SQL collection will enable you to focus on the domain-specific database administration and optimization activities that are critical for your business.

For an even more structured learning experience, there’s our official Plans on Microsoft Learn offering, Migrate and Modernize with Azure Cloud-Scale Database to Enable AI. Designed to equip you with the expertise needed to harness the full potential of Azure SQL, Microsoft Azure Database for MySQL, Microsoft Azure Database for PostgreSQL, and Microsoft SQL Server enabled by Microsoft Azure Arc for hybrid and multi-cloud environments, this plan will immerse you in the latest capabilities and best practices.

Master cloud-scale data analysis for insightful decision making

Cloud-scale analytics help businesses gain valuable insights and make data-driven decisions at an unprecedented speed. Our unified analytics platform, Microsoft Fabric, simplifies data integration, enables seamless collaboration, and democratizes access to AI-powered insights, all within a single, integrated environment.

Looking to take the Fabric Analytics Engineer Associate certification exam? Get ready with Microsoft Fabric Learn Together, a series of live, expert-led sessions designed to help you build proficiency in tools such as Apache Spark and Data Factory and understand concepts from medallion architecture design to lakehouses.

There’s still time to register for our Virtual Training Day session, Implementing a Data Lakehouse with Microsoft Fabric, which aims to supply data pros with technical experience how to unify data analytics using AI and extract critical insights. Key objectives include identifying Fabric core workloads to deliver insights faster and setting up a data lakehouse foundation for ingestion, transformation, modeling, and visualization.

And of course, don’t miss out on our official collection of learning resources for Microsoft Fabric and Azure Databricks, featuring modules on implementing a Data Lakehouse and using Copilot in Fabric, and workshops on building retrieval augmented generation (RAG) Applications and Azure Cosmos DB for MongoDB vCore. For a more curated experience, our Plans on Microsoft Learn collection will get started on how to ingest data with shortcuts, pipelines, or dataflows, how to transform data with dataflows, procedures, and notebooks, and how to store data in the Lakehouse and Data Warehouse.

Unlock maximum cloud efficiency and savings with Azure

Promoting resiliency on Azure is a strategic approach to managing your cloud resources efficiently, ensuring optimal performance while minimizing costs. By right-sizing virtual machines (VMs), utilizing reserved instances or savings plans, and taking advantage of automation tools like Microsoft Azure Advisor, you can maximize the value of your Azure investment.

On another fun episode of our Azure Enablement Show, we explore the Learn Live resources available to help you optimize your cloud adoption journey. Confident cloud operations require an understanding of how to manage cost efficiency, reliability, security, and sustainability. Whether you’re an IT pro or just testing the waters, this two-part episode will point you to the learning resources you need.

There’s always more to explore at Microsoft Learn

Like every year, Microsoft Build delivered exciting new products and advancements in Azure technology. Don’t get left behind! Start your skilling journey today at Microsoft Learn.
The post Build exciting career opportunities with new Azure skilling options appeared first on Azure Blog.
Quelle: Azure

21. Juni 2024

da Agency

6 findings from IoT Signals report: Manufacturers prepare their shop floor for AI

Manufacturers are embracing AI to deliver a new level of automation, optimization, and innovation. To unlock the full potential of AI on the shop floor, organizations are testing and investigating technologies and paradigms that empower them to leverage their data more effectively.

Microsoft, in partnership with IoT Analytics, market research firm, conducted a global survey of manufacturers to gain insight into how they are seizing the AI opportunity while navigating key industry challenges. We asked manufacturers about their current priorities and future visions, their adoption of modern technologies and paradigms, and the benefits they expect from those technologies

In this report, we share the key findings from the survey, to show how manufacturing enterprises are preparing their shopfloors for AI to make them secure, scalable, and automated and how they are adopting advanced technologies such as centralized device management, software containerization at the edge, and unified industrial data operations to accelerate that process.

Accelerate industrial transformation

How manufacturers prepare shopfloors for a future with AI

Download report

Read on to discover the six key lessons learned from manufacturers rethinking their operations for AI and how Microsoft is supporting the factory of the future with Azure’s adaptive cloud approach.

Six findings from manufacturers preparing their shop floor for AI

1. Scale matters the most in the era of AI

Scalability was the main concern for 72% of survey respondents, who highlighted this paradigm as crucial for their factory’s future. Scalability came first, followed by automation and serviceability. These paradigms ensure that factories can efficiently expand with demand, optimize with minimal manual decision making, and maintain high uptime through easy troubleshooting and maintenance.

What does scale look like for industrial environments?

Manufacturers face the challenges of keeping up with the changing demands of the market, the regulations, and the competition. They also recognize the potential of AI to transform their operations, optimize their processes, and enhance their products. But they don’t have the luxury of spending months or years on deploying and scaling solutions across their plants. Manufacturers need a faster way to move, a smarter way to manage, and a more flexible way to adapt. That’s why we have introduced a new approach—the adaptive cloud approach.

To learn more, see how the adaptive cloud approach is designed to help manufacturers unify their teams, sites, and systems with cloud-native and AI technologies that work seamlessly across hybrid, multicloud, edge, distributed computing, and IoT. The adaptive cloud approach empowers manufacturers to deliver value faster, manage devices more efficiently, and run applications more securely to prepares them for the AI-powered factory of the future. 

2. Cybersecurity and data management are top of mind right now

Security risks and data handling difficulties pose serious problems, with 58% of respondents seeing cybersecurity as a severe issue and 49% seeing data management as a severe issue. These concerns are motivating customers to improve network security and ensure data is reliable and accessible for decision-making.

What does security look like for industrial environments?

Security and data protection are critical for the manufacturing sector, as the sector faces increasing regulatory standards and cyber threats. Manufacturers need to secure existing devices, and plan during device refresh to choose devices that meet industry security standards, will enable them to more easily comply with regulatory standards, and provide security to defend from the latest security threats. 

To learn more, see Microsoft’s comprehensive approach to security, from device to cloud, that helps customers meet their compliance needs and defend against attacks. For existing devices, Microsoft provides firmware and network scanning with Microsoft Defender for IoT, which allows customers to inventory their devices and monitor for vulnerabilities and threats. For new devices, customers can choose from leading industry original equipment manufacturers (OEMs) devices labeled Secured-core, which meet the latest security requirements. Both existing and new devices can be monitored and remediated using Microsoft Defender and Microsoft Sentinel.

3. Device management is critical for security and data handling

Device management’s value is evolving beyond updates and device health monitoring to also address security risks and data flow management. The survey data supported this trend, with 68% of respondents noting that the security monitoring aspect of device management was very or extremely important to their organization and 59% of respondents highlighting data management as the second most important aspect of device management.

Why is centralized device management important? 

Centralized device management is vital for ensuring the performance and security of operations in a factory setting. It helps to keep devices secure and functioning optimally, which contributes to the overall efficiency and productivity of a manufacturing environment. Effective management also enables better oversight and control over the factory processes, improving operational reliability and supporting scalability and adaptability in a dynamic industrial landscape.

To learn more, see how Azure Arc delivered centralized management for IT and OT environments. Manufacturers can define resources, such as hybrid, multi-cloud, edge, and IoT, to Azure Resource Manager so services such as system health monitoring, security, and many others can be easily applied across a globally distributed digital estate.

4. Containerized workloads are coming to the shop floor

The adoption of containerized software on the shop floor is rising, with 85% of survey respondents already utilizing this technology. This shift towards containerization at the edge signifies a move to improve operational efficiency, system stability, and security. 55% of respondents indicated that containerized software could significantly or extremely mitigate reliability and uptime challenges, while 53% indicated it could do the same for cybersecurity challenges.

What is containerized software?

Software containerization enables consistent and repeatable development and deployment of solutions across different environments, in the cloud and in factory. Containerization of OT software is essential for the AI-powered factory of the future, as it enables seamless technology deployment in scalable, serviceable, and automated factories. Kubernetes automates the scaling and management of containerized applications, saving time and resources for manufacturers.

To learn more, see how Azure Kubernetes Service helps to securely modernize and optimize Kubernetes environments with unified management, governance, and monitoring. Azure Kubernetes Service (AKS), helps teams accelerate app development and deployment with best-in-class tools and generative AI. With AKS, enabled by Arc, these benefits can also be extended to on-premises and edge-based applications

5. Industrial data operations optimize OT data management

Companies want to combine information technology (IT) and operational technology (OT) systems for context driven decision making. 52% of respondents indicated that having a combined IT and OT data platform was very or extremely important for their company. Industrial data operations enhance the integration of IT and OT data by improving data flow, quality and value; therefore, 87% of companies have already adopted industrial data operations technology in some form or are planning to do so.

What are industrial data operations?

Industrial data operations delivers data in a reliable, real-time manner for optimizing factories and plants. Industrial data operations manages and unifyies data from various sources, facilitates seamless integration of information, and ensures data is accessible and usable for decision-making purposes. Industrial data operations helps break down data silos and improve predictive insights through an exchange and integration between shop floor and cloud environments.

To learn more, see how Azure IoT Operations handles data from equipment and systems in OT environments, ensuring that data is collected, pre-processed, and integrated into applications running onsite. This service, announced in public preview at Ignite 2023, embraces industry standards—such as, open packing conventions unified architecture (OPC UA), message queuing telemetry (MQTT), transportOpen telemetry (OTel)—and natively integrates into Microsoft Fabric. Microsoft Fabric, handles data for cloud environments, centralizing data on one open, organization-wide data lake to eliminate sprawl and reduce duplication. It allows creating and managing AI models on a single foundation, reducing data movement and time to value.

6. Respondents are investing in underlying data architecture for AI

According to the study, manufacturers plan to invest in AI-powered factories of the future within the next two years. On average, respondents expected their organizations to increase their investments in software for orchestrating edge AI by 11%. This investment shows that they recognize the need to overcome technical and skill gaps to fully exploit AI’s capabilities in future manufacturing processes.

How to invest in underlying architecture for AI?

Microsoft recommends embracing advanced technologies such as centralized device management, software containerization at the edge, and unified industrial data operations to accelerate industrial transformation and prepare for AI.

Accelerate industrial transformation in manufacturing

To learn more read the full 2024 IoT Signals report, a comprehensive survey of manufacturers’ priorities, challenges, and plans for adopting new technologies, such as these, in their factories to prepare for AI. The report shows that manufacturers are looking for solutions that can help them secure, scale, and automate. Microsoft Azure is responding to these needs with its adaptive cloud approach, which offers a flexible and scalable platform for managing devices, applications, and integrated data across the edge and the cloud.

To view a presentation of this survey by IoT Analytics’ CEO and Microsoft’s GM of Azure IoT and Edge, recorded at HMI 2024, click here.

To discover more insights and best practices for accelerating industrial transformation, download the 2024 IoT Signals report below.

Download the 2024 IoT Signals report
The post 6 findings from IoT Signals report: Manufacturers prepare their shop floor for AI appeared first on Azure Blog.
Quelle: Azure

18. Juni 2024

da Agency

Azure OpenAI Service: Transforming legal practices with generative AI solutions

In today’s fast-paced legal environment, the ability to efficiently manage and analyze vast amounts of data is crucial. And the field of law is no exception. In fact, a 2023 research paper claimed that of all the industries affected by new AI, the legal field was most exposed.1 AI is increasingly being leveraged to meet this need, enhancing the capabilities of legal professionals, and improving outcomes for clients. A recent Thomson Reuters survey reported that 82% of law firm lawyers said they believe that ChatGPT and generative AI could be readily applied to legal work.2 Another research report, by economists at Goldman Sachs, estimated that 44% of legal work could be automated.3

Over the past several years, the data landscape has exploded, presenting legal teams with the challenge of managing not only increasing volumes of data but also a variety of new data types. Traditional sources like emails and documents are now accompanied by more complex sources such as collaboration platforms, chat data, text messages, and video recordings. Given the potential relevance of all this information in legal matters, modern legal teams must be prepared to identify, collect, and analyze vast amounts of data—often under tight deadlines. A number of law firms and legal service providers are using AI to streamline processes, reduce risks, and increase efficiency. Notably, companies like Icertis, Relativity, and Clifford Chance are pioneering the integration of AI into their workflows, demonstrating the transformative power of Azure AI Services in the legal field.

Azure OpenAI Service

Support better legal services

Explore our capabilities

Key benefits and applications at work

The following AI applications can help teams throughout the legal field manage contracts more efficiently, reduce risk, ensure compliance, and drive better legal business:

Enhanced document review: Uses natural language processing to analyze documents, providing relevant insights for legal cases.

Accelerated e-discovery: Quickly identifies, collects, and analyzes large volumes of data from various sources.

Improved efficiency: Reduces the time and resources needed for document review.

Identification of key information: Uncovers critical terms and conditions buried within documents.

Risk management: Assist legal users to consider problematic terms and ensure compliance.

Cognitive translation: Implements AI-driven translation to improve communication across languages.

Accessible contracts: Natural language processing capabilities help users navigate and understand complex legal language.

Enhanced decision-making: Provides insights for more informed strategic decisions.

Below we look at three companies who have adopted Azure OpenAI Service to support their legal practices, illustrating the profound impact and potential of these technologies in reshaping the industry.

Revolutionizing contract life cycle management with generative AI and AzureContracts can be crucial in business, but managing them often remains disjointed across departments, and may lead to inefficiencies and risks. Icertis, used by 30% of Fortune 100 companies, has partnered with Microsoft to enhance contract management using AI. Their platform, Icertis Contract Intelligence (ICI), now incorporates generative AI through ICI Copilots, which streamlines contract reviews and uncovers hidden terms, thereby reducing risks and increasing efficiency. Icertis natively interoperates with Microsoft 365, Dynamics 365, and Azure AI to empower users to create, view, manage, and collaborate on contracts in the tools and applications they use every day. This collaboration helps customers achieve considerable time savings and better risk management. The partnership emphasizes continuous innovation and customer value, enhancing contract management capabilities and solidifying both companies’ market positions.

Relativity and Microsoft partner to deliver generative AI to litigatorsIn the realm of e-discovery, efficiently organizing and analyzing vast amounts of unstructured data is critical. Relativity, partnering with Microsoft, provides AI-powered solutions to address this challenge. Relativity leverages Microsoft Azure and GPT-4 to enhance document review processes. They developed Relativity aiR for Review on top of Azure OpenAI Service to deliver a streamlined experience directly in RelativityOne. Relativity aiR for Review, uses natural language processing to analyze documents and assists with legal reviews and investigations. This partnership promotes security, interoperability, and global reach—enabling legal teams to manage growing data volumes and diverse data types effectively.The collaboration focuses on responsible AI, aiming to deliver innovative, secure, and efficient tools for legal professionals. Relativity and Microsoft’s joint efforts aim to continue advancing AI capabilities in e-discovery and offer tools to assist with complex data challenges.

Clifford Chance trailblazes Microsoft responsible AI to improve services for its legal clientsClifford Chance, a leading British multinational law firm, leveraged advanced technologies like Azure, Azure OpenAI Service, and Microsoft Copilot for Microsoft 365 to enhance their legal services. Early implementations, such as cognitive translation, have quickly become some of their fastest-growing products, significantly improving their ability to handle sensitive, text-based information efficiently. Additionally, the firm benefits from intelligent recap and enhanced data security features through Microsoft Teams Premium, resulting in substantial cost savings and improved protection of client data. By integrating AI-powered solutions, Clifford Chance aims to free up their professionals’ time for strategic tasks and provide innovative, efficient services to their clients. The firm is excited about the potential of large language models (LLMs) and other AI tools to further transform their operations, making them more responsive and effective in a highly competitive and time-pressured environment.

Azure OpenAI Service: Impact

The integration of Azure AI Services is assisting legal professionals in managing data, conducting reviews, and offering services. Companies like Icertis, Relativity, and Clifford Chance are leveraging AI to boost operational efficiency and foster a more innovative and responsive legal system. As AI technologies continue to advance, their impact on the legal industry will grow, driving greater efficiencies and yielding better outcomes for all stakeholders.

Our commitment to responsible AI

Organizations across industries are leveraging Azure OpenAI Service and copilot services and capabilities to drive growth, increase productivity, and create value-added experiences. From advancing medical breakthroughs to streamlining manufacturing operations, our customers trust that their data is protected by robust privacy protections and data governance practices. As our customers continue to expand their use of our AI solutions, they can be confident that their valuable data is safeguarded by industry-leading data governance and privacy practices in the most trusted cloud on the market today.

At Microsoft, we have a long-standing practice of protecting our customers’ information. Our approach to responsible AI is built on a foundation of privacy, and we remain dedicated to upholding core values of privacy, security, and safety in all our generative AI products and solutions.

Get started with Azure OpenAI Service

Apply for access to Azure OpenAI Service by completing this form.

Learn about Azure OpenAI Service and the latest enhancements.

Get started with GPT-4 in Azure OpenAI Service in Microsoft Learn.

Read our partner announcement blog, empowering partners to develop AI-powered apps and experiences with ChatGPT in Azure OpenAI Service.

Learn how to use the new Chat Completions API (in preview) and model versions for ChatGPT and GPT-4 models in Azure OpenAI Service.

Learn more about Microsoft Azure AI Content Safety.

1 How will Language Modelers like ChatGPT Affect Occupations and Industries? Ed Felten, Manav Raj, and Robert Seamans, March 18, 2023.

2 Thomson Reuters, ChatGPT & Generative AI in Law Firms: New Report Shows Opportunities Abound, April 19, 2023.

3 Goldman Sachs, Global Economics Analyst: The Potentially Large Effects of Artificial Intelligence on Economic Growth, Jan Hatzius, Joseph Briggs, Devesh Kodnani, and Giovanni Pierdomenico, March 26, 2023.
The post Azure OpenAI Service: Transforming legal practices with generative AI solutions appeared first on Azure Blog.
Quelle: Azure

18. Juni 2024

da Agency

Unlock new potential for your SAP workloads on Azure with these learning paths

SAP, a leading provider of enterprise resource planning (ERP) software, is a mission-critical consideration for companies migrating to Azure. Microsoft and SAP have a strong partnership centered on helping customers successfully migrate their SAP workloads to Azure, offering solutions that can be seamlessly integrated with Azure’s cloud infrastructure:

Accelerated cloud savings: As the leading provider for SAP workloads, let us manage your infrastructure as you streamline your cloud spending.

AI intelligence built-in: Harness the power of AI-powered insights to make data-driven decisions that drive your business forward.

Boost productivity and innovation: Integrated apps streamline your team’s workflow and automate repetitive business processes.

Enhanced protection: Our multi-layered cloud security ensures your SAP workloads run smoothly, backed by integrated Azure recovery services.

Together, SAP and Microsoft are not just providing tools and services but are also creating ecosystems that foster innovation and transformation, enabling businesses to stay competitive in a rapidly evolving digital landscape. To help you and your team better take advantage of these benefits, we’ve created an array of learning materials and interactive events—from self-guided courses to Virtual Training Days, certifications to conferences—that build your cloud expertise.

Chart your course to expertise with personalized Learning Paths

Our Microsoft Learn Learning Paths are curated collections of free, online modules and resources designed to help you build specific skills or gain knowledge in a particular technology or subject area. We have a full range of paths related to migrating SAP workloads, including:

Explore Azure for SAP Workloads: Streamline your SAP operations and maximize ROI with our comprehensive Azure training. Empower your team to seamlessly migrate, manage, and optimize SAP workloads on Azure, leveraging its robust infrastructure and specialized tools. This comprehensive training will enhance your SAP performance, drive efficiency, and unlock innovation within your existing environment.

Deploy SAP on Azure: To boost your SAP efficiency and reliability, your team will master the deployment of SAP solutions on Azure, including single-instance SAP HANA and SAP NetWeaver high availability configurations. This expertise will streamline migrations, optimize performance, and ensure smooth operations, ultimately reducing costs and maximizing the value of your SAP investment.

Explore the foundations of IaaS for SAP on Azure: Unlock the power of Azure’s Infrastructure as a Service (IaaS) for your SAP workloads. Our comprehensive training equips your team with the expertise to design and deploy scalable, high-performing SAP solutions on Azure. By mastering essential Azure resources like virtual machines, virtual networks, storage accounts, and Microsoft Entra ID, you’ll optimize your infrastructure for efficiency and resilience, ultimately driving business growth.

Explore SAP HANA on Azure (Large Instances): Optimize your SAP HANA investment as this program equips your team with the expertise to architect, deploy, and manage SAP HANA on Azure (Large Instances) effectively. By mastering key concepts like high availability, disaster recovery, security, and cost optimization, your business can ensure a resilient, secure, and cost-effective SAP HANA environment in the cloud.

Microsoft Sentinelu003cbru003e

Build next-generation security operations powered by the cloud and AI

Plan to deploy the Microsoft Sentinel solution for SAP: This standalone learning module provides an overview of Microsoft Sentinel’s comprehensive security solution for SAP environments. It outlines the roles and responsibilities of the team members involved in designing, deploying, and implementing this solution.

Improve SAP seller productivity with Microsoft Teams and Power Platform: Streamline your sales and service processes with our SAP and Microsoft 365 integration training. Your team will master integrating Teams with SAP Sales and Service Core, enabling seamless collaboration. Additionally, they’ll learn to automate tasks using Power Automate, enhancing productivity and efficiency for your SAP sellers.

Planning and deploying SAP on Azure: Unlock the power of Azure to optimize your SAP operations. Our comprehensive course teaches you to efficiently deploy, configure, and manage SAP workloads in the cloud. Gain expertise in migrating and operating SAP solutions, mastering essential Azure resources like VMs, storage, and networking. Enhance scalability, performance, and security while reducing costs.

Migrate and Modernize SAP in the Microsoft Cloud: Accelerate your SAP deployment on Azure with our one-day course for experienced SAP professionals. Gain hands-on expertise in setting up Azure infrastructure specifically for SAP, including virtual machines, networking, storage, and identity management. Learn best practices for backup, disaster recovery, and monitoring to ensure optimal performance and reliability of your SAP environment in the cloud.

Microsoft Azure

Get started with Azure now with pay-as-you-go pricing

Try today

Learn from the pros with live, interactive Virtual Training Days

Virtual Training Days are instructor-led classes designed to equip individuals and teams with in-demand skills related to cloud migration, AI, and other cutting-edge technologies. We offer Virtual Training Days to help you migrate SAP to Azure, optimizing your performance, reliability, and scalability while reducing costs. In this session, Migrate and Modernize SAP on the Microsoft Cloud, you’ll find out how to secure and monitor SAP workloads on Azure. Come explore how this move enhances productivity, fosters secure collaboration, and gives you AI-powered insights for greater efficiency. Register for our next session here.

Showcase your accomplishments with Certifications

Microsoft Certifications are the official badges that prove you’ve got the skills, whether it’s Azure, Microsoft 365, or other technologies. Getting certified isn’t just a pat on the back; it’s a ticket to career opportunities and industry recognition. Plus, it keeps you on top of the latest tech trends. So, if you want your IT game strong, Microsoft Certifications are the way to go.

Planning and Administering Microsoft Azure for SAP Workloads: To qualify for this certification, you need in-depth knowledge of SAP systems and industry standards for migration, integration, and long-term operation on Azure. Professionals in this career collaborate with cloud administrators, database administrators, and clients to implement solutions, recommending services and adjusting resources for optimal performance and resilience.

Connect and learn: Network with industry leaders at the SAP Sapphire conference

SAP Sapphire 2024 was a series of global events that brought together SAP experts, partners, and customers to explore the latest innovations and strategies in business technology. With a focus on empowering businesses to turn their visions into reality, SAP Sapphire blended in-person and virtual experiences to share valuable insights, practical knowledge, and networking opportunities to help you drive digital transformation and achieve your business goals.

Azure experts were on hand to share their expertise and discuss developments related to the cloud and AI. Both sessions are available on-demand for viewing:

Unlock innovation with AI on the Microsoft Cloud: We discussed how integrating AI with Azure and SAP solutions can help your organization learn valuable insights, automate processes, and optimize efficiency for your most critical business operations. This session showed participants how to make AI a reality for their organizations, boosting productivity and creating new opportunities for growth.

Accenture’s RISE with SAP journey with Microsoft and generative AI: Discover how Accenture, a global IT services and consulting firm, successfully migrated to the RISE with SAP solution on Microsoft Cloud, leveraging Microsoft AI solutions for enhanced innovation and efficiency. This collaborative effort among Accenture, Microsoft, and SAP resulted in a transformed enterprise system, delivering greater insights, agility, and operational efficiency.

Explore more SAP sessions delivered at Sapphire here.
The post Unlock new potential for your SAP workloads on Azure with these learning paths appeared first on Azure Blog.
Quelle: Azure

18. Juni 2024

da Agency

Get the best value in your cloud journey with Azure pricing offers and resources

A guide for businesses to align their pricing needs with their cloud journey

Cloud computing continues to transform the way businesses operate, innovate, and compete. And whether you’re just moving to the cloud or already have an established cloud footprint, you may have questions about how to pay for the services you need, estimate your costs, or optimize your spending. To help answer these questions, Azure provides a variety of resources and offers to help you get the best value at every stage of your cloud journey.

This blog post will show you how to approach and think about pricing throughout your cloud adoption journey. We will also give an example of how a hypothetical digital media company would approach their Azure pricing needs as they transition from evaluating and planning to setting up and running their cloud solutions. After reading this post, you will know more about how to select the best Azure pricing option for your business objectives and cloud needs.

Find guidance and resources to navigate Azure pricing options

If you are new to Azure or cloud computing in general, you may want to learn the basics of how cloud services are priced, and what options you have for paying for them. Azure offers a variety of pricing options to suit different needs and scenarios, from free tier and pay-as-you-go to commitment and benefits. Here’s a brief overview of each option:

Free tier: You can get started with Azure for free, and access over 25 services for 12 months, plus $200 credit to use in your first 30 days. You can also use some services for free, such as Azure App Service, Azure Functions, and Azure DevOps, with certain limits and conditions. The free tier is a great way to explore Azure and learn how it works, without any upfront costs or commitments.

Pay-as-you-go: You can pay only for the services you use or consume, based on the measured usage and the unit prices of each service. For example, you can pay for the number of virtual machine (VMs) hours, the amount of storage space, or the volume of data transferred. Pay-as-you-go is a flexible and scalable option that lets you adjust your usage and costs according to your changing needs and demands.

Read more about how Azure pricing works here.

Estimate Azure project costs

If you have a new project to migrate to or build in Azure, you need an accurate and realistic estimate of your project costs to make an informed decision about moving forward. To help with this decision, Azure provides several tools and resources, such as:

TCO calculator: You can use the Total Cost of Ownership (TCO) calculator to estimate how much you can save by migrating your on-premises workloads to Azure. You can input your current infrastructure details, such as servers, storage, and network, and see a detailed comparison of the costs of running them on-premises versus on Azure.

Azure Migrate: You can use Azure Migrate to assess and plan your migration to Azure. You can discover and evaluate your on-premises servers, databases, and applications, and get recommendations on the best Azure services and sizing options for them. You can also get estimated costs and savings for your migration scenario and track your progress and readiness.

Azure Architecture Center: You can get guidance for architecting solutions on Azure using established patterns and practices such as OpenAI Chatbots, Windows VM Deployment, and Analytics end-to-end with Azure Synapse with cost factors included.

Read more about estimating project costs here.

Calculate costs of Azure products and services

If you are ready to deploy specific Azure services and you want to budget for them, you may want to consider the different pricing options and offers that are available for each service. Azure provides resources and guidance on how to budget for specific Azure services, such as:

Azure pricing calculator: Estimate your monthly costs based on your expected usage and configuration such as region or virtual machine series.

Product pricing details pages: Find detailed pricing information for each Azure service on its pricing details page. You can see the pricing model, the unit prices, the service tiers, and the regional availability.

Azure savings plan for compute: An easy and flexible way to save up to 65% on select compute services, compared to pay-as-you-go prices. The savings plan unlocks lower prices on compute services when you commit to spend a fixed hourly amount for one or three years. You choose whether to pay all upfront or monthly at no extra cost.

Azure reservations: Reserve Azure resources, such as VMs, SQL Database, or Cosmos DB, for one or three years and save up to 72% on your cloud costs. Improve budgeting and forecasting with a single upfront payment that makes it easy to calculate your investments. Or lower your upfront cash outflow with a monthly payment option at no additional cost.

Azure Hybrid Benefit: Apply your existing Windows Server, SQL Server licenses with active Software Assurance or subscriptions to Azure Hybrid Benefit to achieve cost savings. Save up to 85% compared to standard pay-as-you-go rates and achieve the lowest cost of ownership when you combine Azure Hybrid Benefit, reservations savings, and Extended Security Updates. You can also apply your active Linux subscription to Azure Hybrid Benefit.

Read more about budgeting for Azure products and services here.

Manage and optimize your Azure investments

If you are already using Azure and you want to optimize your spend for your current Azure workloads, you may want to review your usage and costs, and look for ways to enhance your investments. Azure provides several tools and resources to help you with this process, such as:

Microsoft Cost Management: You can use Microsoft Cost Management with Copilot to monitor and analyze your Azure spending, and to create and manage budgets and alerts. You can see your current and forecasted costs, your cost trends and anomalies, and your cost breakdown by service, resource group, or subscription. You can also get recommendations on how to optimize your costs.

Azure Advisor: You can use Azure Advisor to get personalized and actionable recommendations on how to improve the performance, security, reliability, and cost-effectiveness of your Azure resources. You can see the potential savings and benefits of each recommendation and apply them with a few clicks.

FinOps on Azure: You can leverage FinOps best practices on Azure to empower your organization by fostering a culture of data-driven decision-making, accountability, and cross-team collaboration. This approach will help you maximize investments and accelerate business growth through improved organizational alignment

Read more about managing and optimizing spend here.

An example of a company’s cloud journey and pricing needs

To illustrate how a customer can choose the best pricing option and resources for their cloud journey, let’s look at an example. Contoso, a hypothetical digital media company, wants to migrate their infrastructure and build a new OpenAI Chatbot application in Azure. Here’s how they would think about their Azure pricing needs at each stage of their journey:

Considering Azure: Contoso wants to understand how Azure pricing works. They use the free tier to try out some Azure services to test functionality. They also leverage the pay-as-you-go model to explore how some services are billed.

Assess and plan Azure projects: Contoso needs to estimate their project costs. To compare the costs of running on-premises versus on Azure they input their on-premises server infrastructure in the TCO calculator. They also use the Azure Architecture Center to learn how to develop an OpenAI chatbot with best practices.

Deployment in Azure: Contoso is ready to migrate their environment and deploy their company’s chatbot app and wants to budget for the specific Azure services needed. They leverage the product specific pricing pages and the pricing calculator to estimate their monthly costs based on their expected usage and configuration. They purchase Reservations for their stable and predictable VMs and Azure Database usage. They already have on-premise Windows Server licenses, so they enroll in Software Assurance to get a credit for those licenses with the Azure Hybrid Benefit when deploying their VMs to save on operating costs.

Post-deployment optimization in Azure: After running their environment on Azure for a few months, Contoso wants to review and optimize their workloads. They use Azure Advisor to get personalized and actionable recommendations on how to enhance their cost-effectiveness. Leveraging these recommendations, they purchase Azure savings plan for compute for their dynamic compute workloads that may change regions or scope and right-size their VMs.

Learn more about Azure pricing

We hope this blog post has helped you understand how to consider Azure pricing in your cloud journey. Whether you are just getting started, ready to deploy, or looking for ways to optimize, Azure has pricing resources that suit your needs and goals. To learn more about Azure pricing, visit the Azure pricing overview page, where you can find more explanatory content, tools, and resources.

Azure pricing

Get the best value at every stage of your cloud journey

Additional resources:

Azure Enablement Show | Understand Azure pricing & resources

Azure Enablement Show | Learn to budget & optimize in Azure

Blog: Azure pricing | How to navigate Azure pricing options and resources

Blog: Azure pricing | How to estimate Azure project costs

Blog: Azure pricing | How to calculate costs of Azure products and services

Blog: Azure pricing | How to optimize costs for your Azure workloads

Azure pricing skilling content collection
The post Get the best value in your cloud journey with Azure pricing offers and resources appeared first on Azure Blog.
Quelle: Azure

18. Juni 2024

da Agency

Microsoft and ServiceNow at Knowledge 2024: Introducing generative AI innovation

We are in the midst of a major platform shift where AI has emerged as a transformative force that’s redefining productivity in the workplace. This evolution compels organizations to embrace new technologies that not only enhance efficiency but also foster innovation and champion responsible design. That’s why Microsoft is proud to partner with ServiceNow, a leader in digital workflows and generative AI, to create seamless and powerful experiences that empower every organization on the planet to achieve more.

Are you ready to put AI to work?

Innovation Unleashed: ServiceNow and the Microsoft Cloud

Discover more

Collaboration and integration with ServiceNow at Knowledge 2024

I had the opportunity to celebrate the results of this partnership at Knowledge 2024, ServiceNow’s flagship event that brought together 20,000 global business leaders, IT professionals, partners, and developers. During this time, industry professionals from both Microsoft and ServiceNow discussed how we’re joining efforts to boost collaboration, increase efficiency, and streamline business processes by integrating generative AI solutions. It was an honor to also have Microsoft Chief Executive Officer Satya Nadella join the keynote, where he expressed gratitude for the progress we’ve made in this partnership and enthusiasm for future innovation.

Since 2019, as partners, Microsoft and ServiceNow have been jointly innovating to bring the best of the Microsoft Cloud and the ServiceNow platform to improve customer and employee experiences. We have delivered over 100 pre-built integrations that provide our mutual customers with the ability to confidently plan, scale, and manage cloud adoption and their digital transformation initiatives.

As an example of this commitment, we recently migrated our internal ServiceNow instances to Azure, introducing greater interoperability between our platforms. Our mutual customers can also procure ServiceNow on Azure through the Azure Marketplace, and streamline procurement against their existing Azure commitment. This strategic collaboration, which combines the power of ServiceNow’s business transformation capabilities with Azure’s cloud infrastructure, has ushered in a host of new and exciting solutions to accelerate cloud value, enhance employee experiences, and invent new AI use cases. It was a privilege to witness the unveiling of one of those solutions at Knowledge 2024—a new connection between the ServiceNow platform and Microsoft Copilot. With this integration, organizations can now access top-tier generative AI models within the natural flow of their work.

Why have one when you could have two powerful generative AI assistants?

Think about how helpful it would be if employees had access to round-the-clock support to fix problems and maximize productivity. This is the vision we’re realizing by combining ServiceNow and Microsoft AI assistants to enhance employee choice and flexibility. The resulting ServiceNow Now Assist and Microsoft Copilot integration allows generative AI experiences to coexist within the same ecosystem. The Now Platform is widely used for IT management, security operations, field service management, compliance, HR, and workflow automation. Now, both ServiceNow and Microsoft customers can benefit from intelligent support using natural language—inside the Now Platform or Microsoft 365.

This new integration lets users benefit from digital assistants on both platforms without leaving their workflows. For example, when a buyer initiates a purchase order for office supplies, Copilot generates the purchase order using simple prompts. It then hands it off to Now Assist to finalize within ServiceNow. The buyer can move quickly through the ordering process without switching platforms or programs. Whichever AI assistant knows the answer will respond, unlocking a newfound level of efficiency and eliminating context switching.

To explore other AI-based enhancements to the Now Platform, watch the demo below:

Generative AI is a personal initiative that’s driving internal value

How are ServiceNow and Microsoft seeing value with generative AI? I had the opportunity to explore this question and more with Nalina Athyantha, Senior Vice President of Enterprise Field Marketing at ServiceNow. Responding to the recent announcement of the ServiceNow platform and Microsoft Copilot integration, Nalina and I were able to provide context for these new developments in the partnership and share more about where this alliance is headed. During our conversation, we discussed the importance of upleveling employee experiences by streamlining workflows and eliminating redundancies with AI. I was impressed to hear how ServiceNow itself is reaping the benefits of AI by embedding these capabilities into the systems their employees use daily. The organization has already observed a $10 million dollar reduction in costs with a notable increase in productivity. By enabling seamless AI-assisted experiences with Now Assist and Microsoft 365 applications, both ServiceNow and Microsoft are seeing the impact firsthand through the lens of our respective organizations. And we’re excited to extend that value to our shared customers, too.

Watch the video below to hear my entire conversation with Nalina:

We’re proud to be innovating alongside pioneers like ServiceNow

I want to extend a sincere thanks to ServiceNow on behalf of Microsoft for recognizing us as their 2024 Innovation Partner of the Year as well as the 2024 Build Partner of the Year. The latter award was particularly meaningful as it commends our joint effort in creating and delivering seamless user experiences on the Now Platform and Azure.

We believe that we can achieve more by collaborating with ServiceNow. That’s why we appreciated the chance to embrace the learning aspect of Knowledge 2024 and show others how they can benefit from integrating ServiceNow into their Microsoft ecosystem. Our team at Microsoft led two sessions during the event that helped attendees delve deeper into ServiceNow on Azure. Reenu Saluja, a Global Partner Technology Strategist within Microsoft’s Industry Partner Solution Organization, and Stephen Bidgood, an Advisory Solution Consultant at ServiceNow, walked participants through a live Q&A that provided a technical overview of AI, security, and modern work. This interactive format allowed for an engaging learning experience that was equally enriching on both sides. While I discussed the value of ServiceNow and the Microsoft Cloud, innovating together and exploring the integration opportunities.

Microsoft team accepts the award as ServiceNow’s 2024 Innovation Partner of the Year and 2024 Build Partner of the Year.

The digital transformation journey continues

The ServiceNow Knowledge 2024 event highlighted how Microsoft and ServiceNow can help organizations of all sizes accelerate their cloud transformation with generative AI. We’re excited about the future of AI innovation that Microsoft and ServiceNow can enable together.

For a more in-depth look at the newly announced integration and to learn more about Microsoft and ServiceNow’s partnership, read our blog “Innovation Unleashed: ServiceNow and the Microsoft Cloud.”
The post Microsoft and ServiceNow at Knowledge 2024: Introducing generative AI innovation appeared first on Azure Blog.
Quelle: Azure

18. Juni 2024

da Agency

Improve cloud performance and reliability with a guided learning plan

Businesses have committed to the cloud for its scalability, agility, and security. As customers continue to deepen their investments in cloud and AI services and environments become more complex, the need for proper cloud management increases. Continuous improvement and careful management through all phases of your cloud journey helps avoid unexpected costs and inefficient resource allocation while improving security and reliability. Strategic optimization delivers the resiliency to efficiently and securely handle fluctuating workloads with ease, ensuring you manage your environment for optimal performance.

Plans on Microsoft Learn

Increase your skills and optimize your performance

Learn more

For cloud professionals looking to systematically upskill and validate their expertise, we’ve created a powerful learning resource called Plans on Microsoft Learn. These customized learning journeys provide a guided, structured approach to mastering specific technical domains and roles with specific learning objectives and milestones. Our official plan, “Improve Reliability, Security and Performance on Azure”, provides learning modules and resources on tools and best practices from Microsoft that can help your business elevate reliability, security, and performance of your cloud and AI investments.

What are Plans on Microsoft Learn?

Plans on Microsoft Learn are hand-crafted curricula that bundle together related Learn modules, learning paths, and certifications into milestones with a logical, end-to-end educational experience. Track progress and percent-completion of each milestone as you work through the plan. Each plan is meticulously designed by Microsoft technical and learning experts to build comprehensive skills for a particular job role or competency area.

Plans offer an efficient, curated approach for learners to navigate Microsoft’s extensive training library. Rather than having to sift through the catalog of individual resources, plans lay out an optimal sequence tailored to each topic and learning objective. They start with fundamentals and progressively advance to more specialized subjects through thoughtful progression.

Beyond just compiling content, plans incorporate hands-on activities, knowledge checks, certifications, and other engagement tools to reinforce practical skills. Up-to-date Microsoft Azure technical content is seamlessly woven in, allowing learners to receive the latest cloud best practices.

What are the benefits of Plans on Microsoft Learn?

While the self-guided flexibility of Microsoft Learn is incredibly empowering, following an official plan yields some distinct benefits:

Comprehensiveness. Plans provide complete coverage of all the concepts and skills required to truly master a domain, leaving no gaps.

Efficiency. The resources within plans are carefully curated, allowing learners to laser-focus their efforts on just what’s needed.

Structure. Clear start-to-finish learning paths prevent knowledge fragmentation and facilitate efficiently building specialized skillsets.

Hands-on. Built-in coding, labs, and other interactive components solidify skills through applied practice.

Validated expertise. Plans can incorporate certifications to formally validate and prove proficiency.

Latest skills. Leveraging Microsoft’s deep technical expertise, plans rapidly integrate the latest cloud service updates and best practices.

What will I learn in the “Improve Reliability, Security and Performance on Azure” Plan?

With cloud spend efficiency becoming an ever-growing priority, these optimization skills are invaluable to organizations seeking to maximize their ROI from Azure. Among our official Learn Plans, the “Improve Reliability, Security, and Performance on Azure” Plan stands out for its immense business value and career impact potential. This comprehensive curriculum is designed to equip learners with deep skills for confidently designing, implementing, and managing cost-optimized Azure architectures at scale.

The Plan kicks off with fundamental cloud concepts like subscription management and organizational structure. It covers core Azure services like virtual machines, storage, databases, and networking through an optimization lens.

Learners then progress to more advanced cost optimization strategies such as reservation model pricing, Microsoft Azure Hybrid Benefit, and the Microsoft Azure Consumption Commitment. Monitoring, analytics, and automation techniques are explored for proactively identifying inefficiencies and waste.

Throughout, learners get hands-on practice with cost management and optimization tools like Azure Advisor, Azure Pricing Calculator, and Cost Management + Billing. Real-world design scenarios challenge them to apply optimization best practices end-to-end.

For those seeking validation, this Skilling Plan aligns perfectly with the AZ-305: Designing Microsoft Azure Infrastructure Solutions expert-level certification exam.

Upon completing the Plan, learners will have cultivated a comprehensive, job-ready skillset for designing and implementing cost-optimized, high-scale Azure architectures. This turbo-charges their impact across roles like cloud architects, solution engineers, cloud administrators and more.

Who should engage with this Plan?

This Azure Skilling Plan is designed for a broad audience, including:

Cloud architects and engineers. Gain the skills to design and implement optimized Azure solutions from the ground up.

Developers. Learn how to build applications that are inherently cost-efficient and performant.

IT pros. Understand how to manage and optimize your existing Azure resources.

Anyone with a passion for the cloud. Whether you’re new to Azure or an experienced pro, this plan offers valuable insights and practical skills to level up your cloud game.

What can I learn next?

After completing the official plan to “Improve Reliability, Security, and Performance on Azure,” you’ll find there’s lots more to discover on Microsoft Learn.

Our Learn Live sessions deliver technical readiness and skilling programming in a television format, typically broadcasted live with Q&A and available on-demand. 

Azure Optimization Virtual Training Days aim to funnel Microsoft’s know-how into helping you optimize and manage your cloud investment. Guided by a Microsoft Technical Trainer, you’ll discover how Azure guidance, resources, and practices can streamline your cloud spend, enable modernization, and fuel innovation in the cloud.

How do I get started?

Whether you’re a cloud pro looking to formalize your optimization chops, or just starting to navigate Microsoft’s vast cloud learning ecosystem, the Microsoft official Plan “Improve Reliability, Security, and Performance on Azure” offers a powerful way to accelerate your skilling. By engaging with its learn modules, you’ll be equipped to confidently design, deploy and manage cost-efficient, high-performance Azure architectures that deliver maximum business value.

Getting started is simple. Head over to Microsoft Learn and enroll in the “Improve Reliability, Security, and Performance on Azure” Plan. The content is organized into logical milestones, so you can easily track your progress and pick up where you left off. Take advantage of the hands-on labs and community forums to solidify your understanding and connect with fellow learners.
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Quelle: Azure