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Helps users understand the breadth of Azure services by organizing them into a reference framework they can use when crafting their own big-data analytics solution.
Explore the advanced capabilities of Azure Virtual Desktop and enhance your skills in cloud-based virtualization and remote application delivery Key Features Learn how to design a strong architecture for your Azure Virtual Desktop Implement, monitor, and maintain a virtual desktop environment Gain insights into Azure Virtual Desktop and prepare successfully for the AZ-140 exam Purchase of the print or Kindle book includes a free PDF eBook Book Description Acquire in-depth knowledge for designing, building, and supporting Azure Virtual Desktop environments with the updated second edition of Mastering Azure Virtual Desktop. With content aligned with exam objectives, this book will help you ace the Microsoft AZ-140 exam. This book starts with an introduction to Azure Virtual Desktop before delving into the intricacies of planning and architecting its infrastructure. As you progress, you’ll learn about the implementation process, with an emphasis on best practices and effective strategies. You’ll explore key areas such as managing and controlling access, advanced monitoring with the new Azure Monitoring Agent, and advanced application deployment. You’ll also gain hands-on experience with essential features like the MSIX app attach, enhancing user experience and operational efficiency. Beyond advancing your skills, this book is a crucial resource for those preparing for the Microsoft Certified: Azure Virtual Desktop Specialty certification. By the end of this book, you’ll have a thorough understanding of the Azure Virtual Desktop environment, from design to implementation. What you will learn Architect a robust Azure Virtual Desktop setup Master the essentials of networking and storage configurations Create and configure session host images and host pools Gain insights into controlling access and enhancing security Implement FSLogix profile containers and Cloud Cache for improved performance Discover MSIX app attach for efficient application delivery Understand strategies for business continuity and disaster recovery Monitor and manage the performance and health of your Azure Virtual Desktop environment Who this book is for Mastering Azure Virtual Desktop is for IT professionals, modern workspace administrators, architects, and consultants who want to learn how to design, implement, and manage Azure Virtual Desktop environments. Whether you're aiming to enhance your expertise in cloud virtualization or preparing for the Microsoft AZ-140 exam, this guide is an invaluable resource for advancing your skills.
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Understand, create, deploy, and maintain a public cloud using Microsoft Azure Mastering Microsoft Azure Infrastructure Services guides you through the process of creating and managing a public cloud and virtual network using Microsoft Azure. With step-by-step instruction and clear explanation, this book equips you with the skills required to provide services both on-premises and off-premises through full virtualization, providing a deeper understanding of Azure's capabilities as an infrastructure service. Each chapter includes online videos that visualize and enhance the concepts presented in the book, and access to a Windows app that provides instant Azure updates and demonstrates the process of going from on-premises to public cloud via Azure. Coverage includes storage customization, connectivity, virtual networks, backing up, hybrid environments, System Center management, and more, giving you everything you need to understand, evaluate, deploy, and maintain environments that utilize Microsoft Azure. Understand cost, options, and applications of Infrastructure as a Service (IaaS) Enable on- and off-premises connectivity to Azure Customize Azure templates and management processes Exploit key technologies and embrace the hybrid environment Mastering Microsoft Azure Infrastructure Services is your total solution.
Unsure of how or where to get started with Azure API Management, Microsoft's managed service for securing, maintaining, and monitoring APIs? Then this guide is for you. Azure API Management integrates services like Azure Kubernetes Services (AKS), Function Apps, Logic Apps, and many others with the cloud and provides users with a single, unified, and well-structured façade in the cloud. Mastering Azure API Management is designed to help API developers and cloud engineers learn all aspects of Azure API Management, including security and compliance. It provides a pathway for getting started and learning valuable management and administration skills. You will learn what tools you need to publish a unified API façade towards backend services, independent of where and what they run on. You will begin with an overview of web APIs. You will learn about today's challenges and how a unified API management approach can help you address them. From there you'll dive into the key concepts of Azure API Management and be given a practical view and approach of API development in the context of Azure API Management. You'll then review different ways of integrating Azure API Management into your enterprise architecture. From there, you will learn how to optimally maintain and administer Azure API Management to secure your APIs, and learn from them, gaining valuable insights through logging and monitoring. What You Will Learn Discover the benefits of an enterprise API platform Understand the basic concepts of API management in the Microsoft cloud Develop and publish your APIs in the context of Azure API Management Onboard users through the developer portal Help your team or other developers to publish their APIs more efficiently Integrate Azure API Management securely into your enterprise architecture Manage and maintain to secure your APIs and gain insights This book is for API developers, cloud engineers, and Microsoft Azure enthusiasts who want to deep dive into managing an API-centric enterprise architecture with Azure API Management. To get the most out of the book, the reader should have a good understanding of micro services and APIs. Basic coding skills, including some experience with PowerShell and Azure, are also beneficial. Sven Malvik is an experienced Azure expert. He specializes in compliance and digital transformation, most recently in the financial industry. He has decades of experience in software development, DevOps, and cloud engineering. Sven is a Microsoft MVP in Azure and a speaker, presenting sessions and tutorials at a number of global conferences, user group meetings, and international companies.
Start empowering users and protecting corporate data, while managing Identities and Access with Microsoft Azure in different environments About This Book Deep dive into the Microsoft Identity and Access Management as a Service (IDaaS) solution Design, implement and manage simple and complex hybrid identity and access management environments Learn to apply solution architectures directly to your business needs and understand how to identify and manage business drivers during transitions Who This Book Is For This book is for business decision makers, IT consultants, and system and security engineers who wish to plan, design, and implement Identity and Access Management solutions with Microsoft Azure. What You Will Learn Apply technical descriptions and solution architectures directly to your business needs and deployments Identify and manage business drivers and architecture changes to transition between different scenarios Understand and configure all relevant Identity and Access Management key features and concepts Implement simple and complex directory integration, authentication, and authorization scenarios Get to know about modern identity management, authentication, and authorization protocols and standards Implement and configure a modern information protection solution Integrate and configure future improvements in authentication and authorization functionality of Windows 10 and Windows Server 2016 In Detail Microsoft Azure and its Identity and Access Management is at the heart of Microsoft's Software as a Service, including Office 365, Dynamics CRM, and Enterprise Mobility Management. It is an essential tool to master in order to effectively work with the Microsoft Cloud. Through practical, project based learning this book will impart that mastery. Beginning with the basics of features and licenses, this book quickly moves on to the user and group lifecycle required to design roles and administrative units for role-based access control (RBAC). Learn to design Azure AD to be an identity provider and provide flexible and secure access to SaaS applications. Get to grips with how to configure and manage users, groups, roles, and administrative units to provide a user- and group-based application and self-service access including the audit functionality. Next find out how to take advantage of managing common identities with the Microsoft Identity Manager 2016 and build cloud identities with the Azure AD Connect utility. Construct blueprints with different authentication scenarios including multi-factor authentication. Discover how to configure and manage the identity synchronization and federation environment along with multi -factor authentication, conditional access, and information protection scenarios to apply the required security functionality. Finally, get recommendations for planning and implementing a future-oriented and sustainable identity and access management strategy. Style and approach A practical, project-based learning experience explained through hands-on examples.
Mastering Azure Security enables you to implement top-level security in your Azure tenant. With a focus on cloud security, this book will look at the architectural approach on how to design your Azure solutions to keep and enforce resources secure.
Master expert techniques for building automated and highly scalable end-to-end machine learning models and pipelines in Azure using TensorFlow, Spark, and Kubernetes Key FeaturesMake sense of data on the cloud by implementing advanced analyticsTrain and optimize advanced deep learning models efficiently on Spark using Azure DatabricksDeploy machine learning models for batch and real-time scoring with Azure Kubernetes Service (AKS)Book Description The increase being seen in data volume today requires distributed systems, powerful algorithms, and scalable cloud infrastructure to compute insights and train and deploy machine learning (ML) models. This book will help you improve your knowledge of building ML models using Azure and end-to-end ML pipelines on the cloud. The book starts with an overview of an end-to-end ML project and a guide on how to choose the right Azure service for different ML tasks. It then focuses on Azure Machine Learning and takes you through the process of data experimentation, data preparation, and feature engineering using Azure Machine Learning and Python. You'll learn advanced feature extraction techniques using natural language processing (NLP), classical ML techniques, and the secrets of both a great recommendation engine and a performant computer vision model using deep learning methods. You'll also explore how to train, optimize, and tune models using Azure Automated Machine Learning and HyperDrive, and perform distributed training on Azure. Then, you'll learn different deployment and monitoring techniques using Azure Kubernetes Services with Azure Machine Learning, along with the basics of MLOps—DevOps for ML to automate your ML process as CI/CD pipeline. By the end of this book, you'll have mastered Azure Machine Learning and be able to confidently design, build and operate scalable ML pipelines in Azure. What you will learnSetup your Azure Machine Learning workspace for data experimentation and visualizationPerform ETL, data preparation, and feature extraction using Azure best practicesImplement advanced feature extraction using NLP and word embeddingsTrain gradient boosted tree-ensembles, recommendation engines and deep neural networks on Azure Machine LearningUse hyperparameter tuning and Azure Automated Machine Learning to optimize your ML modelsEmploy distributed ML on GPU clusters using Horovod in Azure Machine LearningDeploy, operate and manage your ML models at scaleAutomated your end-to-end ML process as CI/CD pipelines for MLOpsWho this book is for This machine learning book is for data professionals, data analysts, data engineers, data scientists, or machine learning developers who want to master scalable cloud-based machine learning architectures in Azure. This book will help you use advanced Azure services to build intelligent machine learning applications. A basic understanding of Python and working knowledge of machine learning are mandatory.
Supercharge and automate your deployments to Azure Machine Learning clusters and Azure Kubernetes Service using Azure Machine Learning services Key Features Implement end-to-end machine learning pipelines on Azure Train deep learning models using Azure compute infrastructure Deploy machine learning models using MLOps Book Description Azure Machine Learning is a cloud service for accelerating and managing the machine learning (ML) project life cycle that ML professionals, data scientists, and engineers can use in their day-to-day workflows. This book covers the end-to-end ML process using Microsoft Azure Machine Learning, including data preparation, performing and logging ML training runs, designing training and deployment pipelines, and managing these pipelines via MLOps. The first section shows you how to set up an Azure Machine Learning workspace; ingest and version datasets; as well as preprocess, label, and enrich these datasets for training. In the next two sections, you'll discover how to enrich and train ML models for embedding, classification, and regression. You'll explore advanced NLP techniques, traditional ML models such as boosted trees, modern deep neural networks, recommendation systems, reinforcement learning, and complex distributed ML training techniques - all using Azure Machine Learning. The last section will teach you how to deploy the trained models as a batch pipeline or real-time scoring service using Docker, Azure Machine Learning clusters, Azure Kubernetes Services, and alternative deployment targets. By the end of this book, you'll be able to combine all the steps you've learned by building an MLOps pipeline. What you will learn Understand the end-to-end ML pipeline Get to grips with the Azure Machine Learning workspace Ingest, analyze, and preprocess datasets for ML using the Azure cloud Train traditional and modern ML techniques efficiently using Azure ML Deploy ML models for batch and real-time scoring Understand model interoperability with ONNX Deploy ML models to FPGAs and Azure IoT Edge Build an automated MLOps pipeline using Azure DevOps Who this book is for This book is for machine learning engineers, data scientists, and machine learning developers who want to use the Microsoft Azure cloud to manage their datasets and machine learning experiments and build an enterprise-grade ML architecture using MLOps. This book will also help anyone interested in machine learning to explore important steps of the ML process and use Azure Machine Learning to support them, along with building powerful ML cloud applications. A basic understanding of Python and knowledge of machine learning are recommended.
Implement machine learning, cognitive services, and artificial intelligence solutions by leveraging Azure cloud technologies Key FeaturesLearn advanced concepts in Azure ML and the Cortana Intelligence Suite architectureExplore ML Server using SQL Server and HDInsight capabilitiesImplement various tools in Azure to build and deploy machine learning modelsBook Description Implementing Machine learning (ML) and Artificial Intelligence (AI) in the cloud had not been possible earlier due to the lack of processing power and storage. However, Azure has created ML and AI services that are easy to implement in the cloud. Hands-On Machine Learning with Azure teaches you how to perform advanced ML projects in the cloud in a cost-effective way. The book begins by covering the benefits of ML and AI in the cloud. You will then explore Microsoft’s Team Data Science Process to establish a repeatable process for successful AI development and implementation. You will also gain an understanding of AI technologies available in Azure and the Cognitive Services APIs to integrate them into bot applications. This book lets you explore prebuilt templates with Azure Machine Learning Studio and build a model using canned algorithms that can be deployed as web services. The book then takes you through a preconfigured series of virtual machines in Azure targeted at AI development scenarios. You will get to grips with the ML Server and its capabilities in SQL and HDInsight. In the concluding chapters, you’ll integrate patterns with other non-AI services in Azure. By the end of this book, you will be fully equipped to implement smart cognitive actions in your models. What you will learnDiscover the benefits of leveraging the cloud for ML and AIUse Cognitive Services APIs to build intelligent botsBuild a model using canned algorithms from Microsoft and deploy it as a web serviceDeploy virtual machines in AI development scenariosApply R, Python, SQL Server, and Spark in AzureBuild and deploy deep learning solutions with CNTK, MMLSpark, and TensorFlowImplement model retraining in IoT, Streaming, and Blockchain solutionsExplore best practices for integrating ML and AI functions with ADLA and logic appsWho this book is for If you are a data scientist or developer familiar with Azure ML and cognitive services and want to create smart models and make sense of data in the cloud, this book is for you. You’ll also find this book useful if you want to bring powerful machine learning services into your cloud applications. Some experience with data manipulation and processing, using languages like SQL, Python, and R, will aid in understanding the concepts covered in this book