Mastering Azure

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.

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.

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.

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Get to grips with artificial intelligence and cybersecurity techniques to respond to adversaries and incidents Key FeaturesLearn how to secure your Azure cloud workloads across applications and networksProtect your Azure infrastructure from cyber attacksDiscover tips and techniques for implementing, deploying, and maintaining secure cloud services using best practicesBook Description Security is integrated into every cloud, but this makes users put their guard down as they take cloud security for granted. Although the cloud provides higher security, keeping their resources secure is one of the biggest challenges many organizations face as threats are constantly evolving. Microsoft Azure offers a shared responsibility model that can address any challenge with the right approach. Revised to cover product updates up to early 2022, this book will help you explore a variety of services and features from Microsoft Azure that can help you overcome challenges in cloud security. You'll start by learning the most important security concepts in Azure, their implementation, and then advance to understanding how to keep resources secure. The book will guide you through the tools available for monitoring Azure security and enforcing security and governance the right way. You'll also explore tools to detect threats before they can do any real damage and those that use machine learning and AI to analyze your security logs and detect anomalies. By the end of this cloud security book, you'll have understood cybersecurity in the cloud and be able to design secure solutions in Microsoft Azure. What you will learnBecome well-versed with cloud security conceptsGet the hang of managing cloud identitiesUnderstand the zero-trust approachAdopt the Azure security cloud infrastructureProtect and encrypt your dataGrasp Azure network security conceptsDiscover how to keep cloud resources secureImplement cloud governance with security policies and rulesWho this book is for This book is for Azure cloud professionals, Azure architects, and security professionals looking to implement secure cloud services using Azure Security Centre and other Azure security features. A solid understanding of fundamental security concepts and prior exposure to the Azure cloud will help you understand the key concepts covered in the book more effectively.

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.

Become an expert in implementing Azure Functions to work seamlessly with your serverless applications Key FeaturesDevelop scalable, robust multi-tier apps without worrying about infrastructure needsDeploy and manage cost-effective and highly available serverless apps using Azure FunctionsAccelerate enterprise-level application development by seamlessly integrating different cloud services with Azure FunctionsBook Description Application development has evolved from traditional monolithic app development to using serverless options and microservices. This book is designed to guide you through using Microsoft's Azure Functions to process data, integrate systems, and build simple APIs and microservices. You will discover how to apply serverless computing to speed up deployment and reduce downtime. You'll also explore Azure Functions, including its core functionalities and essential tools, along with understanding how to debug and even customize Azure Functions. In addition to this, the book will take you through how you can effectively implement DevOps and automation in your working environment. Toward the concluding chapters, you'll cover some quick tips, troubleshooting techniques, and real-world serverless use cases that will help you make the most of serverless computing. By the end of this book, you will have gained the skills you need to develop and deliver cost-effective Azure serverless solutions. What you will learnCreate and deploy advanced Azure FunctionsLearn to extend the runtime of Azure FunctionsOrchestrate your logic through code or a visual workflowAdd caching, security, routing, and filtering to your APIsUse serverless technologies in real-world scenariosUnderstand how to apply DevOps and automation to your working environmentWho this book is for This book is designed for cloud administrators, architects, and developers interested in building scalable systems and deploying serverless applications with Azure Functions. Prior knowledge of core Microsoft Azure services and Azure Functions is necessary to understand the topics covered in this book.

A practical guide that will help you transform your data into actionable insights with Azure Synapse Analytics KEY FEATURES ● Explore the different features in the Azure Synapse Analytics workspace. ● Learn how to integrate Power BI and Data Governance capabilities with Azure Synapse Analytics. ● Accelerate your analytics journey with the no-code/low-code capabilities of Azure Synapse. DESCRIPTION Cloud analytics is a crucial aspect of any digital transformation initiative, and the capabilities of the Azure Synapse analytics platform can simplify and streamline this process. By mastering Azure Synapse Analytics, analytics developers across organizations can boost their productivity by utilizing low-code, no-code, and traditional code-based analytics frameworks. This book starts with a comprehensive introduction to Azure Synapse Analytics and its limitless cloud-scale analytics capabilities. You will then learn how to explore and work with data warehousing features in Azure Synapse. Moving on, the book will guide you on how to effectively use Synapse Spark for data engineering and data science. It will help you learn how to gain insights from your data through Observational analytics using Synapse Data Explorer. You will also discover the seamless data integration capabilities of Synapse Pipeline, and delve into the benefits of Synapse Analytics' low-code and no-code pipeline development features. Lastly the book will show you how to create network topology and implement industry-specific architecture patterns in Azure Synapse Analytics. By the end of the book, you will be able to process and analyze vast amounts of data in real-time to gain insights quickly and make informed decisions. WHAT YOU WILL LEARN ● Leverage Synapse Spark for machine learning tasks. ● Use Synapse Data Explorer for telemetry analysis. ● Take advantage of Synapse's common data model-based database templates. ● Query data using T-SQL, KQL, and Spark SQL within Synapse. ● Integrate Microsoft Purview with Synapse for enhanced data governance. WHO THIS BOOK IS FOR This book is designed for Cloud data engineers with prior experience in Azure cloud computing, as well as Chief Data Officers (CDOs) and Data professionals, who want to use this unified platform for data ingestion, data warehousing, and big data analytics. TABLE OF CONTENTS 1. Cloud Analytics Concept 2. Introduction to Azure Synapse Analytics 3. Modern Data Warehouse with the Synapse SQL Pool 4. Query as a Service- Synapse Serverless SQL 5. Synapse Spark Pool Capability 6. Synapse Spark and Data Science 7. Learning Synapse Data Explorer 8. Synapse Data Integration 9. Synapse Link for HTAP 10. Azure Synapse -Unified Analytics Service 11. Synapse Workspace Ecosystem Integration 12. Azure Synapse Network Topology 13. Industry Cloud Analytics