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The AZ-400 Designing and Implementing Microsoft DevOps Solutions certification helps DevOps engineers and administrators get to grips with practices such as continuous integration and continuous delivery (CI/CD), containerization, and zero downtime deployments using Azure DevOps Services. This new edition is updated with advanced topics such as site reliability engineering (SRE), continuous improvement, and planning your cloud transformation journey. The book begins with the basics of CI/CD and automated deployments, and then moves ahead to show you how to apply configuration management and Infrastructure as Code (IaC) along with managing databases in DevOps scenarios. As you make progress, you'll explore fitting security and compliance with DevOps and find out how to instrument applications and gather metrics to understand application usage and user behavior. This book will also help you implement a container build strategy and manage Azure Kubernetes Services. Lastly, you'll discover quick tips and tricks to confidently apply effective DevOps practices and learn to create your own Azure DevOps organization. By the end of this DevOps book, you'll have gained the knowledge needed to ensure seamless application deployments and business continuity.

Application software --- Development --- Examinations --- Windows Azure

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Master core data architecture design concepts and Azure Data & AI services to gain a cloud data and AI architect's perspective to developing end-to-end solutions Purchase of the print or Kindle book includes a free PDF eBook Key Features Translate and implement conceptual architectures with the right Azure services Inject artificial intelligence into data solutions for advanced analytics Leverage cloud computing and frameworks to drive data science workloads Book Description With data's growing importance in businesses, the need for cloud data and AI architects has never been higher. The Azure Data and AI Architect Handbook is designed to assist any data professional or academic looking to advance their cloud data platform designing skills. This book will help you understand all the individual components of an end-to-end data architecture and how to piece them together into a scalable and robust solution. You'll begin by getting to grips with core data architecture design concepts and Azure Data & AI services, before exploring cloud landing zones and best practices for building up an enterprise-scale data platform from scratch. Next, you'll take a deep dive into various data domains such as data engineering, business intelligence, data science, and data governance. As you advance, you'll cover topics ranging from learning different methods of ingesting data into the cloud to designing the right data warehousing solution, managing large-scale data transformations, extracting valuable insights, and learning how to leverage cloud computing to drive advanced analytical workloads. Finally, you'll discover how to add data governance, compliance, and security to solutions. By the end of this book, you'll have gained the expertise needed to become a well-rounded Azure Data & AI architect. What you will learn Design scalable and cost-effective cloud data platforms on Microsoft Azure Explore architectural design patterns with various use cases Determine the right data stores and data warehouse solutions Discover best practices for data orchestration and transformation Help end users to visualize data using interactive dashboarding Leverage OpenAI and custom ML models for advanced analytics Manage security, compliance, and governance for the data estate Who this book is for This book is for anyone looking to elevate their skill set to the level of an architect. Data engineers, data scientists, business intelligence developers, and database administrators who want to learn how to design end-to-end data solutions and get a bird's-eye view of the entire data platform will find this book useful. Although not required, basic knowledge of databases and data engineering workloads is recommended.

Artificial intelligence --- Database management. --- Cloud computing. --- Data processing. --- Windows Azure.

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Build large-scale, mission-critical hardened applications on the Azure cloud platform. This 2nd edition provides information on the newer features in Azure, such as Linux extensions and supporting Azure Services such as HDInsight and SQL Server on Linux. Updated with new applications Hardening Azure Applications also discusses Scale Sets (VMSS), a major upgrade that enables autoscaling and seamlessly makes machines ready for high availability. The authors take you step by step through the process of evaluating and building applications with the appropriate hardness attributes. After a small introduction to cloud computing, you will learn about various cloud and hardened cloud applications in detail. Next, you will discover service fundamentals such as instrumentation, telemetry, and monitoring followed by key application experiences. Further, you will cover availability and the economics of 9s. Towards the end, you will see how to secure your application and learn about the modernization of software organisations, a new topic in this edition. After reading this book, you will master the techniques and engineering principles that every architect and developer needs to know to harden their Azure/.NET applications to ensure maximum reliability and high availability when deployed at scale. You will: Use techniques and principles to harden Azure/.NET applications Secure your applications on Azure Create a scale set on Azure Work with service fundamentals such as instrumentation, telemetry, and monitoring.

Cloud computing --- Cost effectiveness. --- Microsoft software. --- Microsoft .NET Framework. --- Microsoft and .NET. --- Computer software --- Windows Azure.

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Learn the essential design and deployment skills to utilize Azure VMware Solution to seamlessly move your VMware-based workloads from your datacenter to Azure and to integrate your VMware environment with Azure. This book will teach you how to manage your existing environments with the same VMware products you already know while modernizing your applications with Azure native services.

Microsoft Azure (Computing platform) --- VMware. --- Windows Azure (Computing platform) --- Computing platforms

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Choose the right Azure data service and correct model design for successful implementation of your data model with the help of this hands-on guideKey FeaturesDesign a cost-effective, performant, and scalable database in AzureChoose and implement the most suitable design for a databaseDiscover how your database can scale with growing data volumes, concurrent users, and query complexityBook DescriptionData is at the heart of all applications and forms the foundation of modern data-driven businesses. With the multitude of data-related use cases and the availability of different data services, choosing the right service and implementing the right design becomes paramount to successful implementation. Data Modeling for Azure Data Services starts with an introduction to databases, entity analysis, and normalizing data. The book then shows you how to design a NoSQL database for optimal performance and scalability and covers how to provision and implement Azure SQL DB, Azure Cosmos DB, and Azure Synapse SQL Pool. As you progress through the chapters, you'll learn about data analytics, Azure Data Lake, and Azure SQL Data Warehouse and explore dimensional modeling, data vault modeling, along with designing and implementing a Data Lake using Azure Storage. You'll also learn how to implement ETL with Azure Data Factory. By the end of this book, you'll have a solid understanding of which Azure data services are the best fit for your model and how to implement the best design for your solution.What you will learnModel relational database using normalization, dimensional, or Data Vault modelingProvision and implement Azure SQL DB and Azure Synapse SQL PoolsDiscover how to model a Data Lake and implement it using Azure StorageModel a NoSQL database and provision and implement an Azure Cosmos DBUse Azure Data Factory to implement ETL/ELT processesCreate a star schema model using dimensional modelingWho this book is forThis book is for business intelligence developers and consultants who work on (modern) cloud data warehousing and design and implement databases. Beginner-level knowledge of cloud data management is expected.

Windows Azure. --- Cloud computing. --- Computer architecture. --- Database design. --- COMPUTERS / Database Management / General.