Julian Soh – författare

Written for IT and business professionals, this book provides the technical and business insight needed to plan, deploy and manage the services provided by the Microsoft Azure cloud. Find out how to integrate the infrastructure-as-a-service (IaaS) and platform-as-a-service (PaaS) models with your existing business infrastructure while maximizing availability, ensuring continuity and safety of your data, and keeping costs to a minimum.

The book starts with an introduction to Microsoft Azure and how it differs from Office 365—Microsoft’s ‘other’ cloud. You''ll also get a useful overview of the services available. Part II then takes you through setting up your Azure account, and gets you up-and-running on some of the core Azure services, including creating web sites and virtual machines, and choosing between fully cloud-based and hybrid storage solutions, depending on your needs.

Part III now takes an in-depth look at how to integrate Azure with your existing infrastructure. The authors, Anthony Puca, Mike Manning, Brent Rush, Marshall Copeland and Julian Soh, bring their depth of experience in cloud technology and customer support to guide you through the whole process, through each layer of your infrastructure from networking to operations. High availability and disaster recovery are the topics on everyone’s minds when considering a move to the cloud, and this book provides key

insights and step-by-step guidance to help you set up and manage your resources correctly to optimize for these scenarios. You’ll also get expert advice on migrating your existing VMs to Azure using InMage, mail-in and the best 3rd party tools available, helping you ensure continuity of service with minimum disruption to the business.

In the book’s final chapters, you’ll find cutting edge examples of cloud technology in action, from machine learning to business intelligence, for a taste of some exciting ways your business could benefit from your new Microsoft Azure deployment.

Gain the technical and business insight needed to plan, deploy, and manage the services provided by the Microsoft Azure cloud. This second edition focuses on improving operational decision tipping points for the professionals leading DevOps and security teams. This will allow you to make an informed decision concerning the workloads appropriate for your growing business in the Azure public cloud.  Microsoft Azure starts with an introduction to Azure along with an overview of its architecture services such as IaaS and PaaS. You’ll also take a look into Azure’s data, artificial intelligence, and machine learning services. Moving on, you will cover the planning for and adoption of Azure where you will go through budgeting, cloud economics, and designing a hybrid data center. Along the way, you will work with web apps, network PaaS, virtual machines, and much more. The final section of the book starts with Azure data services and big data with anin-depth discussion of Azure SQL Database, CosmosDB, Azure Data Lakes, and MySQL. You will further see how to migrate on-premises databases to Azure and use data engineering. Next, you will discover the various Azure services for application developers, including Azure DevOps and ASP.NET web apps. Finally, you will go through the machine learning and AI tools in Azure, including Azure Cognitive Services.What You Will LearnApply design guidance and best practices using Microsoft Azure to achieve business growthCreate and manage virtual machinesWork with AI frameworks to process and analyze data to support business decisions and increase revenue Deploy, publish, and monitor a web appWho This Book Is For Azure architects and business professionals looking for Azure deployment and implementation advice.

Gain the technical and business insight needed to plan, deploy, and manage the services provided by the Microsoft Azure cloud. This second edition focuses on improving operational decision tipping points for the professionals leading DevOps and security teams. This will allow you to make an informed decision concerning the workloads appropriate for your growing business in the Azure public cloud.  

Microsoft Azure starts with an introduction to Azure along with an overview of its architecture services such as IaaS and PaaS. You’ll also take a look into Azure’s data, artificial intelligence, and machine learning services. Moving on, you will cover the planning for and adoption of Azure where you will go through budgeting, cloud economics, and designing a hybrid data center. Along the way, you will work with web apps, network PaaS, virtual machines, and much more. 

The final section of the book starts with Azure data services and big data with anin-depth discussion of Azure SQL Database, CosmosDB, Azure Data Lakes, and MySQL. You will further see how to migrate on-premises databases to Azure and use data engineering. Next, you will discover the various Azure services for application developers, including Azure DevOps and ASP.NET web apps. Finally, you will go through the machine learning and AI tools in Azure, including Azure Cognitive Services.

What You Will Learn

Apply design guidance and best practices using Microsoft Azure to achieve business growth Create and manage virtual machines Work with AI frameworks to process and analyze data to support business decisions and increase revenue Deploy, publish, and monitor a web app

Who This Book Is For 

Azure architects and business professionals looking for Azure deployment and implementation advice.

 

Understand and learn the skills needed to use modern tools in Microsoft Azure. This book discusses how to practically apply these tools in the industry, and help drive the transformation of organizations into a knowledge and data-driven entity. It provides an end-to-end understanding of data science life cycle and the techniques to efficiently productionize workloads. The book starts with an introduction to data science and discusses the statistical techniques data scientists should know. You''ll then move on to machine learning in Azure where you will review the basics of data preparation and engineering, along with Azure ML service and automated machine learning. You''ll also explore Azure Databricks and learn how to deploy, create and manage the same. In the final chapters you''ll go through machine learning operations in Azure followed by the practical implementation of artificial intelligence through machine learning. Data Science Solutions on Azure will reveal how the different Azure services work together using real life scenarios and how-to-build solutions in a single comprehensive cloud ecosystem. What You''ll LearnUnderstand big data analytics with Spark in Azure Databricks Integrate with Azure services like Azure Machine Learning and Azure SynapsDeploy, publish and monitor your data science workloads with MLOps Review data abstraction, model management and versioning with GitHubWho This Book Is ForData Scientists looking to deploy end-to-end solutions on Azure with latest tools and techniques. 

This revamped and updated book focuses on the latest in AI technology—Generative AI. It builds on the first edition by moving away from traditional data science into the area of applied AI using the latest breakthroughs in Generative AI.Based on real-world projects, this edition takes a deep look into new concepts and approaches such as Prompt Engineering, testing and grounding of Large Language Models, fine tuning, and implementing new solution architectures such as Retrieval Augmented Generation (RAG). You will learn about new embedded AI technologies in Search, such as Semantic and Vector Search.Written with a view on how to implement Generative AI in software, this book contains examples and sample code.In addition to traditional Data Science experimentation in Azure Machine Learning (AML) that was covered in the first edition, the authors cover new tools such as Azure AI Studio, specifically for testing and experimentation with Generative AI models. What's New in this BookProvides new concepts, tools, and technologies such as Large and Small Language Models, Semantic Kernel, and Automatic Function CallingTakes a deeper dive into using Azure AI Studio for RAG and Prompt Engineering designIncludes new and updated case studies  for Azure OpenAITeaches about Copilots, plugins, and agents What You'll LearnGet up to date on the important technical aspects of Large Language Models, based on Azure OpenAI as the reference platformKnow about the different types of models: GPT3.5 Turbo, GPT4, GPT4o, Codex, DALL-E, and Small Language Models such as Phi-3Develop new skills such as Prompt Engineering and fine tuning of Large/Small Language ModelsUnderstand and implement new architectures such as RAG and Automatic Function CallingUnderstand approaches for implementing Generative AI using LangChain and Semantic KernelSee how real-world projects help you identify great candidates for Applied AI projects, including Large/Small Language Models Who This Book Is ForSoftware engineers and architects looking to deploy end-to-end Generative AI solutions on Azure with the latest tools and techniques.

This revamped and updated book focuses on the latest in AI technology—Generative AI. It builds on the first edition by moving away from traditional data science into the area of applied AI using the latest breakthroughs in Generative AI.

Based on real-world projects, this edition takes a deep look into new concepts and approaches such as Prompt Engineering, testing and grounding of Large Language Models, fine tuning, and implementing new solution architectures such as Retrieval Augmented Generation (RAG). You will learn about new embedded AI technologies in Search, such as Semantic and Vector Search.

Written with a view on how to implement Generative AI in software, this book contains examples and sample code.

In addition to traditional Data Science experimentation in Azure Machine Learning (AML) that was covered in the first edition, the authors cover new tools such as Azure AI Studio, specifically for testing and experimentation with Generative AI models.

 

What''s New in this Book

Provides new concepts, tools, and technologies such as Large and Small Language Models, Semantic Kernel, and Automatic Function CallingTakes a deeper dive into using Azure AI Studio for RAG and Prompt Engineering designIncludes new and updated case studies  for Azure OpenAITeaches about Copilots, plugins, and agents

 

What You''ll Learn

Get up to date on the important technical aspects of Large Language Models, based on Azure OpenAI as the reference platformKnow about the different types of models: GPT3.5 Turbo, GPT4, GPT4o, Codex, DALL-E, and Small Language Models such as Phi-3Develop new skills such as Prompt Engineering and fine tuning of Large/Small Language ModelsUnderstand and implement new architectures such as RAG and Automatic Function CallingUnderstand approaches for implementing Generative AI using LangChain and Semantic KernelSee how real-world projects help you identify great candidates for Applied AI projects, including Large/Small Language Models

 

Who This Book Is For

Software engineers and architects looking to deploy end-to-end Generative AI solutions on Azure with the latest tools and techniques.