Microsoft Office 365 Administration Cookbook. Enhance your Office 365 productivity with recipes to manage and optimize its apps and services

Nate Chamberlain

Organizations across the world have switched to Office 365 to boost workplace productivity. However, to maximize investment in Office 365, you need to know how to efficiently administer Office 365 solutions.Microsoft Office 365 Administration Cookbook is packed with recipes to guide you through common and not-so-common administrative tasks throughout Office 365. Whether you’re administering a single app such as SharePoint or organization-wide Security & Compliance across Office 365, this cookbook offers a variety of recipes that you’ll want to have to hand. The book begins by covering essential setup and administration tasks. You’ll learn how to manage permissions for users and user groups along with automating routine admin tasks using PowerShell. You’ll then progress through to managing core Office 365 services such as Exchange Online, OneDrive, SharePoint Online, and Azure Active Directory (AD). This book also features recipes that’ll help you to manage newer services such as Microsoft Search, Power Platform, and Microsoft Teams. In the final chapters, you’ll delve into monitoring, reporting, and securing your Office 365 services.By the end of this book, you’ll have learned about managing individual Office 365 services along with monitoring, securing, and optimizing your entire Office 365 deployment efficiently.

VMware Cloud on AWS Blueprint. Design, automate, and migrate VMware workloads on AWS global infrastructure

Oleg Ulyanov, Michael Schwartzman, Harsha Sanku

If you’re looking to effortlessly transition from on-premises VMware vSphere environments or capital expenditure (CAPEX) to an agile operational expenditure (OPEX) model, trust the VMware Cloud (VMC) on AWS platform for swift re-platforming of legacy applications into cloud-native framework. This comprehensive guide addresses hybrid cloud challenges, offering detailed solutions within the VMware Cloud on AWS ecosystem.Covering the foundational architecture, software-defined data center (SDDC) components of VMware Cloud on AWS, network and security configurations, and AWS service integrations, this book lays the foundation for you to advance to vCenter management, vSAN storage policies, NSX architecture, compute policies, SDDC console management, and the EDRS mechanism for cluster scaling. You’ll also explore integrated services such as VMware HCX for migration, VMware Aria suite, Tanzu Managed Kubernetes, and disaster recovery.Further, the book takes you through VMware Cloud APIs and guides you in managing workloads with VMware Cloud on AWS Outposts. With the help of practical insights, configuration tips, and best practices, you’ll unlock the full potential of VMC on AWS.By the end of this book, you’ll be equipped to successfully architect and manage VMware Cloud on AWS SDDCs, handling day-to-day operations expertly.

OpenStack Administration with Ansible 2. Automate and monitor administrative tasks - Second Edition

Walter Bentley

Most organizations are seeking methods to improve business agility because they have realized just having a cloud is not enough. Being able to improve application deployments, reduce infrastructure downtime, and eliminate daily manual tasks can only be accomplished through some sort of automation.We start with a brief overview of OpenStack and Ansible 2 and highlight some best practices. Each chapter will provide an introduction to handling various Cloud Operator administration tasks such as managing containers within your cloud; setting up/utilizing open source packages for monitoring; creating multiple users/tenants; taking instance snapshots; and customizing your cloud to run multiple active regions. Each chapter will also supply a step-by-step tutorial on how to automate these tasks with Ansible 2.Packed with real-world OpenStack administrative tasks, this book will walk you through working examples and explain how these tasks can be automated using one of the most popular open source automation tools on the market today.

DevOps for Databases. A practical guide to applying DevOps best practices to data-persistent technologies

David Jambor

In today's rapidly evolving world of DevOps, traditional silos are a thing of the past. Database administrators are no longer the only experts; site reliability engineers (SREs) and DevOps engineers are database experts as well. This blurring of the lines has led to increased responsibilities, making members of high-performing DevOps teams responsible for end-to-end ownership. This book helps you master DevOps for databases, making it a must-have resource for achieving success in the ever-changing world of DevOps.You’ll begin by exploring real-world examples of DevOps implementation and its significance in modern data-persistent technologies, before progressing into the various types of database technologies and recognizing their strengths, weaknesses, and commonalities. As you advance, the chapters will teach you about design, implementation, testing, and operations using practical examples, as well as common design patterns, combining them with tooling, technology, and strategies for different types of data-persistent technologies. You’ll also learn how to create complex end-to-end implementation, deployment, and cloud infrastructure strategies defined as code.By the end of this book, you’ll be equipped with the knowledge and tools to design, build, and operate complex systems efficiently.

Applied Unsupervised Learning with Python. Discover hidden patterns and relationships in unstructured data with Python

Benjamin Johnston, Aaron Jones, Christopher Kruger

Unsupervised learning is a useful and practical solution in situations where labeled data is not available.Applied Unsupervised Learning with Python guides you in learning the best practices for using unsupervised learning techniques in tandem with Python libraries and extracting meaningful information from unstructured data. The book begins by explaining how basic clustering works to find similar data points in a set. Once you are well-versed with the k-means algorithm and how it operates, you’ll learn what dimensionality reduction is and where to apply it. As you progress, you’ll learn various neural network techniques and how they can improve your model. While studying the applications of unsupervised learning, you will also understand how to mine topics that are trending on Twitter and Facebook and build a news recommendation engine for users. Finally, you will be able to put your knowledge to work through interesting activities such as performing a Market Basket Analysis and identifying relationships between different products.By the end of this book, you will have the skills you need to confidently build your own models using Python.

Windows Server 2016 Cookbook. Click here to enter text

Jordan Krause

This hands-on Cookbook is stuffed full of practical recipes that will help you handle the essential administrative tasks in Windows Server 2016. You’ll start by familiarizing yourself with the look and feel of Windows Server 2016, and will then learn how to navigate through some daily tasks using the graphical interface. You will see how to compose optimal Group Policies and facilitate task automation with PowerShell 5.0 scripting. We will also take a look at the functions available to provide remote network access to your traveling users, and explore the much anticipated Nano Server and Hyper-V built-in integration support that is brand new in Windows Server 2016.By the end of this book, you will know how to take your Windows Server 2016-powered server and turn it into any common infrastructure role that might be required in your company.

Advanced TypeScript 3 Programming Projects. Build 9 different apps with TypeScript 3 and JavaScript frameworks such as Angular, React, and Vue

Peter O'Hanlon

With the demand for ever more complex websites, the need to write robust, standard-compliant JavaScript has never been greater. TypeScript is modern JavaScript with the support of a first-class type system, which makes it simpler to write complex web systems. With this book, you’ll explore core concepts and learn by building a series of websites and TypeScript apps.You’ll start with an introduction to TypeScript features that are often overlooked in other books, before moving on to creating a simple markdown parser. You’ll then explore React and get up to speed with creating a client-side contacts manager. Next, the book will help you discover the Angular framework and use the MEAN stack to create a photo gallery. Later sections will assist you in creating a GraphQL Angular Todo app and then writing a Socket.IO chatroom. The book will also lead you through developing your final Angular project which is a mapping app. As you progress, you’ll gain insights into React with Docker and microservices. You’ll even focus on how to build an image classification program with machine learning using TensorFlow. Finally, you’ll learn to combine TypeScript and C# to create an ASP.NET Core-based music library app.By the end of this book, you’ll be able to confidently use TypeScript 3.0 and different JavaScript frameworks to build high-quality apps.

Practical Guide to Applied Conformal Prediction in Python. Learn and apply the best uncertainty frameworks to your industry applications

Valery Manokhin, Agus Sudjianto

In the rapidly evolving landscape of machine learning, the ability to accurately quantify uncertainty is pivotal. Practical Guide to Applied Conformal Prediction in Python addresses this need by offering an in-depth exploration of Conformal Prediction, a cutting-edge framework set to revolutionize uncertainty management in various ML applications.Embark on a comprehensive journey through Conformal Prediction, exploring its fundamentals and practical applications in binary classification, regression, time series forecasting, imbalanced data, computer vision, and NLP. Each chapter delves into specific aspects, offering hands-on insights and best practices for enhancing prediction reliability. The book concludes with a focus on multi-class classification nuances, providing expert-level proficiency to seamlessly integrate Conformal Prediction into diverse industries. Practical examples in Python using real-world datasets reinforce intuitive explanations, ensuring you acquire a robust understanding of this modern framework for uncertainty quantification.This guide is a beacon for mastering Conformal Prediction in Python, providing a blend of theory and practical application. It serves as a comprehensive toolkit to enhance machine learning skills, catering to professionals from data scientists to ML engineers.