Learning OpenStack Networking. Build a solid foundation in virtual networking technologies for OpenStack-based clouds - Third Edition

James Denton

OpenStack Networking is a pluggable, scalable, and API-driven system to manage physical and virtual networking resources in an OpenStack-based cloud. Like other core OpenStack components, OpenStack Networking can be used by administrators and users to increase the value and maximize the use of existing datacenter resources. This third edition of Learning OpenStack Networking walks you through the installation of OpenStack and provides you with a foundation that can be used to build a scalable and production-ready OpenStack cloud.In the initial chapters, you will review the physical network requirements and architectures necessary for an OpenStack environment that provide core cloud functionality. Then, you’ll move through the installation of the new release of OpenStack using packages from the Ubuntu repository. An overview of Neutron networking foundational concepts, including networks, subnets, and ports will segue into advanced topics such as security groups, distributed virtual routers, virtual load balancers, and VLAN tagging within instances.By the end of this book, you will have built a network infrastructure for your cloud using OpenStack Neutron.

Learning Salesforce Einstein. Add artificial intelligence capabilities to your business solutions with Heroku, PredictiveIO, and Force

Mohit Shrivatsava

Dreamforce 16 brought forth the latest addition to the Salesforce platform: an AI tool named Einstein. Einstein promises to provide users of all Salesforce applications with a powerful platform to help them gain deep insights into the data they work on. This book will introduce you to Einstein and help you integrate it into your respective business applications based on the Salesforce platform. We start off with an introduction to AI, then move on to look at how AI can make your CRM and apps smarter. Next, we discuss various out-of-the-box components added to sales, service, marketing, and community clouds from Salesforce to add Artificial Intelligence capabilities. Further on, we teach you how to use Heroku, PredictionIO, and the Force platform, along with Einstein, to build smarter apps. The core chapters focus on developer content and introduce PredictionIO and Salesforce Einstein Vision Services. We explore Einstein Predictive Vision Services, along with analytics cloud, the Einstein Data Discovery product, and IOT core concepts. Throughout the book, we also focus on how Einstein can be integrated into CRM and various clouds such as sales, services, marketing, and communities. By the end of the book, you will be able to embrace and leverage the power of Einstein, incorporating its functions to gain more knowledge. Salesforce developers will be introduced to the world of AI, while data scientists will gain insights into Salesforce’s various cloud offerings and how they can use Einstein’s capabilities and enhance applications.

Learning Veeam Backup & Replication for VMware vSphere. Learn how to protect your data in your VMware vSphere infrastructure with Veeam Backup & Replication

Christian Mohn

Learning VMware App Volumes. Deliver applications to virtual desktop environments in seconds and at scale with the click of a button

Peter von Oven

App Volumes provides a virtualized, real-time application delivery engine for virtual desktop infrastructure and is designed to enable VDI deployments to ensure greater flexibility, agility, and cost reduction.This book starts with an in-depth overview of the architecture and components used to design an optimized solution. We then show you how to install and configure App Volumes for different use cases such as VMware View integration, using VMware ThinApp, Citrix XenApp, and more. Throughout the chapters, we provide hints, tips, and tricks as well as best practices. By the end of the book, you will have built a working App Volumes environment and acquired the skills to build and run a production environment.

Learning VMware NSX. Next-generation network administration skills revealed - Second Edition

Ranjit Singh Thakurratan

VMware NSX is a platform for the software-defined data center. It allows complex networking topologies to be deployed programmatically in seconds. SDNs allow ease of deployment, management, and automation in deploying and maintaining new networks while reducing and in some cases completely eliminating the need to deploy traditional networks. The book allows you a thorough understanding of implementing Software defined networks using VMware’s NSX. You will come across the best practices for installing and configuring NSX to setup your environment. Then you will get a brief overview of the NSX Core Components NSX’s basic architecture. Once you are familiar with everything, you will get to know how to deploy various NSX features. Furthermore, you will understand how to manage and monitor NSX and its associated services and features. In addition to this, you will also explore the best practices for NSX deployments. By the end of the book, you will be able to deploy Vmware NSX in your own environment with ease. This book can come handy if you are preparing for VMware NSX certification.

Learning VMware vCloud Air

Yohan Wadia

Limitless Analytics with Azure Synapse. An end-to-end analytics service for data processing, management, and ingestion for BI and ML

Prashant Kumar Mishra, Mukesh Kumar

Azure Synapse Analytics, which Microsoft describes as the next evolution of Azure SQL Data Warehouse, is a limitless analytics service that brings enterprise data warehousing and big data analytics together. With this book, you'll learn how to discover insights from your data effectively using this platform.The book starts with an overview of Azure Synapse Analytics, its architecture, and how it can be used to improve business intelligence and machine learning capabilities. Next, you'll go on to choose and set up the correct environment for your business problem. You'll also learn a variety of ways to ingest data from various sources and orchestrate the data using transformation techniques offered by Azure Synapse. Later, you'll explore how to handle both relational and non-relational data using the SQL language. As you progress, you'll perform real-time streaming and execute data analysis operations on your data using various languages, before going on to apply ML techniques to derive accurate and granular insights from data. Finally, you'll discover how to protect sensitive data in real time by using security and privacy features.By the end of this Azure book, you'll be able to build end-to-end analytics solutions while focusing on data prep, data management, data warehousing, and AI tasks.

LLM Engineer's Handbook. Master the art of engineering large language models from concept to production

Paul Iusztin, Maxime Labonne, Julien Chaumond, Hamza Tahir, ...

Artificial intelligence has undergone rapid advancements, and Large Language Models (LLMs) are at the forefront of this revolution. This LLM book offers insights into designing, training, and deploying LLMs in real-world scenarios by leveraging MLOps best practices. The guide walks you through building an LLM-powered twin that’s cost-effective, scalable, and modular. It moves beyond isolated Jupyter notebooks, focusing on how to build production-grade end-to-end LLM systems.Throughout this book, you will learn data engineering, supervised fine-tuning, and deployment. The hands-on approach to building the LLM Twin use case will help you implement MLOps components in your own projects. You will also explore cutting-edge advancements in the field, including inference optimization, preference alignment, and real-time data processing, making this a vital resource for those looking to apply LLMs in their projects.By the end of this book, you will be proficient in deploying LLMs that solve practical problems while maintaining low-latency and high-availability inference capabilities. Whether you are new to artificial intelligence or an experienced practitioner, this book delivers guidance and practical techniques that will deepen your understanding of LLMs and sharpen your ability to implement them effectively.

Low-Code Application Development with Appian. The practitioner's guide to high-speed business automation at enterprise scale using Appian

Stefan Helzle

This book is an exhaustive overview of how the Appian Low-Code BPM Suite enables tech-savvy professionals to rapidly automate business processes across their organization, integrating people, software bots, and data. This is crucial as 80% of all software development is expected to be carried out in low code by 2024.This practical guide helps you master business application development with Appian as a beginner low-code developer. You'll learn to automate business processes using Appian low-code, records, processes, and expressions quickly and on an enterprise scale. In a fictional development project, guided by step-by-step explanations of the concepts and practical examples, this book will empower you to transform complex business processes into software.At first, you’ll learn the power of no-code with Appian Quick Apps to solve some of your most crucial business challenges. You’ll then get to grips with the building blocks of an Appian, starting with no-code and advancing to low-code, eventually transforming complex business requirements into a working enterprise-ready application.By the end of this book, you'll be able to deploy Appian Quick Apps in minutes and successfully transform a complex business process into low-code process models, data, and UIs to deploy full-featured, enterprise-ready, process-driven, mobile-enabled apps.

Machine Learning Security with Azure. Best practices for assessing, securing, and monitoring Azure Machine Learning workloads

Georgia Kalyva, George Kavvalakis

With AI and machine learning (ML) models gaining popularity and integrating into more and more applications, it is more important than ever to ensure that models perform accurately and are not vulnerable to cyberattacks. However, attacks can target your data or environment as well. This book will help you identify security risks and apply the best practices to protect your assets on multiple levels, from data and models to applications and infrastructure.This book begins by introducing what some common ML attacks are, how to identify your risks, and the industry standards and responsible AI principles you need to follow to gain an understanding of what you need to protect. Next, you will learn about the best practices to secure your assets. Starting with data protection and governance and then moving on to protect your infrastructure, you will gain insights into managing and securing your Azure ML workspace. This book introduces DevOps practices to automate your tasks securely and explains how to recover from ML attacks. Finally, you will learn how to set a security benchmark for your scenario and best practices to maintain and monitor your security posture.By the end of this book, you’ll be able to implement best practices to assess and secure your ML assets throughout the Azure Machine Learning life cycle.

Machine Learning with Amazon SageMaker Cookbook. 80 proven recipes for data scientists and developers to perform machine learning experiments and deployments

Joshua Arvin Lat

Amazon SageMaker is a fully managed machine learning (ML) service that helps data scientists and ML practitioners manage ML experiments. In this book, you'll use the different capabilities and features of Amazon SageMaker to solve relevant data science and ML problems.This step-by-step guide features 80 proven recipes designed to give you the hands-on machine learning experience needed to contribute to real-world experiments and projects. You'll cover the algorithms and techniques that are commonly used when training and deploying NLP, time series forecasting, and computer vision models to solve ML problems. You'll explore various solutions for working with deep learning libraries and frameworks such as TensorFlow, PyTorch, and Hugging Face Transformers in Amazon SageMaker. You'll also learn how to use SageMaker Clarify, SageMaker Model Monitor, SageMaker Debugger, and SageMaker Experiments to debug, manage, and monitor multiple ML experiments and deployments. Moreover, you'll have a better understanding of how SageMaker Feature Store, Autopilot, and Pipelines can meet the specific needs of data science teams.By the end of this book, you'll be able to combine the different solutions you've learned as building blocks to solve real-world ML problems.

Managing Microsoft Hybrid Clouds. Benefit from hybrid cloud scenarios through this detailed guide to Microsoft Azure Infrastructure Services (IaaS)

Marcel van den Berg

Managing Virtual Infrastructure with Veeam ONE. Discover ways to manage your virtual infrastructure with Veeam ONE in a development environment

Kevin Sapp

Mastering Amazon EC2. Unravel the complexities of EC2 to build robust and resilient applications

Badri Kesavan

This comprehensive guide demystifies the complex landscape of Amazon EC2, from fundamentals to advanced concepts. You’ll begin by understanding EC2 core components, creating and managing AMIs, selecting the right instance type and size, establishing networking and connectivity, and implementing security best practices. Next, you’ll start building resilient apps on EC2, load balancing, auto scaling, storage options, performance optimization, monitoring, logging, and auditing. You'll also explore advanced concepts like containers, serverless, hybrid/multi-cloud architectures, high performance computing, big data, and disaster recovery strategies. By the end, you'll be equipped with the knowledge and confidence to harness the full potential of Amazon EC2.

Mastering Ansible. Master the ins and outs of advanced operations with Ansible - Second Edition

Jesse Keating

This book provides you with the knowledge you need to understand how Ansible 2.1 works at a fundamental level and leverage its advanced capabilities. You'll learn how to encrypt Ansible content at rest and decrypt data at runtime. You will master the advanced features and capabilities required to tackle the complex automation challenges of today and beyond. You will gain detailed knowledge of Ansible workflows, explore use cases for advanced features, craft well thought out orchestrations, troubleshoot unexpected behaviour, and extend Ansible through customizations. Finally, you will discover the methods used to examine and debug Ansible operations, helping you to understand and resolve issues.By the end of the book, the readers will be able to unlock the true power of the Ansible automation engine and will tackle complex real world actions with ease.

Mastering ArcGIS Enterprise Administration. Install, configure, and manage ArcGIS Enterprise to publish, optimize, and secure GIS services

Chad Cooper

ArcGIS Enterprise, the next evolution of the ArcGIS Server product line, is a full-featured mapping and analytics platform. It includes a powerful GIS web services server and a dedicated Web GIS infrastructure for organizing and sharing your work. You will learn how to first install ArcGIS Enterprise to then plan, design, and finally publish and consume GIS services. You will install and configure an Enterprise geodatabase and learn how to administer ArcGIS Server, Portal, and Data Store through user interfaces, the REST API, and Python scripts.This book starts off by explaining how ArcGIS Enterprise 10.5.1 is different from earlier versions of ArcGIS Server and covers the installation of all the components required for ArcGIS Enterprise. We then move on to geodatabase administration and content publication, where you will learn how to use ArcGIS Server Manager to view the server logs, stop and start services, publish services, define users and roles for security, and perform other administrative tasks. You will also learn how to apply security mechanisms on ArcGIS Enterprise and safely expose services to the public in a secure manner. Finally, you’ll use the RESTful administrator API to automate server management tasks using the Python scripting language. You’ll learn all the best practices and troubleshooting methods to streamline the management of all the interconnected parts of ArcGIS Enterprise.