Cloud computing Books

Book SynopsisThis book includes a study of trustworthiness, percentile response time, service availability, and authentication in the networks between users and cloud service providers, and at service stations or sites that may be owned by different service providers. The first part of the book contains an analysis of percentile response time, which is one of the most important SLA (service level agreements) metrics. Effective and accurate numerical solutions for the calculation of the percentile response time in single-class and multi-class queueing networks are obtained. Then, the numerical solution is incorporated in a resource allocation problem. Specifically, the authors present an approach for the resource optimization that minimizes the total cost of computer resources required while preserving a given percentile of the response time. In the second part, the approach is extended to consider trustworthiness, service availability, and the percentile of response time in Web services. These QoS metrics are clearly defined and their quantitative analysis provided. The authors then take into account these QoS metrics in a trust-based resource allocation problem in which a set of cloud computing resources is used by a service provider to host a typical Web services application for single-class customer services and multipleclass customer services respectively. Finally, in the third part of the book a thorough performance evaluation of two notable public key cryptography-based authentication techniques; Public-Key Cross Realm Authentication in Kerberos (PKCROSS) and Public Key Utilizing Tickets for Application Servers (PKTAPP, a.k.a. KX.509/KCA); is given, in terms of computational and communication times. The authors then demonstrate their performance difference using queuing networks. PKTAPP has been proposed to address the scalability issue of PKCROSS. However, their in-depth analysis of these two techniques shows that PKTAPP does not perform better than PKCROSS in a large-scale system. Thus, they propose a new public key cryptography-based group authentication technique. The performance analysis demonstrates that the new technique can scale better than PKCORSS and PKTAPP.Table of ContentsPreface ix Chapter 1. Introduction 1 Chapter 2. Current Approaches for Resource Optimization and Security 13 Chapter 3. Single Class Customers 27 Chapter 4. Multiple-Class Customers 69 Chapter 5. A Trustworthy Service Model 95 Chapter 6. Performance Analysis of Public-Key Cryptography-Based Group Authentication 141 Chapter 7. Summary and Future Work 173 Bibliography 181 Index 193

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Book SynopsisDesign and architect new generation cloud-based data warehouses using Azure and AWS. This book provides an in-depth understanding of how to build modern cloud-native data warehouses, as well as their history and evolution. The book starts by covering foundational data warehouse concepts, and introduces modern features such as distributed processing, big data storage, data streaming, and processing data on the cloud. You will gain an understanding of the synergy, relevance, and usage data warehousing standard practices in the modern world of distributed data processing. The authors walk you through the essential concepts of Data Mesh, Data Lake, Lakehouse, and Delta Lake. And they demonstrate the services and offerings available on Azure and AWS that deal with data orchestration, data democratization, data governance, data security, and business intelligence. After completing this book, you will be ready to design and architect enterprise-grade, cloud-based modern data warehouses using industry best practices and guidelines. What You Will Learn Understand the core concepts underlying modern data warehouses Design and build cloud-native data warehouses Gain a practical approach to architecting and building data warehouses on Azure and AWS Implement modern data warehousing components such as Data Mesh, Data Lake, Delta Lake, and Lakehouse Process data through pandas and evaluate your model’s performance using metrics such as F1-score, precision, and recall Apply deep learning to supervised, semi-supervised, and unsupervised anomaly detection tasks for tabular datasets and time series applications Who This Book Is For Experienced developers, cloud architects, and technology enthusiasts looking to build cloud-based modern data warehouses using Azure and AWSTable of ContentsChapter 1: Introduction.- Chapter 2: Modern Data Warehouses.- Chapter 3: Data Lake, Lake House, and Delta Lake.- Chapter 4: Data Mesh.- Chapter 5: Data Orchestration Techniques.- Chapter 6: Data Democratization, Governance, and Security.- Chapter 7: Business Intelligence.

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Book SynopsisThis book is a comprehensive guide for employing Terraform in infrastructure as code automation, and its application to infrastructure operations. Reverse Engineering with Terraform begins with an introduction to Terraform’s core functionalities, including state files, configuration files, and providers, followed by a deep dive into the tool. You’ll then learn how to pinpoint problems with Terraform automation and how reverse engineering can help you resolve them. Drilling down, authors Sumit Bhatia and Chetan Gabhane walk you through the various steps in reverse engineering with an eye towards more effective Terraform integration with preexisting and legacy IT infrastructure. Using a real-world reverse engineering example, they demonstrate how to import a preexisting resource into your infrastructure, which can help you develop an automatable and scalable method for Terrraform adoption. You’ll also learn how to create reusable, shareable components to streamline infrastructure code and foster collaboration within teams, and advanced techniques for using Terraform to optimize infrastructure provisioning, configuration, and management. Filled with real-world case studies, tips and tricks, and best practices, this book will leave you with a thorough understanding of the infrastructure as code paradigm, and how to leverage Terraform automation with legacy as well as modern IT infrastructure. What You Will Learn Understand Terraform and its infrastructure automation capabilities Explore how Terraform can be used with other platforms like AWS, Azure and VMware Master the basic concepts of reverse engineering for legacy infrastructure entities Enable Terraform in legacy IT environments through reverse engineering Who This Book Is For IT architects, admins, technical managers, and infrastructure solution experts. Minimal knowledge of Python programming is the only prerequisite.Table of Contents1: Terraform Infrastructure as Code.- 2: Deep Dive into Terraform.- 3: Reverse Engineering Basics.- 4: Terraform and Reverse Engineering.- 5: Debugging for import issues.- 6: Lifecycle Management.- 7: Other importing options with Terraform.

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Book SynopsisWritten in a simple and developer-focused style, this book gives you the tools and knowledge you need to ace the GCP Professional Cloud Security Engineer certification exam. The approach is two-fold: introducing and implementing all GCP cloud security concepts and controls based on the certification exam objectives, and demonstrating how these concepts can be applied to real-world scenarios. Your study begins with cloud identities in GCP and different identity types (user accounts, service accounts, groups, and domains) and how separation of duties is implemented with access controls and Identity and Access Management (IAM). Emphasis is placed on the unique GCP approach to managing resources, with its clear distinction between resource ownership and resource billing. Following the defense in depth principle, the book shifts focus to network security and introduces different types of constructs that enable micro-segmentation, as they are implemented in a software-defined network. A chapter devoted to data protection is included. You will learn how to leverage the Data Loss Prevention (DLP) application programming interface (API) to prevent access to your workloads' sensitive data from unauthorized use. Examples on how to use the DLP API are provided using the Go language, which is becoming widely adopted in the developer community due to its simplicity, and high-performance networking and multi-processing capabilities. Encryption at rest, in use, and in transit is covered with an overview on how GCP implements confidential computing. The book concludes with an examination of the GCP services you need to know to monitor, audit, and ensure compliance with the laws and regulations where your workloads and infrastructure operate. By the end of the book, you will have acquired the knowledge and confidence to pass the GCP Professional Cloud Security Engineer certification exam and to successfully design, architect, and engineer security solutions with the Google Cloud Platform. Bonus Material: IAM deny policiesWhat You Will LearnUnderstand the five security principles and how to use them to drive the development of modern security architectures in Google CloudSecure identities with Cloud Identity and Identity & Access Management (IAM)Secure the network with segmentation and private connectivityProtect sensitive data with the Data Loss Prevention (DLP) API and encryptionMonitor, log, audit, and troubleshoot security incidents with the Google Cloud Operations SuiteEnsure compliance and address regulatory concernsWho This Book Is ForSoftware engineers specializing in DevOps, SecOps, and DataOps, who possess expertise in the Software Development Life Cycle (SDLC) methodologies within Agile teams. It also targets software architects with proficiency in various domains such as security, network, solution, data, infrastructure, cloud, and enterprise architecture.

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Book SynopsisChapter 1: Introduction to Snowflake.- Chapter 2: Bringing Your Data into Snowflake.- Chapter 3: Handling Atypical Data.- Chapter 4: Data Security and Privacy.- Chapter 5: Handling Near and Real Time Data.- Chapter 6: Programmable Data Pipelines.- Chapter 7: Data Reusability and Monetization.- Chapter 8: Data Recovery and Protection.- Chapter 9: Applications Integration.- Chapter 10: Machine Learning.

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Book SynopsisGain the knowledge and practical skills needed to deploy a fully functional, secure, and scalable application in AWS EKS. This book is a hands-on guide designed to help you navigate and manage infrastructure in the AWS EKS environment. The book starts by reviewing the concept of DevOps flexibility, emphasizing adaptability to manage changes effectively. It covers foundational elements like IAM basics, user management, and the use of Terraform for infrastructure as code, highlighting the importance of version stability and unique CIDR blocks. Moving forward, you'll explore Kubernetes, and its initial set-up steps, such as configuration management, access control, and storage. You'll also see how to bridge Kubernetes with AWS resources, touching upon service accounts, identity federation, and policy assignment.In the final chapters, the book guides you through the complete setup of a fully working application using Terraform. The book culminates with a step-by-step walkthrough of deploying a complete application environment where you'll generate and distribute access credentials, configure persistent storage, and manage RBAC for users, all using Terraform. Zero-Maintenance Strategies for AWS EKS will provide you with a solid foundation and a toolkit of proven strategies for managing cloud infrastructure. What You Will LearnUnderstand the concept of DevOps flexibility and its practical applicationsAcquire foundational knowledge in IAM basics anduser management. Manage external access to your applications while consolidating load balancing through a single, entry point. Securely configure DNS and SSL, ensuring your application is both accessible and protected. Who This Book Is ForDevOps professionals, IT managers, and software developers who are looking to adopt or improve their DevOps practices, and students and educators in IT-related fields.

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Book SynopsisChapter 1:  Introduction to the Amazon Elastic Kubernetes Service.- Chapter 2: The EKS Architecture and Cluster Access Control.- Chapter 3: EKS Implementations.- Chapter 4: Private Endpoint Access Cluster.- Chapter 5: Hybrid Endpoint Access Cluster.- Chapter 6: Cluster Nodes.- Chapter 7: EKS IP Address Management.- Chapter 8: EKS Addons.- Chapter 9: Identity And Access Management.- Chapter 10: The New Cluster Access Management.- Chapter 11: Kubernetes.- Chapter 12:  Running apps on K8s.- Chapter 13: The Pod Object.- Chapter 14: The Service Object.- Chapter 15: Pod Service Accounts.- Chapter 16: Pod persistent.- Chapter 17: Pod Scaling.- Chapter 18: Pod Monitoring.- Chapter 19: Cluster Scaling.- Chapter 20: App Mesh.

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