Cloud computing Books
Springer Verlag, Singapore Second International Conference on Sustainable
Book SynopsisThis book gathers high-quality papers presented at the Second International Conference on Sustainable Technologies for Computational Intelligence (ICTSCI 2021) held at Graphic Era University, Dehradun, India, during May 22–23, 2021. It covers emerging topics in computational intelligence and effective strategies for its implementation in engineering applications.Table of ContentsAlleviating the Issues of Recommendation System through Deep Learning Techniques.- Communication Assistant using IoT based Device for People with Vision, Speech and Hearing Disability.- An Optimized Object Detection System For Visually Impaired People.- Sentiment Analysis of Zomato and Swiggy food delivery management system.- Text Similarity Identification based on CNN and CNN-LSTM Model.- Survey Based on Configuration of CubeSats Used for Communication Technology.- Ontology Driven Software Development for better Understanding and Maintenance of Software System.- Application of Genetic Algorithm (GA) in Medical Science: A Review.- Designing a Machine Learning Model to Predict Parkinson’s disease from Voice Recordings.- Prediction Techniques for Maintenance of Marine Bilge Pumps onboard ships.
£179.99
Springer Verlag, Singapore Advances in Data and Information Sciences:
Book SynopsisThis book gathers a collection of high-quality peer-reviewed research papers presented at the 3rd International Conference on Data and Information Sciences (ICDIS 2021), held at Raja Balwant Singh Engineering Technical Campus, Agra, India, on May 14 – 15, 2021. In chapters written by leading researchers, developers, and practitioner from academia and industry, it covers virtually all aspects of computational sciences and information security, including central topics like artificial intelligence, cloud computing, and big data. Highlighting the latest developments and technical solutions, it will show readers from the computer industry how to capitalize on key advances in next-generation computer and communication technology.Table of ContentsITSA-KNN: Feature Selection Model Based on Improved Tree-Seed Algorithm and K-Nearest Neighbor for Network Intrusion Detection.- Cost-Effectiveness of Using Tablets for Digital Literacy Training in Tribal Areas of Rajasthan.- Multi-class weather classification: Comparative analysis of Machine learning algorithms.- Deep Learning Based Chatbot Framework ForMental Health Therapy.- Heart Disease Prediction using Core Machine Learning Techniques – A Comparative Study.- Predicting the presence of newt-amphibian using genetic programming.- Prediction of annual Indian Summer Monsoon Rainfall (ISMR) using Parametric Deep learning model.- Early-Stage Detection of Liver Disease through Machine Learning Algorithms.- Applications of High Dimensional Neural Networks: A Survey.- Breast Cancer Classification With Random Forest Classifier With Feature Decomposition Using Principal Component Analysis.- DDNA: A Modified Concept to DNA Cryptography.- A Comprehensive Study of AI-based Steganalysis Techniques on Image and Text Documents.- Image Tampering Forgery Detection using Convolutional Neural Network with Blockchain.
£999.99
Springer Verlag, Singapore Smart Intelligent Computing and Applications,
Book SynopsisThe proceeding presents best selected papers presented at 5th International Conference on Smart Computing and Informatics (SCI 2021), held at Department of Computer Science and Engineering, Vasvi College of Engineering, Hyderabad, Telangana, India, during 17 – 18 September 2021. It presents advanced and multi-disciplinary research towards the design of smart computing and informatics. The theme is on a broader front focuses on various innovation paradigms in system knowledge, intelligence and sustainability that may be applied to provide realistic solutions to varied problems in society, environment and industries. The scope is also extended towards the deployment of emerging computational and knowledge transfer approaches, optimizing solutions in various disciplines of science, technology and healthcare. The work is published in two volumes.Table of ContentsAn Analytical Study of Covid-19 Dataset using Graph-Based Clustering Algorithms.- Development of Different Word Vectors and Testing using Text Classification Algorithms for Telugu.- Online Malayalam Script Assortment And Pre-Processing For Building Recommender Systems.- Design and synthesis of random number generator using LFSR.- A Flexible Accession on Brain Tumour Detection and Classification using VGG16 model.- Advertisement Click Fraud Detection Using Machine Learning Algorithms.- Artificial Intelligence for on-site detection of invasive Rugose Spiralling Whitefly in Coconut Plantation.- Analysis of different methodologies for Sentiment in Hindi Language.- A dynamic model and algorithm for real time traffic management.- A Selection-Based Framework for Building and Validating Regression Model for Covid-19 Information Management.- Fingerprint Liveliness Detectionto Mitigate Spoofing Attacks Using Generative Networks in Biometric System.- Pulmonary Nodule Detection using Laplacian of Gaussian and Deep Convolutional Neural Network.
£197.99
Springer Verlag, Singapore Advanced Intelligent Technologies for Industry:
Book SynopsisThe book includes new research results of scholars from the Second International Conference on Advanced Intelligent Technologies (ICAIT 2021) subtitled Intelligent Technology and Industry organized by IRNet International Academic Communication Center, held during October 15–17, 2021. The book covers research work from active researchers who are working on collaboration of industry and various intelligent technologies such as intelligent technologies applicable/applied to manufacturing and distribution of industrial products, factory automation, business, etc. The book focuses on theory, design, development, testing, and evaluation of all intelligent technologies applicable/applied to various parts of industry and its infrastructure. The topics included are all computational intelligence techniques applicable/applied to industry, intelligent techniques in data science applicable/applied to business and management, intelligent network systems applicable/applied to industrial production, intelligent technologies applicable to smart agriculture, and intelligent information systems for agriculture.Table of ContentsUtilization of the Open-Source Arduino Platform to Control Based on Logic Et.- Ontology Implementation of OPC UA and Automation ML: A Review.- Airport Cab Scheduling Model Based on Queuing Theory .- Machine Reading Comprehension Model Based on Multi-head Attention Mechanism.- Design of Military Physical Fitness Evaluation System based on Big Data Clustering Algorithm.- ResNet-Based Multiscale U-Net for Human Parsing.- Short-Term Electricity Price Forecast Based on SSA-SVM Model.- Research on Mobile Advertising Click-through Rate Estimation Based on Neural Network.- Research on Macroeconomic Prediction Technology Based on Wavelet Neural Network.- Design Research on Financial Risk Control Model Based on CNN.
£179.99
Springer Verlag, Singapore Proceedings of International Conference on
Book SynopsisThis book includes selected papers presented at International Conference on Computational Intelligence, Data Science,, and Cloud Computing (IEM-ICDC 2021), organized by the Department of Information Technology Institute of Engineering and Management, Kolkata, India, during December 22 – 24, 2021. It covers substantial new findings about AI and robotics, image processing and NLP, cloud computing and big data analytics as well as in cyber-security, blockchain and IoT, and various allied fields. The book serves as a reference resource for researchers and practitioners in academia and industry.Table of ContentsAutoDrone: Shortest Optimized Obstacle-Free Path Planning for Autonomous Drones.- Transfer Learning and Transformer Architecture for Financial Sentiment Analysis.- Feature Extraction and Machine Learning for the Classification of Fashion Materials.- Cardamom Quality Evaluation Employing Electronic Nose.- COVID-DeepNet: Deep Convolutional Neural Network Architecture Designed for Early Prognosis of COVID-19 using Post-Anterior View of Chest X-Rays.- Analytical Study on Feature Selection for Big Data using Optimization Algorithms.- A Machine Learning Approach for Predicting the Death Time and Mortality.- Prediction of Crops Production Using Random Forest Regression.- Drowsy Driving Detection based on Deep Neural Network for Accident Avoidance.- An Intelligent Fire-Extinguishing Robotic System to Combat fire in Coal Mines.
£208.99
Springer Verlag, Singapore Inventive Communication and Computational
Book SynopsisThis book gathers selected papers presented at the Inventive Communication and Computational Technologies Conference (ICICCT 2022), held on May 12–13, 2022, at Gnanamani College of Technology, Tamil Nadu, India. The book covers the topics such as Internet of Things, social networks, mobile communications, big data analytics, bio-inspired computing, and cloud computing. The book is exclusively intended for academics and practitioners working to resolve practical issues in this area.Table of ContentsA Comparitive Study of Employee Attrition Analysis using Machine Learning and Deep Learning Techniques.- Efficient RNS Realization of High Speed Arithmetic Multiplier with Respect to Cryptographic Computation.- An Integrated Terrestrial - Satellite Cellular 5G Network Routing Protocol Using Reinforcement Learning Techniques.- Direct Trust-based GPSR Protocol (DT-GPSR) in VANET.- Combating Challenges in Healthcare using Blockchain.- HIDSC2: Host Based Intrusion Detection System in Cloud Computing.- The Impact of Online Reviews on Download Numbers of Mobile Apps.- Learning System During the Covid-19 in a University.- The Adoption of using the Zoom Application as a Learning Tool to Increase Neuro-Cognitive for Public High School in Jakarta.- Context Aware Voice Recognition System for Car Climate and Infotainment Control.- Study of Identification of Breast Tumor Through DL Technique.- Methods for Assessing Information Security Incidents in the Enterprise and Making Decisions.- Data Analytics for Healthcare Institutions: A Data Warehouse Model Proposal.- The Role of Existing Technology Text to Speech in the Deaf Disabled Communities due to Brain Inflammation.- Performance Analysis of Hybrid Deep Learning Approach for Human Actions Recognition.
£179.99
Springer Verlag, Singapore Big Data and Cloud Computing: Select Proceedings
Book SynopsisThe book presents papers from the 7th International Conference on Big Data and Cloud Computing Challenges (ICBCC 2022). The book includes high-quality, original research on various aspects of big data and cloud computing, offering perspectives from the industrial and research communities on addressing the current challenges in the field. This book discusses key issues and highlights recent advances in a single broad topic applicable to different sub-fields by exploring various multidisciplinary technologies. This book supports the transfer of vital knowledge to next-generation researchers, students, and practitioners in academia and industry.Table of ContentsTable of contents: Track 1: Architecture Sample topics include, - Cloud Infrastructure as a Service -Cloud Platform as a Service -Cloud federation and hybrid cloud infrastructure -Programming models and systems/tools -Green data center -Networking technologies for data center -Cloud system design with FPGA, GPU, and APU -Monitoring, management and maintenance -Economic and business models -Dynamic resource provisioning Track 2: MapReduce Sample topics include, -Performance characterization and optimization -MapReduce on multi-core, GPU -MapReduce on hybrid distributed environments -MapReduce on opportunistic / heterogeneous computing systems -Extension of the MapReduce programming model -Debugging and simulation of MapReduce systems -Data-intensive applications using MapReduce -Optimized storage for MapReduce applications -Fault-tolerance & Self-capabilities Track 3: Security and Privacy -Accountability -Audit in clouds -Authentication and authorization -Cryptographic primitives -Reliability and availability -Trust and credential management -Usability and security -Security and privacy in clouds -Legacy systems migration -Cloud Integrity and Binding Issues Track 4: Services and Applications -Cloud Service Composition -Query and discovery models for cloud services -Trust and Security in cloud services -Change management in cloud services -Organization models of cloud services -Innovative cloud applications and experiences -Business process and workflow management -Service-Oriented Architecture in clouds Track 5: Virtualization -Server, storage, network virtualization -Resource monitoring -Virtual desktop -Resilience, fault tolerance -Modeling and performance evaluation -Security aspects -Enabling disaster recovery, job migration -Energy efficient issues Track 6. HPC on Cloud -Load balancing for HPC clouds -Middleware framework for HPC clouds -Scalable scheduling for HPC clouds -HPC as a Service -Performance Modeling and Management -Programming models for HPC clouds -HPC cloud applications -Optimal cloud deployment for HPC Track 7. Big Data Science and Foundations -Novel Theoretical Models for Big Data -New Computational Models for Big Data -Data and Information Quality for Big Data -New Data Standards Track 8.Big Data Infrastructure -Cloud/Grid/Stream Computing for Big Data -High Performance/Parallel Computing Platforms for Big Data -Autonomic Computing and Cyber-infrastructure, System Architectures, Design and Deployment -Energy efficient Computing for Big Data -Programming Models and Environments for Cluster, Cloud, and Grid Computing to Support Big Data -Software Techniques and Architectures in Cloud/Grid/Stream Computing Big Data Open Platforms -New Programming Models for Big Data beyond Hadoop/MapReduce, STORM -Software Systems to Support Big Data Computing Track 9. Big Data Management -Advanced database and Web Applications -Novel Data Model and Databases for Emerging Hardware -Data Preservation -Data Provenance -Interfaces to Database Systems and Analytics Software Systems -Data Protection, Integrity and Privacy Standards and Policies -Information Integration and Heterogeneous and Multi-structured Data Integration -Data management for Mobile and Pervasive Computing -Data Management in the Social Web -Crowd sourcing -Spatiotemporal and Stream Data Management -Scientific Data Management -Workflow Optimization -Database Management Challenges: Architecture, Storage, User Interfaces Track 10. Big Data Search and Mining -Social Web Search and Mining -Web Search -Algorithms and Systems for Big Data Search -Distributed, and Peer-to-peer Search -Big Data Search Architectures, Scalability and Efficiency -Data Acquisition, Integration, Cleaning, and Best Practices -Visualization Analytics for Big Data -Computational Modeling and Data Integration -Large-scale Recommendation Systems and Social Media Systems -Cloud/Grid/Stream Data Mining- Big Velocity Data -Link and Graph Mining -Semantic-based Data Mining and Data Pre-processing -Mobility and Big Data Track 11. Big Data Security & Privacy -Intrusion Detection for Gigabit Networks -Anomaly and APT Detection in Very Large Scale Systems -High Performance Cryptography -Visualizing Large Scale Security Data -Threat Detection using Big Data Analytics -Privacy Threats of Big Data -Privacy Preserving Big Data Collection/Analytics -HCI Challenges for Big Data Security & Privacy -User Studies for any of the above -Sociological Aspects of Big Data Privacy Track 12. Big Data Applications -Complex Big Data Applications in Science, Engineering, Medicine, Healthcare, Finance -Business, Law, Education -Transportation, Retailing, Telecommunication -Big Data Analytics in Small Business Enterprises (SMEs) -Big Data Analytics in Government, Public Sector and Society in General -Real-life Case Studies of Value Creation through Big Data Analytics -Big Data as a Service -Big Data Industry Standards -Experiences with Big Data Project Deployments Track 13. Recent trends -Semantic Cloud -Mobile Cloud -e-Healthcare Applications in Cloud -Cloud analytics for Internet of Things (IoT) -Smart Grid -Fog Computing -Edge Computing -Deep Learning -CNN
£208.99
Taylor & Francis Ltd Securing Cloud and Mobility A Practitioners Guide
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£54.14
Taylor & Francis Ltd Cloud Computing Technologies and Strategies of the Ubiquitous Data Center
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£56.99
Taylor & Francis Ltd Cloud Security
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£123.50
Taylor & Francis Ltd Security and Privacy Trends in Cloud Computing and Big Data
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£74.09
Taylor & Francis Ltd Machine Learning for Cloud Management
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£54.14
Taylor & Francis Ltd Risk Thinking for CloudBased Application Services
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£42.99
Taylor & Francis Ltd Security in the Private Cloud
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£42.74
Taylor & Francis Ltd Applied Cloud Deep Semantic Recognition
Book SynopsisThis book provides a comprehensive overview of the research on anomaly detection with respect to context and situational awareness that aim to get a better understanding of how context information influences anomaly detection. In each chapter, it identifies advanced anomaly detection and key assumptions, which are used by the model to differentiate between normal and anomalous behavior. When applying a given model to a particular application, the assumptions can be used as guidelines to assess the effectiveness of the model in that domain. Each chapter provides an advanced deep content understanding and anomaly detection algorithm, and then shows how the proposed approach is deviating of the basic techniques. Further, for each chapter, it describes the advantages and disadvantages of the algorithm. The final chapters provide a discussion on the computational complexity of the models and graph computational frameworks such as Google Tensorflow and H2O because it is an important issueTable of Contents1 Large-Scale Video Event Detection Using Deep Neural Networks 2 Leveraging Selectional Preferences for Anomaly Detection in Newswire Events 3 Abnormal Event Recognition in Crowd Environments 4 Cognitive Sensing: Adaptive Anomalies Detection with Deep Networks 5 Language-Guided Visual Recognition 6 Deep Learning for Font Recognition and Retrieval 7 A Distributed Secure Machine-Learning Cloud Architecture for Semantic Analysis 8 A Practical Look at Anomaly Detection Using Autoencoders with H2O and the R Programming Language
£114.00
Cambridge University Press Cloud Computing
Book SynopsisWritten in a tutorial style, this comprehensive guide follows a structured approach explaining cloud techniques, models and platforms. Popular cloud services such as Amazon, Google and Microsoft Azure are explained in the text. The security risks and challenges of cloud computing are discussed in detail with useful examples. Emerging trends including mobile cloud computing and internet of things are discussed in the book for the benefit of the readers. Numerous review questions, multiple choice exercises and case studies facilitate enhanced understanding. This textbook is ideal for undergraduate and graduate students of computer science engineering, and information technology.Table of ContentsFigures; Tables; Preface; Acknowledgements; 1. Introduction; 2. Evolution and enabling technologies; 3. Benefits and challenges; 4. Cloud computing model; 5. Cloud computing services; 6. Security reference model; 7. Resource virtualization; 8. Resource pooling, sharing and provisioning; 9. Scaling in the cloud; 10. Capacity planning; 11. Load balancing; 12. Service-oriented architecture; 13. File system and storage; 14. Database technology; 15. Content delivery network; 16. Security issues; 17. Privacy and compliance issues; 18. Portability and interoperability issues; 19. Cloud management and a programming model case study; 20. Popular cloud services; 21. Mobile cloud computing and internet of things; Appendix I. Hot research topics; Index.
£54.14
ISTE Ltd and John Wiley & Sons Inc Resource Optimization and Security for Cloud
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
£132.00
Duncker & Humblot Strafverfolgung Und Die Cloud: Strafprozessuale
Book Synopsis
£117.90
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG Architecting a Modern Data Warehouse for Large Enterprises: Build Multi-cloud Modern Distributed Data Warehouses with Azure and AWS
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.
£39.99
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG Reverse Engineering with Terraform: An Introduction to Infrastructure Automation, Integration, and Scalability using Terraform
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.
£35.99
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG Google Cloud Platform GCP Professional Cloud Security Engineer Certification Companion
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.
£42.49
Apress Snowflake Recipes
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.
£43.99
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG DevOps Simplified ZeroMaintenance Strategies for AWS EKS
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.
£41.24
Apress AWS EKS Essentials
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.
£43.99
