The Self Taught Cloud Computing Engineer

Transform into a cloud-savvy professional by mastering cloud technologies through hands-on projects and expert guidance, paving the way for a thriving cloud computing career Key Features Learn all about cloud computing at your own pace with this easy-to-follow guide Develop a well-rounded skill set, encompassing fundamentals, data, machine learning, and security Work on real-world industrial projects and business use cases, and chart a path for your personal cloud career advancement Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionThe Self-Taught Cloud Computing Engineer is a comprehensive guide to mastering cloud computing concepts by building a broad and deep cloud knowledge base, developing hands-on cloud skills, and achieving professional cloud certifications. Even if you’re a beginner with a basic understanding of computer hardware and software, this book serves as the means to transition into a cloud computing career. Starting with the Amazon cloud, you’ll explore the fundamental AWS cloud services, then progress to advanced AWS cloud services in the domains of data, machine learning, and security. Next, you’ll build proficiency in Microsoft Azure Cloud and Google Cloud Platform (GCP) by examining the common attributes of the three clouds while distinguishing their unique features. You’ll further enhance your skills through practical experience on these platforms with real-life cloud project implementations. Finally, you’ll find expert guidance on cloud certifications and career development. By the end of this cloud computing book, you’ll have become a cloud-savvy professional well-versed in AWS, Azure, and GCP, ready to pursue cloud certifications to validate your skills.What you will learn Develop the core skills needed to work with cloud computing platforms such as AWS, Azure, and GCP Gain proficiency in compute, storage, and networking services across multi-cloud and hybrid-cloud environments Integrate cloud databases, big data, and machine learning services in multi-cloud environments Design and develop data pipelines, encompassing data ingestion, storage, processing, and visualization in the clouds Implement machine learning pipelines in a multi-cloud environment Secure cloud infrastructure ecosystems with advanced cloud security services Who this book is for Whether you're new to cloud computing or a seasoned professional looking to expand your expertise, this book is for anyone in the information technology domain who aspires to thrive in the realm of cloud computing. With this comprehensive roadmap, you’ll have the tools to build a successful cloud computing career.

This self-study book helps you master multiple clouds, including AWS, Azure, and GCP, and serves as a roadmap to becoming a certified cloud computing expert.

Gain in-depth knowledge of cloud computing concepts and apply them to accelerate your career in any cloud engineering role Key FeaturesGet to grips with key cloud computing concepts, cloud service providers, and best practicesExplore demonstrations for cloud computing models using real-world examplesAdopt the self-paced learning strategy and get industry-ready for cloud engineering rolesPurchase of the print or Kindle book includes a free eBook in the PDF formatBook Description If you want to upskill yourself in cloud computing domains to thrive in the IT industry, then you've come to the right place. Cloud Computing Demystified for Aspiring Professionals helps you to master cloud computing essentials and important technologies offered by cloud service providers needed to succeed in a cloud-centric job role. This book begins with an overview of transformation from traditional to modern-day cloud computing infrastructure, and various types and models of cloud computing. You'll learn how to implement secure virtual networks, virtual machines, and data warehouse resources including data lake services used in big data analytics — as well as when to use SQL and NoSQL databases and how to build microservices using multi-cloud Kubernetes services across AWS, Microsoft Azure, and Google Cloud. You'll also get step-by-step demonstrations of infrastructure, platform, and software cloud services and optimization recommendations derived from certified industry experts using hands-on tutorials, self-assessment questions, and real-world case studies. By the end of this book, you'll be ready to successfully implement cloud computing standardized concepts, services, and best practices in your workplace. What you will learnGain insights into cloud computing essentials and public, private, hybrid, and multi-cloud deployment modelsExplore core cloud computing services such as IaaS, PaaS, and SaaSDiscover major public cloud providers such as AWS, Microsoft, and GoogleUnlock the power of IaaS, PaaS, and SaaS with AWS, Azure, and GCPCreate secure networks, containers, Kubernetes, compute, databases, and API services on cloudDevelop industry-based cloud solutions using real-world examplesGet recommendations on exam preparation for cloud accreditationsWho this book is for The book is for aspiring cloud engineers, as well as college graduates, IT enthusiasts, and beginner-level cloud practitioners looking to get into cloud computing or transforming their career and upskilling themselves in a cloud engineering role in any industry. A basic understanding of networking, database development, and data analysis concepts and experience in programming languages such as Python and C# will help you get the most out of this book.

Prepare for the GCP ML certification exam along with exploring cloud computing and machine learning concepts and gaining Google Cloud ML skills Key FeaturesA comprehensive yet easy-to-follow Google Cloud machine learning study guideExplore full-spectrum and step-by-step practice examples to develop hands-on skillsRead through and learn from in-depth discussions of Google ML certification exam questionsBook Description This book aims to provide a study guide to learn and master machine learning in Google Cloud: to build a broad and strong knowledge base, train hands-on skills, and get certified as a Google Cloud Machine Learning Engineer. The book is for someone who has the basic Google Cloud Platform (GCP) knowledge and skills, and basic Python programming skills, and wants to learn machine learning in GCP to take their next step toward becoming a Google Cloud Certified Machine Learning professional. The book starts by laying the foundations of Google Cloud Platform and Python programming, followed the by building blocks of machine learning, then focusing on machine learning in Google Cloud, and finally ends the studying for the Google Cloud Machine Learning certification by integrating all the knowledge and skills together. The book is based on the graduate courses the author has been teaching at the University of Texas at Dallas. When going through the chapters, the reader is expected to study the concepts, complete the exercises, understand and practice the labs in the appendices, and study each exam question thoroughly. Then, at the end of the learning journey, you can expect to harvest the knowledge, skills, and a certificate. What you will learnProvision Google Cloud services related to data science and machine learningProgram with the Python programming language and data science librariesUnderstand machine learning concepts and model development processesExplore deep learning concepts and neural networksBuild, train, and deploy ML models with Google BigQuery ML, Keras, and Google Cloud Vertex AIDiscover the Google Cloud ML Application Programming Interface (API)Prepare to achieve Google Cloud Professional Machine Learning Engineer certificationWho this book is for Anyone from the cloud computing, data analytics, and machine learning domains, such as cloud engineers, data scientists, data engineers, ML practitioners, and engineers, will be able to acquire the knowledge and skills and achieve the Google Cloud professional ML Engineer certification with this study guide. Basic knowledge of Google Cloud Platform and Python programming is required to get the most out of this book.

This is a foundational book for people that want a career in cloud engineering. To understand why some of these cloud engineering roles exist, we need to understand the concept of the cloud. The goal of this book is to introduce the reader to cloud computing, the different paths for cloud engineering and how to navigate a cloud engineering career. Once the reader is able to learn the concepts introduced in this book, they will be ready to take on more complicated cloud related technologies.

The Only Official Google Cloud Study Guide The Official Google Cloud Certified Associate Cloud Engineer Study Guide, provides everything you need to prepare for this important exam and master the skills necessary to land that coveted Google Cloud Engineering certification. Beginning with a pre-book assessment quiz to evaluate what you know before you begin, each chapter features exam objectives and review questions, plus the online learning environment includes additional complete practice tests. Written by Dan Sullivan, a popular and experienced online course author for machine learning, big data, and Cloud topics, Official Google Cloud Certified Associate Cloud Engineer Study Guide is your ace in the hole for deploying and managing Google Cloud Services. • Select the right Google service from the various choices based on the application to be built • Compute with Cloud VMs and managing VMs • Plan and deploying storage • Network and configure access and security Google Cloud Platform is a leading public cloud that provides its users to many of the same software, hardware, and networking infrastructure used to power Google services. Businesses, organizations, and individuals can launch servers in minutes, store petabytes of data, and implement global virtual clouds with the Google Cloud Platform. Certified Associate Cloud Engineers have demonstrated the knowledge and skills needed to deploy and operate infrastructure, services, and networks in the Google Cloud. This exam guide is designed to help you understand the Google Cloud Platform in depth so that you can meet the needs of those operating resources in the Google Cloud.

Learn how to implement, deploy, and manage blockchain solutions across AWS, Azure, and GCP with the help of hands-on labs and real-world use cases Key Features Learn architecture design patterns and access code samples for building Web3 apps in the cloud Master the latest tools and cloud technologies for integrating DevOps in blockchain applications Strengthen your understanding of cloud-native blockchain through real-world use cases and best practices Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionAs Web3 technologies continue to gain momentum across industries, businesses are looking for new ways to leverage the benefits of Web3 and stay at the forefront of technological innovation. This comprehensive guide offers an in-depth exploration of cloud-native blockchain fundamentals, providing valuable insights into the benefits and challenges of deploying these technologies in the cloud. From foundational concepts to advanced techniques, the book covers everything you need to know about developing and deploying secure, scalable blockchain solutions on AWS, Azure, and GCP. Through hands-on tutorials and projects, you’ll explore the latest tools, technologies, real-world use cases, and best practices to expand your understanding of the field’s complexities and opportunities. This book ensures easy comprehension through practical examples and access to source code on GitHub. As you advance, you’ll master platform selection and apply your newfound knowledge to tackle complex problems and deliver innovative cloud-native blockchain solutions tailored for your specific needs. By the end of this book, you’ll have a deep understanding of cloud-native blockchain deployment and implementation, and you’ll be equipped with the skills and knowledge to build secure and scalable solutions.What you will learn Discover the benefits and challenges of deploying Web3 solutions in the cloud Deploy secure and scalable blockchain networks leveraging AWS, Azure, and GCP resources Follow step-by-step tutorials and code samples to build Web3 solutions in the cloud Use hosted Kubernetes platforms, such as EKS, AKS, and GKE, for custom blockchains Compare the blockchain capabilities and offerings of AWS, Azure, and Google Cloud Familiarize yourself with the tools and techniques for automating DevOps practices tailored to Web3 apps Who this book is for The book is for cloud developers and DevOps engineers who want to leverage blockchain technologies in their cloud-native solutions. Whether you’re an IT professional deploying and maintaining Web3 solutions in the enterprise or in public settings, or a business leader evaluating blockchain's potential, this resource is invaluable. Entrepreneurs, students, academics, and hobbyists exploring the latest Web3 development trends will also benefit from this book. Prior knowledge of cloud computing and blockchain concepts is recommended to make the best use of the expert insights, hands-on tutorials, and real-world use cases presented.

Effortlessly create and manage complex multi-component applications based on Docker containers Key Features Gain a clear understanding of software containers from the SecDevOps perspective Master the construction of application pieces within containers to achieve a seamless life cycle Prepare your applications to run smoothly and with ease in complex container orchestrators Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionDevelopers are changing their deployment artifacts from application binaries to container images, giving rise to the need to build container-based apps as part of their new development workflow. Managing an app’s life cycle is complex and requires effort—this book will show you how to efficiently develop, share, and execute applications. You’ll learn how to automate the build and delivery process using CI/CD tools with containers as container orchestrators manage the complexity of running cluster-wide applications, creating infrastructure abstraction layers, while your applications run with high availability, resilience, and persistence. As you advance, you’ll develop, test, and debug applications on your desktop and get them ready to run in production with optimal security standards, using deployment patterns and monitoring tools to help identify common issues. You’ll also review deployment patterns that’ll enable you to solve common deployment problems, providing high availability, scalability, and security to your applications. Finally, you’ll explore different solutions to monitor, log, and instrument your applications as per open-source community standards. By the end of this book, you’ll be able to manage your app’s life cycle by implementing CI/CD workflows using containers to automate the building and delivery of its components.What you will learn Find out how to build microservices-based applications using containers Deploy your processes within containers using Docker features Orchestrate multi-component applications on standalone servers Deploy applications cluster-wide in container orchestrators Solve common deployment problems such as persistency or app exposure using best practices Review your application’s health and debug it using open-source tools Discover how to orchestrate CI/CD workflows using containers Who this book is forThis book is for developers and DevOps engineers looking to learn about the implementation of containers in application development, especially DevOps engineers who deploy, monitor, and maintain container-based applications running on orchestrated platforms. In general, this book is for IT professionals who want to understand Docker container-based applications and their deployment. A basic understanding of coding and frontend-backend architectures is needed to follow the examples presented in this book.