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Author: Ernesto Garbarino
Publisher: Apress
ISBN: 1484254910
Category : Computers
Languages : en
Pages : 331
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Book Description
Use this beginner’s guide to understand and work with Kubernetes on the Google Cloud Platform and go from single monolithic Pods (the smallest unit deployed and managed by Kubernetes) all the way up to distributed, fault-tolerant stateful backing stores. You need only a familiarity with Linux, Bash, and Python to successfully use this book. Proficiency in Docker or cloud technology is not required. You will follow a learn-by-doing approach, running small experiments and observing the effects. Google open sourced Kubernetes in 2015 and now it is the industry standard in container orchestration. It has been adopted by all leading vendors of cloud, on-prem, and hybrid infrastructure services: Microsoft (Azure AKS), Amazon (AWS EKS), IBM (IBM Cloud Kubernetes Services), Alibaba Cloud (ACK), RedHat (OpenShift), and Pivotal (PKS). Even though Kubernetes is offered by all of the market-leading cloud providers, the Google Cloud Platform (GCP) offers an integrated shell (Google Cloud Shell) and a $300 credit to get started, which makes it the ideal platform to not only learn Kubernetes but also to implement final production workloads. What You Will Learn Set up a Kubernetes cluster in GCPDeploy simple Docker images using monolithic PodsArrange highly available and highly scalable applications using DeploymentsAchieve zero-downtime deployments using the Service controllerExternalize configuration using ConfigMaps and SecretsSet up batch processes and recurrent tasks using Jobs and CronJobsInstall horizontal (sidecar pattern) services using DaemonSetsImplement distributed, stateful backing stores using StatefulSets Who This Book Is For Beginners with basic Linux admin and scripting skills (Bash and Python). Proficiency with Docker is not required as all examples in the book use off-the-shelf public images from Docker Hub.
Author: Ernesto Garbarino
Publisher: Apress
ISBN: 1484254910
Category : Computers
Languages : en
Pages : 331
Get Book Here
Book Description
Use this beginner’s guide to understand and work with Kubernetes on the Google Cloud Platform and go from single monolithic Pods (the smallest unit deployed and managed by Kubernetes) all the way up to distributed, fault-tolerant stateful backing stores. You need only a familiarity with Linux, Bash, and Python to successfully use this book. Proficiency in Docker or cloud technology is not required. You will follow a learn-by-doing approach, running small experiments and observing the effects. Google open sourced Kubernetes in 2015 and now it is the industry standard in container orchestration. It has been adopted by all leading vendors of cloud, on-prem, and hybrid infrastructure services: Microsoft (Azure AKS), Amazon (AWS EKS), IBM (IBM Cloud Kubernetes Services), Alibaba Cloud (ACK), RedHat (OpenShift), and Pivotal (PKS). Even though Kubernetes is offered by all of the market-leading cloud providers, the Google Cloud Platform (GCP) offers an integrated shell (Google Cloud Shell) and a $300 credit to get started, which makes it the ideal platform to not only learn Kubernetes but also to implement final production workloads. What You Will Learn Set up a Kubernetes cluster in GCPDeploy simple Docker images using monolithic PodsArrange highly available and highly scalable applications using DeploymentsAchieve zero-downtime deployments using the Service controllerExternalize configuration using ConfigMaps and SecretsSet up batch processes and recurrent tasks using Jobs and CronJobsInstall horizontal (sidecar pattern) services using DaemonSetsImplement distributed, stateful backing stores using StatefulSets Who This Book Is For Beginners with basic Linux admin and scripting skills (Bash and Python). Proficiency with Docker is not required as all examples in the book use off-the-shelf public images from Docker Hub.
Author: Ernesto Garbarino
Publisher: Apress
ISBN: 1484254910
Category : Computers
Languages : en
Pages : 331
Get Book Here
Book Description
Use this beginner’s guide to understand and work with Kubernetes on the Google Cloud Platform and go from single monolithic Pods (the smallest unit deployed and managed by Kubernetes) all the way up to distributed, fault-tolerant stateful backing stores. You need only a familiarity with Linux, Bash, and Python to successfully use this book. Proficiency in Docker or cloud technology is not required. You will follow a learn-by-doing approach, running small experiments and observing the effects. Google open sourced Kubernetes in 2015 and now it is the industry standard in container orchestration. It has been adopted by all leading vendors of cloud, on-prem, and hybrid infrastructure services: Microsoft (Azure AKS), Amazon (AWS EKS), IBM (IBM Cloud Kubernetes Services), Alibaba Cloud (ACK), RedHat (OpenShift), and Pivotal (PKS). Even though Kubernetes is offered by all of the market-leading cloud providers, the Google Cloud Platform (GCP) offers an integrated shell (Google Cloud Shell) and a $300 credit to get started, which makes it the ideal platform to not only learn Kubernetes but also to implement final production workloads. What You Will Learn Set up a Kubernetes cluster in GCPDeploy simple Docker images using monolithic PodsArrange highly available and highly scalable applications using DeploymentsAchieve zero-downtime deployments using the Service controllerExternalize configuration using ConfigMaps and SecretsSet up batch processes and recurrent tasks using Jobs and CronJobsInstall horizontal (sidecar pattern) services using DaemonSetsImplement distributed, stateful backing stores using StatefulSets Who This Book Is For Beginners with basic Linux admin and scripting skills (Bash and Python). Proficiency with Docker is not required as all examples in the book use off-the-shelf public images from Docker Hub.
Author: Alasdair Gilchrist
Publisher: Alasdair Gilchrist
ISBN:
Category : Computers
Languages : en
Pages : 372
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Book Description
Google Cloud Platform for Data Engineering is designed to take the beginner through a journey to become a competent and certified GCP data engineer. The book, therefore, is split into three parts; the first part covers fundamental concepts of data engineering and data analysis from a platform and technology-neutral perspective. Reading part 1 will bring a beginner up to speed with the generic concepts, terms and technologies we use in data engineering. The second part, which is a high-level but comprehensive introduction to all the concepts, components, tools and services available to us within the Google Cloud Platform. Completing this section will provide the beginner to GCP and data engineering with a solid foundation on the architecture and capabilities of the GCP. Part 3, however, is where we delve into the moderate to advanced techniques that data engineers need to know and be able to carry out. By this time the raw beginner you started the journey at the beginning of part 1 will be a knowledgable albeit inexperienced data engineer. However, by the conclusion of part 3, they will have gained the advanced knowledge of data engineering techniques and practices on the GCP to pass not only the certification exam but also most interviews and practical tests with confidence. In short part 3, will provide the prospective data engineer with detailed knowledge on setting up and configuring DataProc - GCPs version of the Spark/Hadoop ecosystem for big data. They will also learn how to build and test streaming and batch data pipelines using pub/sub/ dataFlow and BigQuery. Furthermore, they will learn how to integrate all the ML and AI Platform components and APIs. They will be accomplished in connecting data analysis and visualisation tools such as Datalab, DataStudio and AI notebooks amongst others. They will also by now know how to build and train a TensorFlow DNN using APIs and Keras and optimise it to run large public data sets. Also, they will know how to provision and use Kubeflow and Kube Pipelines within Google Kubernetes engines to run container workloads as well as how to take advantage of serverless technologies such as Cloud Run and Cloud Functions to build transparent and seamless data processing platforms. The best part of the book though is its compartmental design which means that anyone from a beginner to an intermediate can join the book at whatever point they feel comfortable.
Author: Praveen Kukreti
Publisher: BPB Publications
ISBN: 9355513321
Category : Computers
Languages : en
Pages : 298
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Book Description
Explore the Essential Concepts, Tools, and Services in GCP KEY FEATURES ● Build a solid foundation of the Google Cloud Platform. ● Work with different AI and Machine Learning services offered by Google Cloud. ● Learn how to use Google cloud services to build scalable apps. DESCRIPTION Google Cloud platform has a suite of cloud computing services for developing and maintaining software. It includes products like Google Compute Engine, Google App Engine, Google Cloud Storage, and Google Container Engine. With so much to offer, we will learn how to manage services running on Google Cloud. ‘Google Cloud Platform All-In-One Guide’ is primarily for everyone who wants to get familiar with the comprehensive list of services in GCP. You will work with various cloud-based services in computing, storage, database, and networking domains. You will understand how Big Data services can be used for developing end-to-end ETL/ELT pipelines. Lastly, you will explore various APIs available in Google cloud. The book ends with a chapter on best practices that will help you maximize resource utilization and cost optimization. By the end of the book, you will be able to design, develop, and deploy apps in GCP. WHAT YOU WILL LEARN ● Explore and work with security and monitoring services in Google Cloud. ● Learn how to build an ETL Pipeline in the Google Cloud Platform. ● Build and deploy code-based custom models using Vertex AI and Jupyter notebook. ● Learn how to create workflows using GCP services. ● Get an overview of best practices for securely deploying your workloads on Google Cloud. WHO THIS BOOK IS FOR This book is for everyone new to cloud computing or Google cloud. Cloud professionals who are looking to migrate their services to the Google cloud platform will find this book helpful. TABLE OF CONTENTS 1. Cloud Computing Fundamentals 2. Compute in Google Cloud 3. Storage in Google Cloud 4. Database Services in Google Cloud 5. Networking in Google Cloud 6. Security and Monitoring Services in Google Cloud 7. Big Data in Google Cloud 8. AI/ML in Google Cloud 9. Orchestration Services in GCP 10. Migration Services in GCP 11. Best Practices 12. Bonus Chapter 13. Use Cases
Author: Alasdair Gilchrist
Publisher: Alasdair Gilchrist
ISBN:
Category : Computers
Languages : en
Pages : 607
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Book Description
Learn fundamental to advanced GCP architectural techniques using 30 + real-world use cases. The 'Google Cloud Platform an Architect's Guide' is a comprehensive handbook that covers everything that you need to know from GCP fundamentals to advanced cloud architecture topics. The book covers what you need to understand to pass the Google certification exams but goes far further and deeper as it explores real-world use cases and business scenarios. But you don't need to be an IT expert as the book is designed to cater for both beginners and those experienced in other cloud or on other on-premises networks. To that end, the book is split into distinct parts that caters for all levels of expertise. Part -1 is aimed at the novice someone new to a cloud architecture environment that needs to become familiar with the fundamentals of cloud architecture and industry best practices so the more experienced reader may wish to skip this section. Part-2 takes a far deeper dive into GCP theory and practice as well as providing real-world use cases and practical tips that are beneficial for architects at all levels. Part-3 delves much deeper into GCP practical theory on elasticity, scalability and resilience. It also covers Kubernetes in greater detail and touches on High-Performance Computing and IoT designs. The book closes with a final part dealing with cloud-native design practices and as such it covers design, monitoring, notification and remediation techniques to ensure best practice in cloud-native application design, deployment, stabilisation and commissioning.
Author: Alasdair Gilchrist
Publisher: Alasdair Gilchrist
ISBN:
Category : Computers
Languages : en
Pages : 509
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Book Description
Welcome to "Google Cloud Platform – Networking: Beginner to Skilled GCP Network Practitioner in One Book". As the subtitle conveys this book is a beginners-to-experts comprehensive guide to networking for the Google Cloud Platform. We do not assume any prior networking skills or knowledge so the book is designed for both the beginner in networking as well as those proficient in on-premise networking who want to transfer their skill to the GCP. It is a thorough and comprehensive guide to the entire set of core networking technologies, principles and best practices that you will need to know about for the GCP Networking Certification exam. Nonetheless, this book is not just for those pursuing GCP Networking certification it is also aimed at those wishing to pursue a career in GCP networking. Consequently, it covers not just the exam syllabus but goes into much greater depth and scope through practical examples and relevant networking tips and best practices. The goal is to provide you, the reader, with a deep and wide understanding of GCP networking and its core technologies, techniques and concepts so that you can ultimately call yourself and importantly confidently demonstrate your skills as a proficient GCP network engineer. To that end, we have designed the book into parts: Part 1 is a network primer aimed at the beginner as it serves as an introduction to key generic network concepts that you as a beginner will need to know when we move the focus to specific GCP networking concepts; Part 2, is an introduction to Google’ internal private and global network, the underlying technologies and how it works under the bonnet. This should be of value and interest to readers of all skill levels; Part 3, is all about GCP cloud-specific networking that encompasses; VPC design, planning, deployment, migration, operations and performance monitoring and management. We will study relevant use-case in each chapter to better demonstrate the use of a particular technology and to help solidify a deeper understanding. The final chapter is aimed at those pursuing a career as a GCP network designer or a pre-sales consultant as well as project managers as it concerns Billing. Hence we will take a deep dive into Billing from a network perspective but it is not just an appendix for your everyday reference – it is a comprehensive guide to cost forecasting, monitoring and cost management. Overall, this book can be read cover-to-cover, by individual parts, or as a reference for particular technologies. Take your time to browse the Table of Reference to discover the scope and get a feel for the depth of knowledge within each chapter and topic.
Author: Daniel Danielecki
Publisher: Daniel Danielecki
ISBN:
Category : Computers
Languages : en
Pages : 70
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Book Description
⌛️ Short and to the point; why should you buy the PDF with these Practice Tests Exams: 1. Always happy to answer your questions on Google Play Books and outside :) 2. Failed? Please submit a screenshot of your exam result and request a refund; we'll always accept it. 3. Learn about topics, such as: - BigQuery; - Billing Administrator; - Cloud Audit; - Cloud Bigtable; - Cloud Concepts; - Cloud Dataflow; - Cloud Datastore; - Cloud Identity and Access Management (Cloud IAM); - Cloud Logging; - Cloud Pub/Sub; - Cloud Run; - Cloud SDK; - Cloud Shell; - Cloud Spanner; - Cloud SQL; - Cloud Storage; - Coldline Storage; - Compute Engine; - Deployment Manager; - Google Cloud Platform Console (GCP Console); - Google App Engine; - Google Cloud Marketplace; - Google Kubernetes Engine (GKE); - Nearline Storage; - Project Billing Manager; - Stackdriver; - Virtual Private Cloud (VPC); - Much More! 4. Questions are similar to the actual exam, without duplications (like in other practice exams ;-)). 5. These tests are not a GCP Associate Cloud Engineer (ACE) Exam Dump. Some people use brain dumps or exam dumps, but that's absurd, which we don't practice. 6. 179 unique questions.
Author: Legorie Rajan PS
Publisher: Packt Publishing Ltd
ISBN: 1788294564
Category : Computers
Languages : en
Pages : 274
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Book Description
Practical recipes to implement cost-effective and scalable cloud solutions for your organization Key Features Implement Google Cloud services in your organization Leverage Google Cloud components to secure your organization’s data A recipe-based guide that promises hands-on experience in deploying a highly scalable and available environment Book Description Google Cloud Platform is a cloud computing platform that offers products and services to host applications using state-of-the art infrastructure and technology. You can build and host applications and websites, store data, and analyze data on Google's scalable infrastructure. This book follows a recipe-based approach, giving you hands-on experience to make the most of Google Cloud services. This book starts with practical recipes that explain how to utilize Google Cloud's common services. Then, you'll see how to make full use of Google Cloud components such as networking, security, management, and developer tools. Next, we'll deep dive into implementing core Google Cloud services into your organization, with practical recipes on App Engine, Compute Engine microservices with Cloud Functions, virtual networks, and Cloud Storage. Later, we'll provide recipes on implementing authentication and security, Cloud APIs, command-line management, deployment management, and the Cloud SDK. Finally, we'll cover administration troubleshooting tasks with the Compute and Container Engines and we'll show how to monitor your organization's efficiency with best practices. By the end of this book, you'll have a complete understanding of how to implement Google Cloud services in your organization with ease. What you will learn Host a Python application on Google Compute Engine Host an application using Google Cloud Functions Migrate a MySQL DB to Cloud Spanner Configure a network for a highly available application on GCP Learn simple image processing using Storage and Cloud Functions Automate security checks using Policy Scanner Understand tools for monitoring a production environment in GCP Learn to manage multiple projects using service accounts Who this book is for This book is for IT professionals, engineers, and developers looking at implementing Google Cloud in their organizations. Administrators and architects planning to make their organization more efficient with Google Cloud will also find this book useful. Basic understanding of Cloud services and the Google Cloud platform is necessary.
Author: Ted Hunter
Publisher: Packt Publishing Ltd
ISBN: 1838648704
Category : Computers
Languages : en
Pages : 763
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Book Description
Build cost-effective and robust cloud solutions with Google Cloud Platform (GCP) using these simple and practical recipes Key FeaturesExplore the various service offerings of the GCPHost a Python application on Google Compute EngineSecurely maintain application states with Cloud Storage, Datastore, and BigtableBook Description GCP is a cloud computing platform with a wide range of products and services that enable you to build and deploy cloud-hosted applications. This Learning Path will guide you in using GCP and designing, deploying, and managing applications on Google Cloud. You will get started by learning how to use App Engine to access Google's scalable hosting and build software that runs on this framework. With the help of Google Compute Engine, you’ll be able to host your workload on virtual machine instances. The later chapters will help you to explore ways to implement authentication and security, Cloud APIs, and command-line and deployment management. As you hone your skills, you’ll understand how to integrate your new applications with various data solutions on GCP, including Cloud SQL, Bigtable, and Cloud Storage. Following this, the book will teach you how to streamline your workflow with tools, including Source Repositories, Container Builder, and Stackdriver. You'll also understand how to deploy and debug services with IntelliJ, implement continuous delivery pipelines, and configure robust monitoring and alerts for your production systems. By the end of this Learning Path, you'll be well versed with GCP’s development tools and be able to develop, deploy, and manage highly scalable and reliable applications. This Learning Path includes content from the following Packt products: Google Cloud Platform for Developers Ted Hunter and Steven PorterGoogle Cloud Platform Cookbook by Legorie Rajan PSWhat you will learnHost an application using Google Cloud FunctionsMigrate a MySQL database to Cloud SpannerConfigure a network for a highly available application on GCPLearn simple image processing using Storage and Cloud FunctionsAutomate security checks using Policy ScannerDeploy and run services on App Engine and Container EngineMinimize downtime and mitigate issues with Stackdriver Monitoring and DebuggerIntegrate with big data solutions, including BigQuery, Dataflow, and Pub/SubWho this book is for This Learning Path is for IT professionals, engineers, and developers who want to implement Google Cloud in their organizations. Administrators and architects planning to make their organization more efficient with Google Cloud will also find this Learning Path useful. Basic understanding of GCP and its services is a must.
Author: Murari Ramuka
Publisher: BPB Publications
ISBN: 9389423635
Category : Computers
Languages : en
Pages : 287
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Book Description
Step-by-step guide to different data movement and processing techniques, using Google Cloud Platform Services DESCRIPTION Modern businesses are awash with data, making data-driven decision-making tasks increasingly complex. As a result, relevant technical expertise and analytical skills are required to do such tasks. This book aims to equip you with enough knowledge of Cloud Computing in conjunction with Google Cloud Data platform to succeed in the role of a Cloud data expert. The current market is trending towards the latest cloud technologies, which is the need of the hour. Google being the pioneer, is dominating this space with the right set of cloud services being offered as part of GCP (Google Cloud Platform). At this juncture, this book will be very vital and will cover all the services that are being offered by GCP, putting emphasis on Data services. This book starts with sophisticated knowledge on Cloud Computing. It also explains different types of data services/technology and machine learning algorithm/Pre-Trained API through real-business problems, which are built on the Google Cloud Platform (GCP). With some of the latest business examples and hands-on guide, this book will enable the developers entering the data analytics fields to implement an end-to-end data pipeline, using GCP Data services. Through the course of the book, you will come across multiple industry-wise use cases, like Building Datawarehouse using Big Query, a sample real-time data analytics solution on machine learning and Artificial Intelligence that helped with the business decision, by employing a variety of data science approaches on Google Cloud environment. Whether yourÊbusinessÊis at the early stage of cloud implementation in its journey or well on its way to digital transformation,ÊGoogle Cloud'sÊsolutions and technologies will always help chart a path to success. This book can be used to develop the GCP concepts in an easy way. It contains many examples showcasing the implementation of a GCP service. It enables the learning of the basic and advance concepts of Google Cloud Data Platform. This book is divided into 7 chapters and provides a detailed description of the core concepts of each of the Data services offered by Google Cloud. KEY FEATURES Learn the basic concept of Cloud Computing along with different Cloud service provides with their supported Models (IaaS/PaaS/SaaS) Learn the basics of Compute Engine, App Engine, Container Engine, Project and Billing setup in the Google Cloud Platform Learn how and when to use Cloud DataFlow, Cloud DataProc and Cloud DataPrepÊ Build real-time data pipeline to support real-time analytics using Pub/Sub messaging service Setting up a fully managed GCP Big Data Cluster using Cloud DataProc for runningÊApache SparkÊandÊApache HadoopÊclusters in a simpler, more cost-efficient manner Learn how to use Cloud Data Studio for visualizing the data on top of Big Query Implement and understand real-world business scenarios for Machine Learning, Data Pipeline Engineering WHAT WILL YOU LEARN By the end of the book, you will have come across different data services and platforms offered by Google Cloud, and how those services/features can be enabled to serve business needs. You will also see a few case studies to put your knowledge to practice and solve business problems such as building a real-time streaming pipeline engine, Scalable Data Warehouse on Cloud, fully managed Hadoop cluster on Cloud and enabling TensorFlow/Machine Learning APIÕs to support real-life business problems. Remember to practice additional examples to master these techniques. WHO IS THIS BOOK FOR This book is for professionals as well as graduates who want to build a career in Google Cloud data analytics technologies. While no prior knowledge of Cloud Computing or related technologies is assumed, it will be helpful to have some data background and experience. One stop shop for those who wish to get an initial to advance understanding of the GCP data platform. The target audience will be data engineers/professionals who are new, as well as those who are acquainted with the tools and techniques related to cloud and data space.ÊÊ _Ê Ê Ê Individuals who have basic data understanding (i.e. Data and cloud) and have done some work in the field ofÊ data analytics, can refer/use this book to master their knowledge/understanding. _Ê Ê Ê The highlight of this book is that it will start with theÊ basic cloud computing fundamentals and will move on to cover the advance concepts on GCP cloud data analytics and hence can be referred across multiple different levels of audiences.Ê Table of Contents 1. GCP Overview and Architecture 2. Data Storage in GCPÊ 3. Data Processing in GCP with Pub/Sub and DataflowÊ 4. Data Processing in GCP with DataPrep and Dataflow 5. Big Query and Data Studio 6. Machine Learning with GCP 7. Sample Use cases and Examples
