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Google Cloud Quickstart

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Google Cloud Quickstart

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Author : E. Paintsil
language : en
Publisher:
Release Date : 2021-12-26

Google Cloud Quickstart written by E. Paintsil and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-26 with Computers categories.

There is no easy and consistent way to introduce a beginner to Google Cloud and help him or her navigate the steep learning curve of the cloud platform. Again, it has never been easy to find a book that focuses on an aspect of Google Cloud and give a helping hand to gain the requisite practical experience to "takeoff" on your own. This book introduces beginner and intermediate users alike to Google Cloud Platform (GCP). I believe that one of the best ways to gain practical experience is to focus on infrastructure as a service and practice how to configure the important services in this domain. By this, I hope to bring the materials necessary to experience Google Cloud infrastructure in one place to make it easy for students to learn Google Cloud in a short time. As a textbook, I hope to explain the concepts behind the common but important infrastructure resources and services.

Google Cloud Quickstart

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Author : E. Paintsil
language : en
Publisher:
Release Date : 2021-12-26

Official Google Cloud Certified Associate Cloud Engineer Study Guide

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Author : Dan Sullivan
language : en
Publisher: John Wiley & Sons
Release Date : 2019-04-01

Official Google Cloud Certified Associate Cloud Engineer Study Guide written by Dan Sullivan and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-01 with Computers categories.

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.

Machine Learning With Go Quick Start Guide

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Author : Michael Bironneau
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-05-31

Machine Learning With Go Quick Start Guide written by Michael Bironneau and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-31 with Computers categories.

This quick start guide will bring the readers to a basic level of understanding when it comes to the Machine Learning (ML) development lifecycle, will introduce Go ML libraries and then will exemplify common ML methods such as Classification, Regression, and Clustering Key FeaturesYour handy guide to building machine learning workflows in Go for real-world scenariosBuild predictive models using the popular supervised and unsupervised machine learning techniquesLearn all about deployment strategies and take your ML application from prototype to production readyBook Description Machine learning is an essential part of today's data-driven world and is extensively used across industries, including financial forecasting, robotics, and web technology. This book will teach you how to efficiently develop machine learning applications in Go. The book starts with an introduction to machine learning and its development process, explaining the types of problems that it aims to solve and the solutions it offers. It then covers setting up a frictionless Go development environment, including running Go interactively with Jupyter notebooks. Finally, common data processing techniques are introduced. The book then teaches the reader about supervised and unsupervised learning techniques through worked examples that include the implementation of evaluation metrics. These worked examples make use of the prominent open-source libraries GoML and Gonum. The book also teaches readers how to load a pre-trained model and use it to make predictions. It then moves on to the operational side of running machine learning applications: deployment, Continuous Integration, and helpful advice for effective logging and monitoring. At the end of the book, readers will learn how to set up a machine learning project for success, formulating realistic success criteria and accurately translating business requirements into technical ones. What you will learnUnderstand the types of problem that machine learning solves, and the various approachesImport, pre-process, and explore data with Go to make it ready for machine learning algorithmsVisualize data with gonum/plot and GophernotesDiagnose common machine learning problems, such as overfitting and underfittingImplement supervised and unsupervised learning algorithms using Go librariesBuild a simple web service around a model and use it to make predictionsWho this book is for This book is for developers and data scientists with at least beginner-level knowledge of Go, and a vague idea of what types of problem Machine Learning aims to tackle. No advanced knowledge of Go (and no theoretical understanding of the math that underpins Machine Learning) is required.

Cloud Native Apps On Google Cloud Platform

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Author : Alasdair Gilchrist
language : en
Publisher: BPB Publications
Release Date : 2022-04-13

Cloud Native Apps On Google Cloud Platform written by Alasdair Gilchrist and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-13 with Computers categories.

Step-by-step guide for developing cloud native apps on GCP powered by hands-on interactive learning KEY FEATURES ● Cutting-edge coverage on Google Cloud Build, Cloud Run, GKE, Kubectl and Anthos. ● Includes tutorials and exercises to learn designing, deploying and running cloud native apps. ● Covers Service Mesh, Apps Optimization, logs monitoring and cloud IAM access. DESCRIPTION The book “Cloud Native Apps on Google Cloud Platform” teaches the readers how to design, construct, and maintain successful cloud-native apps using the Google Cloud Platform. With interactive tutorials, the book reinforces learning and helps to develop practical skills for working in an Agile and DevOps context. The book provides a step-by-step approach to building and managing cloud-native applications on Google Cloud Platform for Google Cloud Users, DevOps teams, and Cloud-Native Developers. First, you will investigate the advantages and applicability of each Google Serverless Computing option. You'll learn about Cloud Build and how to use it to prepare code files, create microservices, and build container images. The book walks readers through creating and running Docker image containers on Cloud Run and App Engine. You'll learn how to use kubectl to create and manage Kubernetes clusters, as well as how to configure the autoscaler for increased resilience and availability. You'll build a pipeline that uses Cloud Build to automate CI/CD and Pub/Sub to ingest streaming data. Finally, you'll have the opportunity to learn about Anthos, which enables you to manage massive GKE clusters in both Cloud and on-premises environments. WHAT YOU WILL LEARN ● Distinguish between using containers or microservices for cloud native apps. ● Build a streaming data pipeline using BigQuery and Dataflow using Pub/Sub. ● Practice to deploy and optimize cloud native applications on Kubernetes Engine. ● Build continuous integration/continuous delivery pipelines and improve Kubernetes apps. ● Learn to protect apps running on GCP from cyberattacks. WHO THIS BOOK IS FOR This book is meant for the Cloud and DevOps professionals and for those who wish to learn about Google Cloud services and incorporate them into end-to-end cloud applications. TABLE OF CONTENTS 1. Introducing Cloud Native Apps 2. Developing Cloud Native Apps with Cloud Shell 3. Preparing Source-Code with Cloud Build 4. Create and Deploy Microservices 5. Building and Deploying Containers in Cloud Build 6. Create a Serverless Pipeline with Pub/Sub, Dataflow and BigQuery 7. Container Orchestration with Google Kubernetes Engine 8. Deploying and Managing Kubernetes Applications 9. Optimizing Kubernetes Cluster and Apps in GKE 10. Deploying a CI/CD Pipeline with Kubernetes and Cloud Build 11. Build a Software Delivery Platform with Anthos 12. Application Management with Anthos 13. Securing Cloud Native Apps in Anthos

Google Cloud Platform For Data Engineering

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Author : Alasdair Gilchrist
language : en
Publisher: Alasdair Gilchrist
Release Date :

Google Cloud Platform For Data Engineering written by Alasdair Gilchrist and has been published by Alasdair Gilchrist this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.

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.

The Ultimate Guide To Building A Google Cloud Foundation

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Author : Patrick Haggerty
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-08-26

The Ultimate Guide To Building A Google Cloud Foundation written by Patrick Haggerty and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-26 with Computers categories.

Follow Google's own ten-step plan to construct a secure, reliable, and extensible foundation for all your Google Cloud base infrastructural needs Key FeaturesBuild your foundation in Google Cloud with this clearly laid out, step-by-step guideGet expert advice from one of Google's top trainersLearn to build flexibility and security into your Google Cloud presence from the ground upBook Description From data ingestion and storage, through data processing and data analytics, to application hosting and even machine learning, whatever your IT infrastructural need, there's a good chance that Google Cloud has a service that can help. But instant, self-serve access to a virtually limitless pool of IT resources has its drawbacks. More and more organizations are running into cost overruns, security problems, and simple "why is this not working?" headaches. This book has been written by one of Google's top trainers as a tutorial on how to create your infrastructural foundation in Google Cloud the right way. By following Google's ten-step checklist and Google's security blueprint, you will learn how to set up your initial identity provider and create an organization. Further on, you will configure your users and groups, enable administrative access, and set up billing. Next, you will create a resource hierarchy, configure and control access, and enable a cloud network. Later chapters will guide you through configuring monitoring and logging, adding additional security measures, and enabling a support plan with Google. By the end of this book, you will have an understanding of what it takes to leverage Terraform for properly building a Google Cloud foundational layer that engenders security, flexibility, and extensibility from the ground up. What you will learnCreate an organizational resource hierarchy in Google CloudConfigure user access, permissions, and key Google Cloud Platform (GCP) security groupsConstruct well thought out, scalable, and secure virtual networksStay informed about the latest logging and monitoring best practicesLeverage Terraform infrastructure as code automation to eliminate toilLimit access with IAM policy bindings and organizational policiesImplement Google's secure foundation blueprintWho this book is for This book is for anyone looking to implement a secure foundational layer in Google Cloud, including cloud engineers, DevOps engineers, cloud security practitioners, developers, infrastructural management personnel, and other technical leads. A basic understanding of what the cloud is and how it works, as well as a strong desire to build out Google Cloud infrastructure the right way will help you make the most of this book. Knowledge of working in the terminal window from the command line will be beneficial.

Beginning Postgresql On The Cloud

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Author : Baji Shaik
language : en
Publisher: Apress
Release Date : 2018-03-19

Beginning Postgresql On The Cloud written by Baji Shaik and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-19 with Computers categories.

Get started with PostgreSQL on the cloud and discover the advantages, disadvantages, and limitations of the cloud services from Amazon, Rackspace, Google, and Azure. Once you have chosen your cloud service, you will focus on securing it and developing a back-up strategy for your PostgreSQL instance as part of your long-term plan. Beginning PostgreSQL on the Cloud covers other essential topics such as setting up replication and high availability; encrypting your saved cloud data; creating a connection pooler for your database; and monitoring PostgreSQL on the cloud. The book concludes by showing you how to install and configure some of the tools that will help you get started with PostgreSQL on the cloud. This book shows you how database as a service enables you to spread your data across multiple data centers, ensuring that it is always accessible. You’ll discover that this model does not expect you to install and maintain databases yourself because the database service provider does it for you. You no longer have to worry about the scalability and high availability of your database. What You Will Learn Migrate PostgreSQL to the cloud Choose the best configuration and specifications of cloud instances Set up a backup strategy that enables point-in-time recovery Use connection pooling and load balancing on cloud environments Monitor database environments on the cloud Who This Book Is For Those who are looking to migrate to PostgreSQL on the Cloud. It will also help database administrators in setting up a cloud environment in an optimized way and help them with their day-to-day tasks.

Cloud Computing For Science And Engineering

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Author : Ian Foster
language : en
Publisher: MIT Press
Release Date : 2017-09-29

Cloud Computing For Science And Engineering written by Ian Foster and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-29 with Computers categories.

A guide to cloud computing for students, scientists, and engineers, with advice and many hands-on examples. The emergence of powerful, always-on cloud utilities has transformed how consumers interact with information technology, enabling video streaming, intelligent personal assistants, and the sharing of content. Businesses, too, have benefited from the cloud, outsourcing much of their information technology to cloud services. Science, however, has not fully exploited the advantages of the cloud. Could scientific discovery be accelerated if mundane chores were automated and outsourced to the cloud? Leading computer scientists Ian Foster and Dennis Gannon argue that it can, and in this book offer a guide to cloud computing for students, scientists, and engineers, with advice and many hands-on examples. The book surveys the technology that underpins the cloud, new approaches to technical problems enabled by the cloud, and the concepts required to integrate cloud services into scientific work. It covers managing data in the cloud, and how to program these services; computing in the cloud, from deploying single virtual machines or containers to supporting basic interactive science experiments to gathering clusters of machines to do data analytics; using the cloud as a platform for automating analysis procedures, machine learning, and analyzing streaming data; building your own cloud with open source software; and cloud security. The book is accompanied by a website, Cloud4SciEng.org, that provides a variety of supplementary material, including exercises, lecture slides, and other resources helpful to readers and instructors.

Google Cloud For Devops Engineers

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Author : Sandeep Madamanchi
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-07-02

Google Cloud For Devops Engineers written by Sandeep Madamanchi and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-02 with Computers categories.

Explore site reliability engineering practices and learn key Google Cloud Platform (GCP) services such as CSR, Cloud Build, Container Registry, GKE, and Cloud Operations to implement DevOps Key FeaturesLearn GCP services for version control, building code, creating artifacts, and deploying secured containerized applicationsExplore Cloud Operations features such as Metrics Explorer, Logs Explorer, and debug logpointsPrepare for the certification exam using practice questions and mock testsBook Description DevOps is a set of practices that help remove barriers between developers and system administrators, and is implemented by Google through site reliability engineering (SRE). With the help of this book, you'll explore the evolution of DevOps and SRE, before delving into SRE technical practices such as SLA, SLO, SLI, and error budgets that are critical to building reliable software faster and balance new feature deployment with system reliability. You'll then explore SRE cultural practices such as incident management and being on-call, and learn the building blocks to form SRE teams. The second part of the book focuses on Google Cloud services to implement DevOps via continuous integration and continuous delivery (CI/CD). You'll learn how to add source code via Cloud Source Repositories, build code to create deployment artifacts via Cloud Build, and push it to Container Registry. Moving on, you'll understand the need for container orchestration via Kubernetes, comprehend Kubernetes essentials, apply via Google Kubernetes Engine (GKE), and secure the GKE cluster. Finally, you'll explore Cloud Operations to monitor, alert, debug, trace, and profile deployed applications. By the end of this SRE book, you'll be well-versed with the key concepts necessary for gaining Professional Cloud DevOps Engineer certification with the help of mock tests. What you will learnCategorize user journeys and explore different ways to measure SLIsExplore the four golden signals for monitoring a user-facing systemUnderstand psychological safety along with other SRE cultural practicesCreate containers with build triggers and manual invocationsDelve into Kubernetes workloads and potential deployment strategiesSecure GKE clusters via private clusters, Binary Authorization, and shielded GKE nodesGet to grips with monitoring, Metrics Explorer, uptime checks, and alertingDiscover how logs are ingested via the Cloud Logging APIWho this book is for This book is for cloud system administrators and network engineers interested in resolving cloud-based operational issues. IT professionals looking to enhance their careers in administering Google Cloud services and users who want to learn about applying SRE principles and implementing DevOps in GCP will also benefit from this book. Basic knowledge of cloud computing, GCP services, and CI/CD and hands-on experience with Unix/Linux infrastructure is recommended. You'll also find this book useful if you're interested in achieving Professional Cloud DevOps Engineer certification.

Google Cloud Quickstart

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