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Google Cloud Platform Administration

Author : Ranjit Singh Thakurratan

Publisher : Packt Publishing Ltd

Page : 224 pages

File Size : 49,64 MB

Release : 2018-09-29

Category : Computers

ISBN : 1788626605

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Book Description

Make the most of GCP’s offerings to manage your data center workload and optimize deployments Key FeaturesDiscover new techniques to administer, manage, and deploy applications on GCPUnderstand effective solutions for storing, retrieving, and deploying your container imagesExplore various offerings of GCP for operations and security Book Description On-premise data centers are costly to manage. If you need a data center but don’t want to deal with a physical one, Google Cloud Platform (GCP) is the solution. With GCP, you can build, test, and deploy applications on Google’s infrastructure. Google Cloud Platform Administration begins with GCP fundamentals, with the help of which you will deploy your first app and gain an understanding of Google Cloud architecture and services. Furthermore, you will learn how to manage Compute, networking, and storage resources. As you make your way through the book, you will learn how to track and manage GCP’s usage, monitoring, and billing access control. You will also be able to manage your GCP's access and permissions. In the concluding chapters, you will explore a list of different developer tools for managing and interacting with the GCP platform. By the end of this book, you will have learned how to effectively deploy workloads on GCP. What you will learnUnderstand all GCP Compute componentsDeploy and manage multiple GCP storage optionsManage and utilize the networking resources offered by GCPExplore the functionalities and features of the GCP Container Understand the workings of GCP operations such as monitoring and error reporting Discover an immune GCP using its identity and security optionsWho this book is for Google Cloud Platform Administration is for administrators, cloud architects, and engineers who want to leverage the upcoming Google Cloud Platform. Some basic understanding of cloud computing will be useful.



GOOGLE CLOUD QUICKSTART

Author : E. Paintsil

Publisher :

Page : 489 pages

File Size : 44,42 MB

Release : 2021-12-26

Category : Computers

ISBN :

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Book Description

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.



Building Google Cloud Platform Solutions

Author : Ted Hunter

Publisher : Packt Publishing Ltd

Page : 763 pages

File Size : 37,20 MB

Release : 2019-03-26

Category : Computers

ISBN : 1838648704

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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.



Google Cloud Platform for Data Engineering

Author : Alasdair Gilchrist

Publisher : Alasdair Gilchrist

Page : 372 pages

File Size : 31,8 MB

Release :

Category : Computers

ISBN :

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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.



Data Science on the Google Cloud Platform

Author : Valliappa Lakshmanan

Publisher : "O'Reilly Media, Inc."

Page : 403 pages

File Size : 28,69 MB

Release : 2017-12-12

Category : Computers

ISBN : 1491974532

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Book Description

Learn how easy it is to apply sophisticated statistical and machine learning methods to real-world problems when you build on top of the Google Cloud Platform (GCP). This hands-on guide shows developers entering the data science field how to implement an end-to-end data pipeline, using statistical and machine learning methods and tools on GCP. Through the course of the book, you’ll work through a sample business decision by employing a variety of data science approaches. Follow along by implementing these statistical and machine learning solutions in your own project on GCP, and discover how this platform provides a transformative and more collaborative way of doing data science. You’ll learn how to: Automate and schedule data ingest, using an App Engine application Create and populate a dashboard in Google Data Studio Build a real-time analysis pipeline to carry out streaming analytics Conduct interactive data exploration with Google BigQuery Create a Bayesian model on a Cloud Dataproc cluster Build a logistic regression machine-learning model with Spark Compute time-aggregate features with a Cloud Dataflow pipeline Create a high-performing prediction model with TensorFlow Use your deployed model as a microservice you can access from both batch and real-time pipelines



Cloud Native Apps on Google Cloud Platform

Author : Alasdair Gilchrist

Publisher : BPB Publications

Page : 431 pages

File Size : 13,48 MB

Release : 2022-04-13

Category : Computers

ISBN : 935551123X

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Book Description

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





Cloud Analytics with Google Cloud Platform

Author : Sanket Thodge

Publisher : Packt Publishing Ltd

Page : 273 pages

File Size : 34,96 MB

Release : 2018-04-10

Category : Computers

ISBN : 1788838599

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Book Description

Combine the power of analytics and cloud computing for faster and efficient insights Key Features Master the concept of analytics on the cloud: and how organizations are using it Learn the design considerations and while applying a cloud analytics solution Design an end-to-end analytics pipeline on the cloud Book Description With the ongoing data explosion, more and more organizations all over the world are slowly migrating their infrastructure to the cloud. These cloud platforms also provide their distinct analytics services to help you get faster insights from your data. This book will give you an introduction to the concept of analytics on the cloud, and the different cloud services popularly used for processing and analyzing data. If you’re planning to adopt the cloud analytics model for your business, this book will help you understand the design and business considerations to be kept in mind, and choose the best tools and alternatives for analytics, based on your requirements. The chapters in this book will take you through the 70+ services available in Google Cloud Platform and their implementation for practical purposes. From ingestion to processing your data, this book contains best practices on building an end-to-end analytics pipeline on the cloud by leveraging popular concepts such as machine learning and deep learning. By the end of this book, you will have a better understanding of cloud analytics as a concept as well as a practical know-how of its implementation What you will learn Explore the basics of cloud analytics and the major cloud solutions Learn how organizations are using cloud analytics to improve the ROI Explore the design considerations while adopting cloud services Work with the ingestion and storage tools of GCP such as Cloud Pub/Sub Process your data with tools such as Cloud Dataproc, BigQuery, etc Over 70 GCP tools to build an analytics engine for cloud analytics Implement machine learning and other AI techniques on GCP Who this book is for This book is targeted at CIOs, CTOs, and even analytics professionals looking for various alternatives to implement their analytics pipeline on the cloud. Data professionals looking to get started with cloud-based analytics will also find this book useful. Some basic exposure to cloud platforms such as GCP will be helpful, but not mandatory.



Google Cloud Platform for Developers

Author : Ted Hunter

Publisher : Packt Publishing Ltd

Page : 496 pages

File Size : 10,53 MB

Release : 2018-07-30

Category : Computers

ISBN : 1788830830

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Book Description

Develop, deploy, and scale your applications with Google Cloud Platform Key Features Create and deploy your applications on Google Cloud Platform Store and manage source code and debug Cloud-hosted apps with plugins and IDEs Streamline developer workflows with tools for alerting and managing deployments Book Description Google Cloud Platform (GCP) provides autoscaling compute power and distributed in-memory cache, task queues, and datastores to write, build, and deploy Cloud-hosted applications. With Google Cloud Platform for Developers, you will be able to develop and deploy scalable applications from scratch and make them globally available in almost any language. This book will guide you in designing, deploying, and managing applications running on Google Cloud. You’ll start with App Engine and move on to work with Container Engine, compute engine, and cloud functions. You’ll learn how to integrate your new applications with the various data solutions on GCP, including Cloud SQL, Bigtable, and Cloud Storage. This book will teach you how to streamline your workflow with tools such as Source Repositories, Container Builder, and StackDriver. Along the way, you’ll see how to deploy and debug services with IntelliJ, implement continuous delivery pipelines, and configure robust monitoring and alerting for your production systems. By the end of this book, you’ll be well-versed with all the development tools of Google Cloud Platform, and you’ll develop, deploy, and manage highly scalable and reliable applications. What you will learn Understand the various service offerings on GCP Deploy and run services on managed platforms such as App Engine and Container Engine Securely maintain application states with Cloud Storage, Datastore, and Bigtable Leverage StackDriver monitoring and debugging to minimize downtime and mitigate issues without impacting users Design and implement complex software solutions utilizing Google Cloud Integrate with best-in-class big data solutions such as Bigquery, Dataflow, and Pub/Sub Who this book is for Google Cloud Platform for Developers is for application developers. This book will enable you to fully leverage the power of Google Cloud Platform to build resilient and intelligent software solutions.



Hands-On Machine Learning on Google Cloud Platform

Author : Giuseppe Ciaburro

Publisher : Packt Publishing Ltd

Page : 489 pages

File Size : 38,95 MB

Release : 2018-04-30

Category : Computers

ISBN : 1788398874

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Book Description

Unleash Google's Cloud Platform to build, train and optimize machine learning models Key Features Get well versed in GCP pre-existing services to build your own smart models A comprehensive guide covering aspects from data processing, analyzing to building and training ML models A practical approach to produce your trained ML models and port them to your mobile for easy access Book Description Google Cloud Machine Learning Engine combines the services of Google Cloud Platform with the power and flexibility of TensorFlow. With this book, you will not only learn to build and train different complexities of machine learning models at scale but also host them in the cloud to make predictions. This book is focused on making the most of the Google Machine Learning Platform for large datasets and complex problems. You will learn from scratch how to create powerful machine learning based applications for a wide variety of problems by leveraging different data services from the Google Cloud Platform. Applications include NLP, Speech to text, Reinforcement learning, Time series, recommender systems, image classification, video content inference and many other. We will implement a wide variety of deep learning use cases and also make extensive use of data related services comprising the Google Cloud Platform ecosystem such as Firebase, Storage APIs, Datalab and so forth. This will enable you to integrate Machine Learning and data processing features into your web and mobile applications. By the end of this book, you will know the main difficulties that you may encounter and get appropriate strategies to overcome these difficulties and build efficient systems. What you will learn Use Google Cloud Platform to build data-based applications for dashboards, web, and mobile Create, train and optimize deep learning models for various data science problems on big data Learn how to leverage BigQuery to explore big datasets Use Google’s pre-trained TensorFlow models for NLP, image, video and much more Create models and architectures for Time series, Reinforcement Learning, and generative models Create, evaluate, and optimize TensorFlow and Keras models for a wide range of applications Who this book is for This book is for data scientists, machine learning developers and AI developers who want to learn Google Cloud Platform services to build machine learning applications. Since the interaction with the Google ML platform is mostly done via the command line, the reader is supposed to have some familiarity with the bash shell and Python scripting. Some understanding of machine learning and data science concepts will be handy