Book Image

Architecting Google Cloud Solutions

By : Victor Dantas
Book Image

Architecting Google Cloud Solutions

By: Victor Dantas

Overview of this book

Google has been one of the top players in the public cloud domain thanks to its agility and performance capabilities. This book will help you design, develop, and manage robust, secure, and dynamic solutions to successfully meet your business needs. You'll learn how to plan and design network, compute, storage, and big data systems that incorporate security and compliance from the ground up. The chapters will cover simple to complex use cases for devising solutions to business problems, before focusing on how to leverage Google Cloud's Platform-as-a-Service (PaaS) and Software-as-a-Service (SaaS) capabilities for designing modern no-operations platforms. Throughout this book, you'll discover how to design for scalability, resiliency, and high availability. Later, you'll find out how to use Google Cloud to design modern applications using microservices architecture, automation, and Infrastructure-as-Code (IaC) practices. The concluding chapters then demonstrate how to apply machine learning and artificial intelligence (AI) to derive insights from your data. Finally, you will discover best practices for operating and monitoring your cloud solutions, as well as performing troubleshooting and quality assurance. By the end of this Google Cloud book, you'll be able to design robust enterprise-grade solutions using Google Cloud Platform.
Table of Contents (17 chapters)
1
Section 1: Introduction to Google Cloud
4
Section 2: Designing Great Solutions in Google Cloud
10
Section 3: Designing for the Modern Enterprise

Summary

In this first chapter, you learned about the appeal of cloud computing and how to make the case for cloud adoption and for Google Cloud in particular. You also learned about some of Google Cloud's key differentiators, such as its fast network and its cutting-edge big data and AI services. We had a look at the core services of the platform and things such as regions and zones, the resource hierarchy, and other GCP concepts. Finally, we got started with the platform by setting up an account and installing the Cloud SDK, before teasing out BigQuery's powerful capabilities by running a fast serverless query on a sample public dataset.

In the next chapter, we will get into IAM in Google Cloud and look at ways to improve the cost discipline. To help you truly master the basics, we will end the next chapter with a case study and a small hands-on project.