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

Designing and building data pipelines

A data pipeline for big data systems must be able to integrate, consolidate, and transform many different types of data from various sources. Other useful supporting capabilities include data discovery, preparation, and management. Let's look at each of these.

Data integration

Google Cloud has a suite of services for data integration functions. Cloud Dataflow is a unified stream and batch processing service based on Apache Beam. It is a fully managed, serverless service offering with horizontal autoscaling. It allows you to create Apache Beam pipelines. These are data integration pipelines that offer functionalities to read, transform, and ingest data. If you're unfamiliar with Apache Beam pipelines and their use cases, one simple example would be a pipeline that writes different data subsets to different data stores based on a filter. Suppose, for instance, that you have a database of books identified by their titles. Your pipeline...