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

Chapter 11: Applying Machine Learning and Artificial Intelligence

The subject of Artificial Intelligence (AI) is no longer exclusive to research and innovation. It's here and now. In fact, it's been around for quite some time. With the advancements in Machine Learning (ML) science and techniques, along with the increase in hardware capacity and data availability, the entry barrier has never been lower. Modern and data-driven enterprises can now leverage cloud-based AI to unlock insights from their data.

In this chapter, you will learn how to leverage Google Cloud Platform's (GCP's) AI services and prebuilt ML models. You will learn how these cloud-based solutions can add business value and discover real-world use cases. Then, we're going to explore how to build, train, and run custom models on GCP and even look at ways to do so without any coding or data science experience. Finally, you will learn how to apply MLOps to automate ML pipelines and productionize...