Book Image

Google Cloud Platform for Developers

By : Ted Hunter, Steven Porter
Book Image

Google Cloud Platform for Developers

By: Ted Hunter, Steven Porter

Overview of this book

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.
Table of Contents (17 chapters)

Big data and Google Cloud Platform

One of the major drivers towards the public cloud model is that public clouds drastically reduce both the upfront infrastructure and long-term operational cost of projects. This is largely due to the cost advantage public clouds gain by achieving economies of scale. One side effect of achieving economies of scale is that otherwise infeasible solutions become economically sound. As we saw in Chapter 10, Google Cloud Storage, one space this holds especially true is in data storage solutions, such as Google's ability to provide very cheap, always-online, nearline, and coldline storage. More generally, by lowering the cost of data storage, customers witness a shift in the cost-to-value ratio of storing large amounts of data. As a result, developers and analysts have access to much richer datasets, enabling very powerful data analysis and machine...