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Google Cloud Platform for Developers

Google Cloud Platform for Developers

By : Ted Hunter, Steven Porter
4.3 (4)
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Google Cloud Platform for Developers

Google Cloud Platform for Developers

4.3 (4)
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)
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Summary

Google has played a major role in advancing the world of large-scale data persistence. Necessity is the mother of invention. With the creation of Bigtable, Google had an ideal solution to some of its hardest internal problems, such as indexing the internet, charting the entire planet, and building the world's largest catalog of cat videos. As a managed service in the GCP catalog, anyone can solve data problems on the same scale.

While Bigtable presents an extremely powerful platform for building systems on huge datasets, it does so at the cost of basic database functionality such as transactions and queries. It also only solves the problem of scale at the far end. For most applications, there simply isn't a need for petabytes of data or millions of writes per second. Many of these applications simply need to be solved for persistence in an easy-to-use way that...

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