Book Image

The Definitive Guide to Modernizing Applications on Google Cloud

By : Steve (Satish) Sangapu, Dheeraj Panyam, Jason Marston
Book Image

The Definitive Guide to Modernizing Applications on Google Cloud

By: Steve (Satish) Sangapu, Dheeraj Panyam, Jason Marston

Overview of this book

Legacy applications, which comprise 75–80% of all enterprise applications, often end up being stuck in data centers. Modernizing these applications to make them cloud-native enables them to scale in a cloud environment without taking months or years to start seeing the benefits. This book will help software developers and solutions architects to modernize their applications on Google Cloud and transform them into cloud-native applications. This book helps you to build on your existing knowledge of enterprise application development and takes you on a journey through the six Rs: rehosting, replatforming, rearchitecting, repurchasing, retiring, and retaining. You'll learn how to modernize a legacy enterprise application on Google Cloud and build on existing assets and skills effectively. Taking an iterative and incremental approach to modernization, the book introduces the main services in Google Cloud in an easy-to-understand way that can be applied immediately to an application. By the end of this Google Cloud book, you'll have learned how to modernize a legacy enterprise application by exploring various interim architectures and tooling to develop a cloud-native microservices-based application.
Table of Contents (26 chapters)
1
Section 1: Cloud-Native Application Development and App Modernization in Google Cloud
5
Section 2: Selecting the Right Google Cloud Services
10
Section 3: Rehosting and Replatforming the Application
17
Section 4: Refactoring the Application on Cloud-Native/PaaS and Serverless in Google Cloud

Chapter 11: Re-Platforming the Data Layer

At this point, we have a fully working solution that addresses scalability and availability in the application layer by using a Regional Managed Instance Group and an HTTP(S) Load Balancer. In this chapter, we will be looking at the data layer in our application and seeing how we can improve our architecture to address scalability and availability while reducing the administrative overhead of managing virtual machines. The two areas in the data layer we will cover are session handling and persistent relational data. We will do this by examining the services provided by Google Cloud in this area: Cloud Memorystore for handling sessions, then Cloud SQL (with Cloud SQL Proxy), and Cloud Spanner for relational data. Finally, we will take a brief look at importing data into our relational systems.

In this chapter, we will cover the following:

  • Designing for scalability and availability
  • Using Cloud Memorystore
  • Using Cloud SQL
  • ...