The Definitive Guide to Modernizing Applications on Google Cloud: The what, why, and how of application modernization on Google Cloud

BIRMINGHAM—MUMBAI

The Definitive Guide to Modernizing Applications on Google Cloud

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To the memory of my father, Ishwar, and my mother, Savithri, for their sacrifices and exemplifying that hard work has positive outcomes. To my wife, Sanju, for being my loving and supportive partner, and to my children, Riya and Risha, for keeping us on our toes.

– Steve (Satish) Sangapu

To my parents, who have encouraged me in writing this book, with their push for tenacity ringing in my ears.

– Dheeraj Panyam

Contributors

About the authors

Steve (Satish) Sangapu has been working with software since 2000. He specializes in migrating and modernizing applications from monoliths to containerized microservices as well as creating data engineering pipelines to mine vast amounts of structured and unstructured data.

He has extensive experience successfully leading large, cross-functional, geographically dispersed teams utilizing modern Agile development methodologies while collaborating effectively with product teams in creating high-performance, fault-tolerant, and high-availability systems.

He also holds seven patents from the United States Patent and Trademark Office and certifications from Carnegie Mellon Software Engineering Institute and Google Cloud.

I want to thank the people who have given me and the people around me love and support in different ways in my life.

Dheeraj Panyam has been working in the IT industry since 2000. His experience spans diverse domains (optical, telecom, retail, and healthcare) and covers all phases of the SDLC, including application development, production support, QA automation, and cloud architecture. He lives in India and collaborates with a Google Cloud consulting company, helping them design solutions and architecture set up on public cloud platforms.

He holds multiple Google Cloud certifications in addition to other certifications in networking and testing.(in new line)

Jason Marston is a Cloud Solution Architect based in England. He was recruited by Microsoft because of his OSS background. Jason has worked with Java since version 1 and has a long history with open source. He has over 30 years' of experience in developing software and now helps organizations migrate and modernize legacy applications to the cloud. Jason was an SME in the Worldwide Communities project at Microsoft and, as a part of the leadership team for those communities, helped many people solve their problems by adopting Java on Azure. In his spare time, Jason reads science fiction books and has two children who think he is a geek/nerd.

About the reviewer

Radhakrishnan (Krishna) Gopal is a cloud evangelist, seasoned technology professional, and mentor with over 22 years of industry experience in all major cloud hyperscalers, including AWS, Azure, and Google Cloud. He is currently helping organizations to drive business value through cloud adoption and innovation. He has worked in many facets of IT throughout his career and delivered high-quality, mission-critical, and innovative technology solutions leveraging multi-cloud, data, AI, and intelligent automation. He is a Google Cloud Certified Professional Cloud Architect, Google data engineer, Azure certified solutions architect expert, Azure data engineer, data science associate, AI engineer, and AWS Certified Solutions Architect Associate. He loves to explore new frontiers of technology and impart them in solutions to make his clients very successful.

Table of Contents

Preface

Section 1: Cloud-Native Application Development and App Modernization in Google Cloud

Chapter 1: Cloud-Native Application Fundamentals

The cloud-native ecosystem

Benefits of cloud-native applications

Increased speed of delivery

Increased scalability

Increased resiliency

Mixed technology stack and workforce

Continuous integration and delivery

Increased automation

Principles of cloud-native architecture

Principle 1 – lightweight microservices

Principle 2 – leveraging automation

Principle 3 – DevOps culture

Principle 4 – better to go managed

Principle 5 – innovate

Limitations of microservices

Applying the 12-factor app principles on Google Cloud

Code base

Dependencies

Config

Backing services

Build, release, run

Processes

Port binding

Concurrency

Disposability

Dev/prod parity

Logs

Admin processes

Summary

Chapter 2: End-to-End Extensible Tooling for Cloud-Native Application Development

Moving past third-party services – the beauty of end-to-end tooling

Google Cloud Code

Features and benefits of Cloud Code

The role of Cloud Code in the cloud-native app development pipeline

Google Cloud Build

Features and benefits of Cloud Build

The role of Cloud Build in the cloud-native app development pipeline

Google Container Registry

Features and benefits of GCR

The next-gen container registry – Artifact Registry

The role of GCR in the cloud-native app development pipeline

Google Cloud Run

Features and benefits of Cloud Run

The role of Google Cloud Run in the cloud-native app development pipeline

Google Kubernetes Engine

Features and benefits of GKE

The role of GKE in the cloud-native app development pipeline

Operations suite

Features of Google Cloud Monitoring

Features of Google Cloud Logging

The role of the Cloud operations suite in the cloud-native app development pipeline

Summary

Chapter 3: Cloud-Native Architecture Patterns and System Architecture Tenets

Cloud-native patterns

The scope of cloud-native patterns

Solving challenges with cloud-native patterns

Be proactive, not reactive

Scaling and performance

Deployments

Resiliency and availability

Monitoring

Security

Cloud-native design patterns

Microservices

Strangler applications

Decomposition patterns

Event-driven patterns

Command Query Responsibility Segregation

The saga pattern

Multiple service instances

Canary deployments

Stateless services

Immutable infrastructure

Anti-corruption layer

API composition

Event sourcing

The Retry pattern

Circuit breaker pattern

The bulkhead pattern

Using the cloud-native pattern judiciously

Hybrid and multi-cloud architecture recommendations

Distributed deployment patterns

Redundant deployment patterns

Summary

Section 2: Selecting the Right Google Cloud Services

Chapter 4: Choosing the Right Compute Option

Five compute options… and Firebase

Firebase

Cloud Functions

GAE

Cloud Run

GKE

GCE

Pricing

How important is it to choose the right option?

Changing compute options

Making a decision

Summary

Chapter 5: Choosing the Right Database and Storage

Storage and database options on Google Cloud – the big three

GCS – basics

GCS

Cloud SQL

Cloud Firestore (previously Datastore)

Cloud Spanner

Cloud Bigtable

Wrapping up the big five

Additional storage and database options

BigQuery

Filestore

Persistent disks/local solid-state drive (SSD) (block storage)

MemoryStore

Security and flexibility

Summary

Chapter 6: Implementing a Messaging and Scheduling System

Understanding the requirements of a messaging system

Requirement #1: Scalability

Requirement #2: Extensibility

Requirement #3: Agility

Requirement #4: Resiliency

Introduction to asynchronous messaging

Messaging products available (open source and cloud native) on the market

Amazon SQS

Kafka

RabbitMQ

NATS Streaming

Advantages of asynchronous messaging

Introduction to Pub/Sub

What is Cloud Pub/Sub?

Pub/Sub key features

Additional benefits

Pub/Sub Concepts – topics and subscriptions

Pub/Sub model – fan-in and fan-out

Pull versus push types – differences and when to use each type

Getting started with Cloud Pub/Sub

Introduction to Cloud Tasks

Introduction to Cloud Scheduler

Summary

Chapter 7: Implementing Cloud-Native Security

The principles and concepts of cloud security

Economy of Mechanism

Defense in Depth

Principle of Least Privilege

Adding infrastructure security layers (revision)

Cloud IAM

Traditional access control versus Cloud IAM

Concepts of IAM

Entity

Identity

Permissions

Policy

Authentication and authorization

Cloud IAM on Google Cloud Platform

Features of Cloud IAM

Components of Cloud IAM

Members

All authenticated users

All users

Resources

Permissions

Roles

IAM policy bindings

Limitations of Cloud IAM

Cloud Identity

Features of Cloud Identity

Setting up Cloud Identity

Cloud Identity Platform

Features of Cloud Identity Platform

BeyondCorp (a new approach to enterprise security)

Cloud Identity-Aware Proxy (IAP)

Summary

Section 3: Rehosting and Replatforming the Application

Chapter 8: Introducing the Legacy Application

Technical requirements

The infrastructure architecture

The software architecture

Spring Boot

Thymeleaf

Bootstrap

jQuery

Explaining the software architecture

Implementing the software

Spring Boot configuration

Understanding the layers of the application

The presentation layer

The controller layer

The domain layer

Validation and defensive programming

Summary

Chapter 9: The Initial Architecture on Google Compute Engine

Technical requirements

The initial infrastructure design

Designing our network

Designing our network security

Creating the modernization project

Implementing the network

Implementing the VMs

Importing the data

Summary

Chapter 10: Addressing Scalability and Availability

Technical Requirements

Designing for scalability and availability

Using instance templates

Using managed instance groups

Using an HTTP(S) load balancer

Summary

Chapter 11: Re-Platforming the Data Layer

Designing for scalability and availability

Using Cloud Memorystore

Provisioning a Cloud Memorystore instance

Updating the Regional Managed Instance Group

Using Cloud SQL

Using Cloud SQL Proxy

Using Cloud Spanner

Provisioning Cloud Spanner

Updating the build

Updating the application settings

Importing data into Cloud SQL

Exporting data from our MySQL virtual machine

Importing to Cloud SQL

Cloud SQL versus Cloud Spanner

Summary

Chapter 12: Designing the Interim Architecture

The infrastructure architecture

Google Identity Platform

Cloud Pub/Sub

The software architecture

Refactoring the frontend and exposing REST services

Adding Google Identity Platform for identity and authentication

Publishing events

Consuming events

Refactoring to microservices

Microservice boundaries

Summary

Chapter 13: Refactoring to Microservices

Technical requirements

Analyzing the structure of the application backend

Refactoring into microservices

Refactoring the database

The web frontend

The Strangler Pattern revisited

Google HTTP(S) Load Balancer Routing

Google App Engine Dispatcher

Apigee API Manager

Containerizing the deployment units with Docker

Summary

Section 4: Refactoring the Application on Cloud-Native/PaaS and Serverless in Google Cloud

Chapter 14: Refactoring the Frontend and Exposing REST Services

Technical requirements

Creating REST controllers

Creating an AngularJS web frontend

Modules

Components

Routing

Services

Authenticating in the web frontend

Setting up Firebase and Google Identity Platform

Initializing Firebase Authentication

Router updates

The authentication cycle

The signout controller

Validating the authentication token in the REST controllers

The authentication filter

Summary

Chapter 15: Handling Eventual Consistency with the Compensation Pattern

Technical requirements

The distributed transaction problem

The compensation pattern

Creating topics and subscriptions with Google Cloud Pub/Sub

Implementing eventual consistency and the compensation pattern

Deploying and testing the application

Summary

Chapter 16: Orchestrating Your Application with Google Kubernetes Engine

Technical requirements

Introducing GKE

Modes of operation

Creating a GKE cluster

Configuring the environment

Kubernetes ConfigMaps and Secrets

Deploying and configuring the microservices

Kubernetes Pods

Kubernetes ReplicaSets

Kubernetes Deployments

Kubernetes Horizontal Pod Autoscalers

Kubernetes Services

Automating the deployment of our components

Configuring public access to the application

Kubernetes-managed certificates

Kubernetes Ingress

When to use GKE

Summary

Chapter 17: Going Serverless with Google App Engine

Technical requirements

Introducing Google App Engine

Google App Engine standard environment

Google App Engine flexible environment

Components of App Engine and the hierarchy of an application deployed on App Engine

Deploying containers to the App Engine flexible environment

Application configuration updates

Deployment configuration

Automating deployment

When to use Google App Engine

Summary

Chapter 18: Future Proofing Your App with Google Cloud Run

Technical requirements

Cloud Run

The Knative stack

Cloud Run environments

Deploying containers to Google Cloud Run

Frontend configuration

Service manifest

Google Cloud Build

Domain name mapping

When to use Cloud Run

Summary

Appendix A: Choosing the Right Migration Strategy

Step 1 – assess

Cataloging existing applications

Educating teams

Choosing what to migrate first

Capable and innovative teams

The effort required for migration

License restrictions and compliance

Can afford downtime

Step 2 – plan

Migration paths versus migration strategies

Choosing the right migration path

Step 3 – migrate

Transferring your data

Deploying workloads

Setting up automated and containerized deployments

Step 4 – optimize

Letting internal teams takeover

Setting up monitoring

Leveraging managed services and automation

Cost and performance

Appendix B: Application Modernization Solutions

Modernizing Java apps

What is Google Anthos?

Preparing to modernize Java apps

Phase 1 – containerizing Java applications

Phase 2 – Refactoring and re-platforming

Modernization strategies (the 6 Rs of modernization)

Retire, retain, and re-architect

Other Books You May Enjoy

Preface

75-80% of enterprise applications are legacy and stuck in the data center. How do we modernize these applications to transform them into modern cloud-native applications so that they can scale in a cloud environment without taking months or years to see the benefits?

This book introduces the services available on Google Cloud and showcases the steps involved in modernizing an example Java Spring Boot application from legacy status to the cloud by replatforming and rehosting with target deployments on IaaS, PaaS, and serverless options available on Google Cloud.

Who this book is for

Software developers and solution architects seeking to gain experience in how to modernize their applications, moving them to Google Cloud and transforming them into cloud-native applications, will benefit from this book.

What this book covers

Chapter 1, Cloud-Native Application Fundamentals, introduces the characteristics of cloud-native applications, including their benefits, along with the ever-popular Twelve-Factor App principles.

Chapter 2, End-to-End Extensible Tooling for Cloud-Native Application Development, introduces the development toolset and services available on Google Cloud to aid in building a modern cloud-native application.

Chapter 3, Cloud-Native Architecture Patterns and System Architecture Tenets, explains the different design patterns and best practices to address specific development challenges, client needs, and platform requirements.

Chapter 4, Choosing the Right Compute Option, introduces the various compute options available on Google Cloud from IaaS, PaaS, and containers to serverless options.

Chapter 5, Choosing the Right Database and Storage, introduces the various database and storage services available on Google Cloud.

Chapter 6, Implementing a Messaging and Scheduling System, explains the need for a messaging system for cloud-native applications, introducing the Pub/Sub service in Google Cloud and comparing it to other open source options.

Chapter 7, Implementing Cloud-Native Security, introduces identity and access management and how it can be used to secure applications deployed on Google Cloud.

Chapter 8, Introducing the Legacy Application, introduces the monolithic Java Spring Boot application along with the frontend and backend components that we will modernize at a later stage.

Chapter 9, The Initial Architecture on Google Compute Engine, explains how the sample legacy application can be rehosted on Google Compute Engine virtual machines.

Chapter 10, Addressing Scalability and Availability, addresses the scalability of the legacy application by utilizing Managed Instance Groups (MIG), which is a collection of Google Compute Engine virtual machines.

Chapter 11, Re-platforming the Data Layer, showcases how to move the backend database from a self-hosted option on Google Compute Engine to a managed service on Google Cloud.

Chapter 12, Designing the Interim Architecture, focuses on understanding how infrastructure and software architecture needs to be changed to prepare for the move to microservices.

Chapter 13, Refactoring to Microservices, explains how we can package our application into separate microservices for the frontend and backend.

Chapter 14, Refactoring the Frontend and Exposing REST Services, explains how to break our monolithic legacy application into microservices for the frontend along with the backend REST APIs.

Chapter 15, Handling Eventual Consistency with the Compensation Pattern, explains how our legacy application can be designed to handle eventual consistency to allow loose coupling between the microservices.

Chapter 16, Orchestrating Your Application with Google Kubernetes Engine, explains the deployment of our legacy application to Google Kubernetes Engine. Now that we have all the individual microservices, we are ready to deploy to containerized platforms.

Chapter 17, Going Serverless with Google App Engine, explains how to deploy our containerized legacy application to Google App Engine.

Chapter 18, Future-Proofing Your App with Google Cloud Run, explains how to deploy our legacy application to Google Cloud Run, which is Google's latest serverless offering.

Appendix A, Choosing the Right Migration Strategy, explains the various migration options available when moving to Google Cloud.

Appendix B, Application Modernization Solutions, introduces Anthos, an application modernization platform.

To get the most out of this book

You will need to install the Google Cloud SDK that contains the gcloud CLI. You will also require familiarity with the Java Spring Boot framework and working knowledge of CLIs in general and the gcloud CLI specifically. You will need to have knowledge of basic DNS concepts such as setting up A records and CNAME records and understanding domains and sub-domains. Experience of working with domain registrars would be helpful. Familiarity with working YAML syntax will be useful to understand CloudBuild configuration files

In addition, if you want to set up a custom domain for your application as mentioned in the chapters that refer to deployments on GCE, GAE, GKE, and Cloud Run, you will need to purchase a DNS domain from a domain registrar. App Engine and Cloud Run, however, come with predefined URLs provided by Google Cloud in case you do not want a custom domain.

If you are using the digital version of this book, we advise you to type the code yourself or access the code via the GitHub repository (link available in the next section). Doing so will help you avoid any potential errors related to the copying and pasting of code.

After reading the book, you should have a fair understanding of applying the right architecture pattern for your use case to transform a legacy application into a modern cloud-native application, and then use advanced application modernization technologies such as Anthos to create containerized applications that run on Kubernetes.

Download the example code files

You can download the example code files for this book from GitHub at https://github.com/PacktPublishing/Modernizing-Applications-with-Google-Cloud-Platform. In case there's an update to the code, it will be updated on the existing GitHub repository.

We also have other code bundles from our rich catalog of books and videos available at https://github.com/PacktPublishing/. Check them out!

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layout (content)

xmlns:th=http://www.thymeleaf.org

xmlns:sec=https://www.thymeleaf.org/thymeleaf-extras-springsecurity3>

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Bold: Indicates a new term, an important word, or words that you see onscreen. For example, words in menus or dialog boxes appear in the text like this. Here is an example: From the Instances page, click CREATE INSTANCE.

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Section 1: Cloud-Native Application Development and App Modernization in Google Cloud

On completion of Section 1, you will have gained an understanding of the cloud-native ecosystem, principles and benefits of cloud-native architecture as well as how to apply the 12-factor app principles on Google Cloud. In addition, you will get insights into the end-to-end tooling that goes into developing a cloud-native application on Google Cloud, along with a sample reference architecture. Finally, you will learn how to solve common challenges with cloud-native design patterns as well as hybrid and multi-cloud architecture recommendations.

This part of the book comprises the following chapters:

Chapter 1, Cloud-Native Application Fundamentals

Chapter 2, End-to-End Extensible Tooling for Cloud-Native Application Development

Chapter 3, Cloud-Native Architecture Patterns and System Architecture Tenets

Chapter 1: Cloud-Native Application Fundamentals

Cloud computing brought about a paradigm shift in the world of software engineering and changed how we build applications. The cloud ecosystem powers some of the most powerful, largest, and most innovative applications using the same set of universal principles. However, some of these principles go against the best practices in traditional application development but are crucial to the success of a cloud-native application.

In this chapter, we are going to explore these fundamentals and core principles to help you utilize the full potential of the cloud-native ecosystem. After finishing this chapter, you'll have a clear understanding of the following topics and how they are used in day-to-day development on the cloud:

The cloud-native ecosystem

Benefits of cloud-native architecture

Principles of cloud-native architecture

Applying the 12-factor app principles on Google Cloud

The cloud-native ecosystem

The cloud-native ecosystem is a combination of three very basic elements: the cloud platform, the architecture, and, of course, the cloud-native application. Let's break them down one by one.

The cloud platform is what makes cloud-native applications possible. For instance, the virtually unlimited computing and storage capabilities of a cloud platform give cloud-native applications the following characteristics:

Scalability, a defining characteristic.

The pay-per-use model makes the applications cost-effective.

Managed services that make cloud-native applications not only versatile but also very developer-friendly.

There are ample reasons why the industry is choosing cloud-native architecture as the foundation for its applications. The architecture dictates how the software is engineered and with cloud-native architecture, developers have far more control. It enables developers to adopt DevOps, containers, automation, microservices, and more. Microservices, in particular, are one of the most important components of a cloud-native architecture and they are what give cloud-native applications the rest of their defining characteristics: agility and resiliency.

An application can be considered cloud-native when it can take advantage of the cloud platform, and in order to take full advantage, it usually needs to be built on a cloud-native architecture. Therefore, a cloud-native application should be the following:

Managed: Use the cloud platform as an infrastructure (be dependent on it to do all the computing).

Scalable: Quickly increase or decrease resources to match the demand.

Resilient: A single bug or crash should not take down the application.

Loosely coupled: Parts of the application should be isolated enough for them to be altered or removed without any downtime.

If the cloud-native ecosystem were a house, the cloud platform would be the underground foundation, the architecture would be the main pillars, and the cloud applications would be the rooms.

Benefits of cloud-native applications

Cloud-native applications have many benefits that make them superior to traditional applications in many ways. These benefits are why people build cloud-native applications, but not all the benefits are innate; they're not guaranteed automatically.

Simply rehosting to a cloud platform does not mean that the time to market will decrease or that the application will be more resilient. It's up to the developer to ensure that the characteristics of the cloud platform and architecture are carried over to the end user. So, before learning how to develop cloud-native applications, it's a good idea to learn what makes cloud-native applications so powerful and popular among businesses.

Increased speed of delivery

Simply building applications isn't enough – delivering the service to the market is just as important. Bringing a new service or product to the market before competitors has a huge advantage (first-mover advantage). Similarly, timely feature updates and bug fixes are incredibly important as well.

Cloud-native applications can be built in a very short time and are generally much faster at pushing updates as well. This is possible due to the way they are architected as well as because of the approach developers take. Let's take a look at some of the architectural benefits first.

Not monolithic

A decade ago, the trend was to make everything monolithic. Today, the trend is to break the monolith into microservices. This paradigm shift was driven by the need to be more agile and resilient and monoliths were neither. The solution? Use a loosely coupled architecture that is not affected by the limitations of monolithic architecture.

Unlike a monolith, the cloud-native architecture supports an application being built in pieces and then joined together. These pieces are called microservices and they are completely isolated from each other in their own environments called containers. They communicate with each other through APIs. The popular saying breaking the monolith refers to breaking down the web of a complex and interconnected code base into neatly organized microservices that are much easier to maintain.

A popular real-world example of breaking the monolith is Netflix. By the time it turned 1 in 2008, Netflix's monolithic architecture had already become a problematic mess that caused extremely long downtimes. So, after 3 years of refactoring, Netflix's engineers were able to break down their giant monolith into 500-700 microservices, reducing cost, time to market, and downtimes.

A microservices architecture also reduces the time to fix bugs as each microservice is monitored separately and buggy microservices can be quickly identified, replaced with an older version, or completely removed without any downtime.

Independent development of microservices

Another major advantage of microservices is that because they are independent, developers can work on different microservices at once. This gives developers the ability to build and update different parts of the application at once, without constantly worrying about app-breaking updates or having to shut down the entire server for a small bug fix. Although compatibility issues haven't been completely eliminated in cloud-native applications, they are far fewer and rarer.

Amazon's two pizza policy is a great example of the independent development of microservices. The policy states that a microservice is too big if the team working on it cannot be fed by two pizzas. Although not very scientific, it illustrates just how great microservices are for small, especially remote, teams.

Independent deployment of microservices

The loosely coupled design philosophy has given rise to a new breed of applications that are modular. As microservices are usually designed with functionality in mind, they can be thought of as modular features that can be changed, replaced, or completely taken out with minimum impact on the entire application. But they can also be introduced independently. When adding a new microservice to the main code base, no major refactoring is required, which significantly reduces the time to market.

Increased scalability

Scalability is one of the key characteristics of cloud-native applications. They are extremely scalable due to the vast (unlimited as far as most businesses are concerned) hardware capabilities of modern cloud platforms. However, cloud-native applications are not scalable in the same way as traditional applications.

Historically, businesses increased their capacity to serve concurrent users by vertically scaling or scaling up. This means that they went from 2 gigabytes of memory to 8 gigabytes and from a 1 GHz CPU to a 2.4 GHz one.

Cloud-native applications, on the other hand, scale up using a different approach: horizontal scaling or scaling out. Instead of increasing the raw computing and storage capabilities of each unit, cloud platforms increase the number of units. Instead of a single stick of 8 gigabytes, they have four sticks of 2 gigabytes.

Although vertical scaling is easier, horizontal scaling opens up far more possibilities in terms of how resources are allocated and how applications scale with the latter, providing much better scalability.

Additionally, cloud platforms provide a number of scalability benefits such as autoscaling and pay-per-use pricing schemes that make cloud-native applications much better investments.

Increased resiliency

Risks can never be completely eliminated, so instead of solely focusing on avoiding failures, cloud-native applications are architected to respond to failures – that is, to be resilient. The resiliency of