Architecting Google Cloud Solutions

Victor Dantas

• Publisher: Packt Publishing
• Year: 2021
• ISBN:
  9781800564152
• Edition: 1
• Topic: Informatica
• Subtopic: Architettura di sistemi

Achieve your business goals and build highly available, scalable, and secure cloud infrastructure by designing robust and cost-effective solutions as a Google Cloud Architect.Key Features• Gain hands-on experience in designing and managing high-performance cloud solutions• Leverage Google Cloud Platform to optimize technical and business processes using cutting-edge technologies and services• Use Google Cloud Big Data, AI, and ML services to design scalable and intelligent data solutionsBook DescriptionGoogle 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.What you will learn• Get to grips with compute, storage, networking, data analytics, and pricing• Discover delivery models such as IaaS, PaaS, and SaaS• Explore the underlying technologies and economics of cloud computing• Design for scalability, business continuity, observability, and resiliency• Secure Google Cloud solutions and ensure compliance• Understand operational best practices and learn how to architect a monitoring solution• Gain insights into modern application design with Google Cloud• Leverage big data, machine learning, and AI with Google CloudWho this book is forThis book is for cloud architects who are responsible for designing and managing cloud solutions with GCP. You'll also find the book useful if you're a system engineer or enterprise architect looking to learn how to design solutions with Google Cloud. Moreover, cloud architects who already have experience with other cloud providers and are now beginning to work with Google Cloud will benefit from the book. Although an intermediate-level understanding of cloud computing and distributed apps is required, prior experience of working in the public and hybrid cloud domain is not mandatory.

Section 1: Introduction to Google Cloud

In this section, you will get an overview of cloud computing technologies and the economics of cloud computing, as well as an introduction to Google Cloud. You will learn how to make a case for Google Cloud and the essential concepts to master for a strong start.

The following chapters will be covered in this section:

• Chapter 1, An Introduction to Google Cloud for Architects
• Chapter 2, Mastering the Basics of Google Cloud

Chapter 1: An Introduction to Google Cloud for Architects

Is the "cloud” just someone else's data center? Some may see it that way, but there is much more to cloud computing than that. Cloud computing builds on infrastructure virtualization technologies to deliver services on demand, enabling not only a technological but a cultural shift in the way we work with IT systems. Furthermore, cloud computing has facilitated a new economic model for infrastructure services and has lowered the entry barrier for highly demanding applications, particularly in the areas of big data and artificial intelligence (AI), making it easier for smaller players to join the data-driven market. Foundational knowledge of cloud business and Google Cloud is a fundamental first step in a cloud architect's journey toward designing solutions with confidence using Google Cloud, so this is where we will start. In this chapter, you will learn about the enabling technologies of cloud computing and the motivations for its adoption, as well as develop a basic understanding of cloud economics and different cloud delivery models. You will then be provided with an overview of Google Cloud services and learn about some of its competitive advantages and best-of-breed technologies. Finally, you will get hands-on with Google Cloud by setting up an account, installing the SDK, and running a minor deployment.

In this chapter, we're going to cover the following main topics:

• Understanding the motivations and economics of cloud computing
• Making the business case for cloud adoption (and Google Cloud)
• Learning about Google Cloud's key differentiators – big data and AI
• Getting an overview of Google Cloud for cloud architects
• Getting started with Google Cloud Platform (GCP)

Technical requirements

Check out the following link to see the Code in Action video: https://bit.ly/3bYNoEv

Understanding the motivations and economics of cloud computing

At what point do we stop calling it just a data center, and start calling it the "cloud”? The National Institute of Standards and Technology (NIST) defines the following five essential traits that characterize cloud computing:

• On-demand, self-service
• Broad network access
• Resource pooling
• Rapid elasticity or expansion
• Measured service

The ability to deliver elastic services that can scale to adapt to varying demand, while paying only for the resources that you use, is what makes cloud computing so appealing and powerful.

The main enabling technology is that of infrastructure virtualization (or cloudification, as it is sometimes referred to), which has been made possible in the past few decades by the commoditization of hardware and new paradigms such as software-defined networking (SDN), in which the system's "intelligence” (control plane) is decoupled from the system's underlying hardware processing functions (the data plane).

These new technologies have allowed for increased levels of programmability of the infrastructure, where provisioned infrastructure resources can be abstracted and services can be exposed through application programming interfaces (APIs), in the same way that software applications' resources are. For example, with a few REST API calls, you can deploy a virtual network environment with virtual machines and public IP addresses. This has made cloud computing much more accessible to professionals working in roles beyond those of traditional enterprise IT or solution architects. It has also facilitated the emergence of the Infrastructure-as-Code (IaC) paradigm and the DevOps culture.

It has done this by enabling infrastructure resources to be defined in text-based declarative language and source-controlled in a code repository, and deployments to be streamlined via pipelines. At the time of writing, there is nothing standing between a team of developers and a complete infrastructure ready to run application workloads at any scale, except perhaps the required budget for doing so.

The NIST definition also lists four cloud deployment models:

• Private
• Community
• Public
• Hybrid

These models relate to the ownership of the hosting infrastructure. This book is about Google Cloud, which is owned and operated by Google as the cloud service provider and delivered over the internet through the public cloud model. In a public cloud, the infrastructure resources are shared between organizations (or cloud "tenants”), which means that within the same physical hosting infrastructure, several different virtualized systems from different customers may be running alongside each other. This, along with the lack of control and visibility over the underlying physical infrastructure, is one of the most criticized aspects of the public cloud model since it raises security and privacy concerns. It is the reason some organizations are reluctant to seriously consider migrating their infrastructure to the public cloud, and also the reason several others settle "somewhere in the middle” with a hybrid cloud deployment, in which only part of their infrastructure is hosted in a public cloud environment (the remaining part being privately hosted).

What makes cloud computing so disruptive and appealing, however, is not solely the new technological model that's enabled by virtualization technologies and commodity hardware, but the economic model that ensues (at least for the players in the market with deep enough pockets), which is that of economies of scale and global reach. While IT systems are generally expensive to purchase and maintain, being able to buy resources in massive quantities and build several data centers across the globe enables you to reduce and amortize those costs greatly, and then pass those savings on to your customers, who themselves can benefit from the consumption-based model and avoid large upfront investments and commitments. It's a win-win situation.

This is the shift from Capital Expenditures (CAPEX) to Operational Expenditures (OPEX) that we hear about so often, and is one of the tenets of cloud computing.

CAPEX versus OPEX

Instead of purchasing your own expensive infrastructure with a large upfront investment (the CAPEX model), you can benefit from the pay-as-you-go pricing model offered in the public cloud as a monthly consumption fee with no termination penalty (the OPEX model). Pay-as-you-go simply means you pay only for the resources you consume, while you consume them, and it's a bundled price that includes everything from any potential software licenses down to maintenance costs of the physical infrastructure running the service. This is in contrast to acquiring your own private infrastructure (or private cloud), in which case you would size it for the expected maximum demand and commit with a large upfront investment to this full available capacity, even if you only utilize a fraction of that capacity most of the time.

For organizations whose line-of-business applications have varying demands based on, for example, day of the week or time of the year (indeed, this is the case for most web-based applications today), the ability to only pay for extra resource allocation only during the few hours or days that those extra resources are needed is very beneficial financially. Resource utilization efficiency is maximized. What is even better is that such scaling events can be done automatically, and they require no on-call operations personnel to handle them.

The shift from CAPEX to OPEX also has implications on cash flow. Rather than havi...

Table of contents

• Architecting Google Cloud Solutions
• Contributors
• Preface
• Section 1: Introduction to Google Cloud
• Chapter 1: An Introduction to Google Cloud for Architects
• Chapter 2: Mastering the Basics of Google Cloud
• Section 2: Designing Great Solutions in Google Cloud
• Chapter 3: Designing the Network
• Chapter 4: Architecting Compute Infrastructure
• Chapter 5: Architecting Storage and Data Infrastructure
• Chapter 6: Configuring Services for Observability
• Chapter 7: Designing for Security and Compliance
• Section 3: Designing for the Modern Enterprise
• Chapter 8: Approaching Big Data and Data Pipelines
• Chapter 9: Jumping on the DevOps Bandwagon with Site Reliability Engineering (SRE)
• Chapter 10: Re-Architecting with Microservices
• Chapter 11: Applying Machine Learning and Artificial Intelligence
• Chapter 12: Achieving Operational Excellence
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