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Learning AWS

Learning AWS: Design, build, and deploy responsive applications using AWS Cloud components , Second Edition

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Profile Icon Sarkar Profile Icon Shah
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eBook Feb 2018 412 pages 2nd Edition
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Profile Icon Sarkar Profile Icon Shah
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€20.98 €29.99
Full star icon Full star icon Full star icon Full star icon Half star icon 4.3 (7 Ratings)
eBook Feb 2018 412 pages 2nd Edition
eBook
€20.98 €29.99
Paperback
€36.99
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Free Trial
Renews at €18.99p/m
eBook
€20.98 €29.99
Paperback
€36.99
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Renews at €18.99p/m

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Learning AWS

Cloud 101 – Understanding the Basics

In this chapter, we will introduce you to cloud computing and the key terminologies used commonly by cloud practitioners. We will briefly describe what public, private and hybrid clouds are, followed by a description of various cloud service models (offered by the service providers) including the features of Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS).

One of the main cloud-based product design elements is multi-tenancy; often considered critical from a profitability and ROI perspective. So, we will spend some time discussing, at a high level, models of multi-tenancy and their implications on design and operations.

We will also discuss some of the traditional workloads being shifted to the cloud and others being developed from the ground up, to leverage cloud services, extensively. These include shifting in-premise systems to the cloud, replacing in-premise product offerings such as ERP and CRM applications with cloud-based versions, and using a mix of in-premise and cloud-based systems. Additionally, we will look at how a large number of modern big data applications, such as recommendation engines, large-scale analytics applications, machine learning pipelines, deep learning workloads, are being targeted for cloud environment deployment only.

To help you get started on AWS, we will end the chapter by walking you through a step-by-step process of creating an AWS account and describing some of the salient features of the AWS dashboard.

This chapter will cover the following points:

  • Define cloud computing and describe some of its characteristics
  • Describe and compare public, private, and hybrid clouds
  • Explain and compare IaaS, PaaS, and SaaS cloud service delivery models
  • Explain multi-tenancy models and some challenges they present in design, implementation and operations
  • Briefly describe typical cloud-based workloads
  • Outline the steps to create an AWS account
  • A brief overview of the AWS management console

Defining cloud computing

Wikipedia defines cloud computing as:

"…internet-based computing in which large groups of remote servers are networked to allow the centralized data storage, and online access to computer services or resources."

The National Institute of Standards and Technology (NIST) gives the following definition of cloud computing:

"…a model for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction."

There are several other broadly accepted definitions of cloud computing. Some explicitly emphasize configurability of the resources, while others include the need for rapid on-demand provisioning of resources, still others drop the requirement of access via the internet. We define cloud computing as a model that enables the features listed as follows:

  • Users should be able to provision and release resources on-demand
  • The resources can be scaled up or scaled down, automatically, depending on the load
  • The provisioned resources should be accessible over a network
  • Cloud service providers should enable a pay-as-you-go model where customers are charged, based on the type and quantum of resources they consume

Some of the implications of choosing to use the cloud for your computing needs are:

  • The illusion of infinite processing and storage resources available on demand reduce the need for detailed advance planning and procurement processes.
  • The model promotes the use of resources as per customer needs, for example, starting small, and then increasing resources based on an increase in need.
  • Provisioning development and test environments on a smaller scale, and enabling them only during working hours to reduce the cost of development.
  • The staging environment can be provisioned for a short duration to be a replica of the production environment. This enables testing using production configuration (and scale) and for improved production defect resolution.
  • The ability to auto scale in order to better manage spikes in demand and variations due to business cycles or time-of-day reasons, and so on.
  • It encourages experimentation by trying out new ideas and software by quickly provisioning resources rather than requisition for resources through time consuming and cumbersome processes.

These and other implications of using cloud services to design scalable, highly available and secure applications are discussed in depth in the subsequent chapters.

Introducing public, private, and hybrid clouds

Basically, there are three types of clouds in cloud computing, they are public, private and hybrid clouds.

In a public cloud, third-party service providers make resources and services available to their customers via the internet. The customers' applications and data are deployed on infrastructure that is owned and secured by the service provider.

A private cloud provides many of the same benefits of a public cloud but the services and data are managed by the organization, or a third-party, solely, for the customer's organization. Usually, a private cloud places increased administrative overheads on the customer but gives greater control over the infrastructure and reduces security-related concerns. The infrastructure may be located on or off the organization’s premises.

A hybrid cloud is a combination of both a private and a public cloud. The decision on what runs on the private versus the public cloud is usually based on business criticality of the application and sensitivity of the data. But in some cases, spikes in demand for resources, or spillovers, in the private cloud are also handled in the public cloud.

Introducing cloud service models – IaaS, PaaS, and SaaS

There are three cloud-based service models. The main features of each of these are listed as follows:

  • IaaS provides a capability for users to provision processing, storage, and network resources on demand. The customers deploy and run their own applications on these resources. Using this service model is closest to the traditional in-premise models but without the lengthy procurement processes. The onus of administering these resources rests, largely, with the customer.
  • In PaaS, the service provider makes certain core components such as databases, queues, workflow engines, email, and so on, available as services to the customer. The customer then leverages these components for building their own applications. The service provider ensures high service levels, and is responsible for scalability, high availability, and so on, for these components. This allows customers to focus a lot more on their application functionality. However, this model also leads to application-level dependency on the providers' services.
  • In the SaaS model, typically, third-party providers using a subscription model provide end user applications to their customers. The customers may have some administrative capability at the application level, for example, to create and manage their users. Such applications also provide some degree of customizability, for example, the customers can use their own corporate logos, colors, and so on. Applications that have a very wide user base most often operate in a self-service mode. In contrast, the provider provisions the infrastructure and the application for the customer for more specialized applications. The provider also hands over the management of the application to the customer's application administrator (in most cases this is limited to user management tasks).

From an infrastructure perspective, the customer does not manage or control the underlying cloud infrastructure in all three service models.

The following figure illustrates who is responsible for managing the various components of a typical user application across IaaS, PaaS, and SaaS cloud service models. The shaded boxes represent the service-providers' responsibilities, while the other boxes represent the users' or end customers' responsibilities.

The level of control the user has over operating systems, storage, applications, and certain network components (for example, load balancers) is the highest in the IaaS model while the least (or none) in the SaaS model.

Introducing multi-tenancy models

Multi-tenancy and multi-tenant architecture come up, repeatedly, especially in the context of cloud product design and architecture discussions. Given that most SaaS products are offered as a subscription, it is vital to understand this concept clearly as it can often be the difference between having a highly profitable and an easy-to-manage product, and a failed product or venture.

Multi-tenancy is a principle in software architecture where a single instance of the software serves multiple tenants or customers. The realization of this concept in software design is probably one of more complex tasks in implementing and operating a cloud-based product.

Let's start by examining three basic models of a multi-tenant application. The following figure illustrates these models:

In the first model, (A) Shared Nothing architecture, each customer has a separate copy of the application and the database for their exclusive use. In some cases, the hardware infrastructure is also separated out for each customer. Large enterprises may insist on this separation mainly due to security concerns but also due to service-level concerns associated with resource sharing. This is essentially application hosting rather than application multi-tenancy.

The second model, (B) Shared Application architecture, shares the same application instance but the data is separated for each customer. And in the third model, (C) Shared Everything architecture, both the application and the database instances are shared resources among all the customers.

In real life, it is fairly common for customers to request a dedicated application and infrastructure stack. Most smaller companies and start-ups give in under pressure, especially if it is a major customer. However, this can be a very expensive option to sustain over a period of time. Before you know it, you are maintaining several different versions of the application and technology stacks, multiple database schema, operational and support-related overheads across a set of customers. This makes application maintenance, QA/testing effort, upgrades/releases, and customer support impossibly complex or expensive or both. You are no longer an SaaS application provider!

It is very common and reasonable to expect a majority of customers to request that their data be kept separated from other customers. It is also common for smaller businesses and price-sensitive customers to not care how and where you store their data, as long as they are satisfied by the security measures you have implemented. In all cases, it is imperative to use encryption for the securing of sensitive data-at-rest.

Hence, in reality you end up with a mix of models where the concern is more focused on data security rather than shared infrastructure or application code (as long as you can provide a certain level of application customizability per customer and meet their service-level requirements).

In this scenario, apart from security considerations (discussed in a later chapter) some of the challenges that arise are listed as follows:

  • Increased costs of development: Isolating each customer's data in a separate database is easier and faster to build, while using a shared approach requires a larger development effort and initial costs, but can result in being able to serve more tenants per server at a lower overall operational cost.
  • Isolating each tenant's database can give you more flexibility in handling each customer's individual requirements (but there could be severe complications when you release product upgrades, especially if your database schema is not designed to handle such changes).
  • Regulatory considerations can directly impact your design and leave you with no choice in terms of using a shared approach.
  • Backups and restores are simpler operations in the case of isolated databases. In the shared database approach, the impact of servicing a particular tenant's backup or restore request will impact other active customers. These kinds of issues can lead to SLA-related issues and other management overheads related to explaining and issuing appropriate communications to all other customers, and so on.

Normally, businesses charge their customers differently based on whether a customer requests a separate database instance, or a fully segregated infrastructure for their exclusive use only. Suppose you have grouped your customers into three categories such as Platinum, Gold, and Silver. Your Platinum class customers are your biggest and the best. They are willing to pay a premium for additional features and/or better service levels. Let's say, you decide to provision separate infrastructure and database instances, for such customers. Simultaneously, you decide to share the infrastructure and use a single database instance for all your regular, or Silver class, customers. Imagine the operational complexity of a situation where one of your Platinum class customers (Shared Nothing) wants to downgrade their subscription level to the Silver class (Shared Everything) the following year!

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Key benefits

  • • Get well-versed with building and deploying serverless APIs with microservices
  • • Learn to build distributed applications and microservices with AWS Step Functions
  • • A step-by-step guide that will get you up and running with building and managing applications on the AWS platform

Description

Amazon Web Services (AWS) is the most popular and widely-used cloud platform. Administering and deploying application on AWS makes the applications resilient and robust. The main focus of the book is to cover the basic concepts of cloud-based development followed by running solutions in AWS Cloud, which will help the solutions run at scale. This book not only guides you through the trade-offs and ideas behind efficient cloud applications, but is a comprehensive guide to getting the most out of AWS. In the first section, you will begin by looking at the key concepts of AWS, setting up your AWS account, and operating it. This guide also covers cloud service models, which will help you build highly scalable and secure applications on the AWS platform. We will then dive deep into concepts of cloud computing with S3 storage, RDS and EC2. Next, this book will walk you through VPC, building real-time serverless environments, and deploying serverless APIs with microservices. Finally, this book will teach you to monitor your applications, automate your infrastructure, and deploy with CloudFormation. By the end of this book, you will be well-versed with the various services that AWS provides and will be able to leverage AWS infrastructure to accelerate the development process.

Who is this book for?

If you are an I.T. professional or a system architect who wants to improve infrastructure using AWS, then this book is for you. It is also for programmers who are new to AWS and want to build highly efficient, scalable applications.

What you will learn

  • • Set up your AWS account and get started with the basic concepts of AWS
  • • Learn about AWS terminology and identity access management
  • • Acquaint yourself with important elements of the cloud with features such as computing, ELB, and VPC
  • • Back up your database and ensure high availability by having an understanding of database-related services in the AWS cloud
  • • Integrate AWS services with your application to meet and exceed non-functional requirements
  • • Create and automate infrastructure to design cost-effective, highly available applications

Product Details

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Publication date : Feb 01, 2018
Length: 412 pages
Edition : 2nd
Language : English
ISBN-13 : 9781787289314
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Product Details

Publication date : Feb 01, 2018
Length: 412 pages
Edition : 2nd
Language : English
ISBN-13 : 9781787289314
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Table of Contents

11 Chapters
Cloud 101 – Understanding the Basics Chevron down icon Chevron up icon
Designing Cloud Applications Chevron down icon Chevron up icon
Introducing AWS Components Chevron down icon Chevron up icon
Designing for and Implementing Scalability Chevron down icon Chevron up icon
Designing for and Implementing High Availability Chevron down icon Chevron up icon
Designing for and Implementing Security Chevron down icon Chevron up icon
Deploying to Production and Going Live Chevron down icon Chevron up icon
Designing a Big Data Application Chevron down icon Chevron up icon
Implementing a Big Data Application Chevron down icon Chevron up icon
Deploying a Big Data System Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon

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Sarat Chandra Dash May 09, 2019
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Good one
Amazon Verified review Amazon
Alexey Apr 01, 2019
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One of the worst technical books I have ever purchased. It's lacking depth and feels like a series of very brief blog posts barely scratching the surface.
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Rainbow5 Feb 10, 2019
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Helpful introduction to AWS
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manish sharma Dec 10, 2018
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Nice simple and clear
Amazon Verified review Amazon
Ian Stirk Oct 17, 2018
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ConclusionLearning AWS, Second Edition aims to introduce Amazon Web Services to architects, and tentatively succeeds. On the upside, it has useful explanations, helpful diagrams, instructive step-by-step walkthroughs, and lots of real-world practical advice. The downside is the book is not for beginners, it assumes you’re an experienced software architect, familiar with the various patterns and approaches.I wonder if it would have been better to expand the existing chapters for the beginner – perhaps this could have been done instead of including the final three chapters on designing, implementing, and deploying a Big Data application. Owing to the prevalence of acronyms, a glossary would be useful.The book competes with various free offerings from Amazon itself. That said, it is useful to see the evolution of an AWS application from start to end.I suspect in the near future, especially if privacy concerns abate, the cloud will become the default platform for software applications. As a personal insight into the advantages of using the cloud, I often work in financial environments, where the lead time for getting a new on-premise server can be 3 to 6 months - with a cloud-based offering the server can be available within minutes. Other advantages (e.g. cost-saving, on-demand scalability), are similarly convincing.Overall, if you’re an existing architect wanting to learn about AWS, this is a very good book. Otherwise it is limited.
Amazon Verified review Amazon
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