Foundations of Scalable Systems

230 Pages·2022·1.993 MB·English

by  Ian Gorton

Foundations of Scalable
Systems
Designing Distributed Architectures
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Ian Gorton
Foundations of Scalable Systems
by Ian Gorton
Copyright © Ian Gorton. All rights reserved.
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August 2022: First Edition
Revision History for the Early Release
2021-05-10: First Release
2021-06-22: Second Release
2021-09-08: Third Release
2021-10-04: Fourth Release
2021-11-19: Fifth Release
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Preface
A NOTE FOR EARLY RELEASE READERS
With Early Release ebooks, you get books in their earliest form—the
author’s raw and unedited content as they write—so you can take
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If you have comments about how we might improve the content and/or
examples in this book, or if you notice missing material within this
chapter, please reach out to the editor at [email protected].
This book is built around the thesis that the ability of software systems to
operate at scale is increasingly a driving system quality. As our world
becomes more interconnected, this characteristic will only accelerate.
Hence the goal of the book is to provide the reader with the core knowledge
of distributed and concurrent systems. It will also introduce a collection of
software architecture approaches and distributed technologies that can be
used to build scalable systems.
Why Scalability?
The pace of change in our world is daunting. Innovations appear daily,
creating new capabilities for us all to interact with, conduct business, be
entertained, end pandemics. The fuel for much of this innovation is
software, written by veritable armies of developers in major internet
companies, crack small teams in startups, and all shapes and sizes of teams
in between.
Delivering software systems that are responsive to user needs is difficult
enough, but it becomes an order of magnitude more difficult to do for
systems at scale. We all know of systems that fail suddenly when exposed
to unexpected high loads - such situations are minimally bad publicity for
organizations, and at worst can lose jobs and destroy companies.
Software is unlike physical systems in that it’s amorphous—its physical
form (1’s and 0’s) bears no resemblance to its actual capabilities. We’d
never expect to transform a small village of 500 people into a city of 10
million overnight. But we sometimes expect our software systems to
suddenly handle 1000x the number of requests they were designed for. Not
surprisingly, the outcomes are rarely pretty.
Who This Book Is For
The major target audience for this book is software engineers and architects
who have no or limited experience with distributed, concurrent systems.
They need to deepen both their theoretical and practical design knowledge
in order to meet the challenges of building larger scale, typically Internet-
facing applications.
Much of the content of this book has been developed in the context of an
advanced undergraduate/graduate course at Northeastern University. It has
proven a very popular and effective approach for equipping students with
the knowledge and skills needed to launch their careers with major Internet
companies. Additional materials on the book web site are available to
support educators who wish to use the book for their course.
What You Will Learn
This book covers the landscape of concurrent and distributed systems
through the lens of scalability. While it’s impossible to totally divorce
scalability from other architectural qualities, scalability is the main focus of
discussion. Of course, other qualities necessarily come in to play, with
performance, availability and consistency regularly raising their heads.
Building distributed systems requires some fundamental understanding of
distribution and concurrency - this knowledge is a recurrent theme
throughout this book. It’s needed because at their core, there are two
problems in distributed systems that make them complex, as I describe
below.
First, although systems operate perfectly correctly nearly all the time, an
individual part of the system may fail at any time. When a component fails
(hardware crash, network down, bug in server), we have to employ
techniques that enable the system as a whole to continue operations and
recover from failures. And any distributed system will experience
component failure, often in weird and mysterious and unanticipated ways.
Second, creating a scalable distributed system requires the coordination of
multiple moving parts. Each component of the system needs to keep its part
of the bargain and process requests as quickly as possible. If just one
component causes requests to be delayed, the whole system may perform
poorly and even eventually crash.
To deal with these problems there is a rich deep body of literature available
to draw on. And luckily for us engineers, there’s a rich, extensive collection
of technologies that are designed to help us build distributed systems that
are tolerant to fail and scalable. These technologies embody theoretical
approaches and complex algorithms that are incredibly hard to build
correctly. Using these platform level, widely applicable technologies, our
applications can stand on the shoulders of giants, enabling us to build
sophisticated business solutions.
Specifically, readers of this book will learn:
The fundamental characteristics of distributed systems, including
state management, time coordination, concurrency,
communications and coordination
Architectural approaches and supporting technologies for building
scalable, robust services
How distributed databases operate and can be used to build
scalable distributed systems
Architectures and technologies such as Apache Kafka and Flink for
building streaming, event-based systems
Part I. Scalability in Modern
Software Systems
A NOTE FOR EARLY RELEASE READERS
With Early Release ebooks, you get books in their earliest form—the
author’s raw and unedited content as they write—so you can take
advantage of these technologies long before the official release of these
titles.
If you have comments about how we might improve the content and/or
examples in this book, or if you notice missing material within this
chapter, please reach out to the editor at [email protected].
The first four chapters in Part 1 of this book motivate the need for
scalability as a key architectural attribute in modern software systems. The
chapters provide broad coverage of the basic mechanisms for achieving
scalability, the fundamental characteristics of distributed systems, and an
introduction to concurrent programming. This knowledge lays the
foundation for what follows, and if you are new to the areas of distributed,
concurrent systems, you’ll need to spend some time on these four chapters.
They will make the rest of the book much easier to digest.
Chapter 1. Introduction to
Scalable Systems
A NOTE FOR EARLY RELEASE READERS
With Early Release ebooks, you get books in their earliest form—the
author’s raw and unedited content as they write—so you can take
advantage of these technologies long before the official release of these
titles.
This will be the 1st chapter of the final book.
If you have comments about how we might improve the content and/or
examples in this book, or if you notice missing material within this
chapter, please reach out to the editor at [email protected].
The last 20 years have seen unprecedented growth in the size, complexity
and capacity of software systems. This rate of growth is hardly likely to
slow in the next 20 years – what these future systems will look like is close
to unimaginable right now. The one thing we can guarantee is that more and
more software systems will need to be built with constant growth - more
requests, more data, more analysis - as a primary design driver.
Scalable is the term used in software engineering to describe software
systems that can accommodate growth. In this chapter I’ll explore what
precisely is meant by the ability to scale – known, not surprisingly, as
scalability. I’ll also describe a few examples that put hard numbers on the
capabilities and characteristics of contemporary applications and give a
brief history of the origins of the massive systems we routinely build today.
Finally, I’ll describe two general principles for achieving scalability, namely
replication and optimization, that will recur in various forms throughout the