“Civilization advances by extending the number of important operations
which we can perform without thinking about them.”
—Alfred North Whitehead, Introduction to Mathematics
This book is about cloud computing and how you, the reader, m ay apply it to
advantage in science and engineering. It is a practical guide, with many hands-on
examples, all accessible online, of how to use cloud computing to address specific
problems that arise in technical computing, and actionable advice on how and
when to apply cloud computing in your daily work.
The term cloud computing was first used in 1996; today, it appears on billboards
in airports. You may wonder whether it is a technology, movement, repackaging of
old ideas, or marketing slogan. It is all of these things and more. Above all, though,
it is a transformation i n the state of aairs that we ignore at our peril, in science as
in other parts of our life. As Tim Bray wrote in 2015: “Yeah, computing is moving
to a utility model. Yeah, you can do all sorts of things in a public cloud that are
too hard or too expensive in your own computer room. Yeah, the public-cloud
operators are going to provide way better uptime, security, and distribution th an
you can build yourself. And yeah, there was a Tuesd ay in last week.” [77]
This emergence of powerful, always-on, accessible cloud utilities has transformed
how we, as consumers, interact with in formatio n technology, allowing us to stream
videos from Netflix (hosted on the Amazon cloud), s earch for web content via
Google (leveraging the Google cloud), update friends on our doings via Facebook,
and ask Alexa to buy our groceries. The cloud has also allowed many companies to
outsource much of their information technology to cloud providers, slashing costs
and increas ing velocity. Myriad previously manual activities are being automated
via software running on cloud utilities, in ways imagined by McCarthy in 1960 and
explored by grid in the 1990s, and now realized at scale by cloud providers such as
Amazon, Google, and Microsoft.
But what about science and engineering? Many scientists and engineers use
cloud services su ch as Dropbox, GitHub, Google Docs, Skype, and even Twitter in
their work. But they are far from exploiting the full benefits of cloud computing.
Some technical applications run on cloud computers, but few researchers outsource
much else to the cloud. This is a missed opp ortun ity. After all, science and
engineering, while fascinating and intellectually rewarding professions, include
many mundane and time-consuming activities. Can we not accelerate discovery
(and have more fun) via automation and outsourcing? We believe that the answer
to this question is yes, which is why we wrote thi s book.
In the chapters that follow, we examine the new technologies that underpin
cloud, the new approaches to technical problems that cloud enables, and the new
ways of thinking that are required to apply cloud eectively in research. We do
not aspire to provide a comprehensive guide to cloud computing: the major cloud
providers operate literally hundreds of services, and there are surely many beyond
those presented here that can be applied eectively in science and engineering.
But we do describe the essentials and provide you with the concepts required to
integrate cloud services into your work.
The following are s ome of the questions that we find people asking, and for
which we aim to provide answers. Should I buy a cluster or use cloud? Will my
grant pay the bills if I use a co mmerci al cloud? How can I get my data to the
cloud? Is it safe there? Can I share it with my collaborators? How do I comp ute
in the cloud ? Can cloud computing scale? What if I want to compute on large
quantities of data? Should I u se cloud platform services in my work? Which ones
are good for science and engineering? How can I build my own cloud s ervices?
Can I ma ke them scale on demand to address really large problems? What are
some examples of successful uses of cloud in science and engineering? How can I
build my own cloud?
Lacking a crystal ball, we cannot provide definitive answers to these questions.
But we can at least provide you with information and perspectives that you can
use to make up your own mind on these and other questions.
All flows, nothing stays.
So wrote Heraclitus 2,500 years ago,
and software is worse. Some technical details in this bo ok will
prove more transient than we would like. Do not despair. Help
us and your colleagues by letting us know at
We will update the website, and prepare for the second edition.