Cloud 101

Clouds 101
Understanding the state of cloud computing

Wednesday, May 26, 2010

http://www.ﬂickr.com/photos/jamesjordan/2751393381/

Cloud computing is an approach to computing that’s more ﬂexible and lets organizations
focus on their core business by insulating them from much of the underlying IT work.

http://www.ﬂickr.com/photos/juniorvelo/3577399832/

At its most basic, it’s computing as a utility – pay for what you need, when you need it, rather
than paying for it all up front.


This is what Nicolas Carr talked about in his book The Big Switch.


But clouds can be confusing. Part of the reason is that they’re a big deal, which means
everyone wants to be a part of them – even companies who have nothing to do with clouds.

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http://www.ﬂickr.com/photos/creative_tools/4339787963/

I’m going to try and clear some of this up for you.

Part one:
Disruption and the democratization of IT


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First, let’s talk about disruption.

http://www.ﬂickr.com/photos/harshlight/3235469361
Once, IT was a monopoly.

http://www.ﬂickr.com/photos/theclevelandkid24/4251408727/
Today, it’s a free market. The line of business has tremendous choice in what it owns, runs, and uses.

http://www.ﬂickr.com/photos/hyku/2039448524/
The boardroom loves this: instead of managing machines, they manage services.

http://www.ﬂickr.com/photos/ukanda/4455286483/
But enterprise IT doesn’t like it much, because it forces them to compete, and puts them side-by-side with organizations that
spend their entire day doing detailed usage and billing.

http://en.wikipedia.org/wiki/Adam_Smith
It’s not all bad, though. There’s a lot to be learned from a transition from monopoly to a free market.

Two reasons.

There were a couple of reasons IT was a monopoly for so long.

http://www.ﬂickr.com/photos/brewbooks/3319730327/
(16MB)
First, the machines were expensive. That meant they were a scarce resource, and someone had to control what we could do with
them.

http://www.ﬂickr.com/photos/argonne/4563394851/
Second, they were complicated. It took a very strange sect of experts to understand them. AVIDAC, Argonne's ﬁrst digital
computer, began operation in January 1953. It was built by the Physics Division for $250,000. Pictured is pioneer Argonne
computer scientist Jean F. Hall.

AVIDAC stands for "Argonne Version of the Institute's Digital Automatic Computer" and was based on the IAS architecture
developed by John von Neumann.

http://www.ﬂickr.com/photos/ebeam/3586287989/
This was also a result of scarcity. When computers and humans interact, they need to meet each other halfway. But it takes a lot
of computing power to make something that’s easy to use;

http://www.ﬂickr.com/photos/ecastro/3053916892/
in the early days of computing, humans were cheap and machines weren’t

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So we used punched cards,

http://50ans.imag.fr/images/galerie/Source/IBM-1130-1.jpg
and switches,

http://honeynet.onofri.org/scans/scan22/sol/submission/reverse.jpg
and esoteric programming languages like assembler.

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Think about what a monopoly means.

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A monopoly was once awarded for a big project beyond the scope of any one organization, but needed for the public good.

http://www.ﬂickr.com/photos/athomeinscottsdale/2850893998/
Sometimes, nobody wants the monopoly—like building the roads.

For the most part, governments have a monopoly on roadwork, because it’s something we need, but the beneﬁts are hard to
quantify or charge back for.

http://www.ﬂickr.com/photos/leokoivulehto/2257818167/
(IT’s been handed many of these thankless tasks over the years, and the business has never complained.)

http://www.ﬂickr.com/photos/crobj/4148482980/
The only time we can charge back for roads are when the resource is speciﬁc and billable: a toll highway, a bridge.

http://en.wikipedia.org/wiki/File:Bell_System_hires_1900_logo.PNG
Sometimes, we form a company with a monopoly, or allow one to operate, in order to build something or allow an inventor to
recoup investment. This is how we got the telephone system, or railways.

For much of its history, AT&T and its Bell System functioned as
a legally sanctioned, regulated monopoly.
The US accepted this principle, initially in a 1913 agreement
known as the Kingsbury Commitment.
Anti-trust suit ﬁled in 1949 led in 1956 to a consent decree
whereby AT&T agreed to restrict its activities to the regulated
business of the national telephone system and government
work.
Changes in telecommunications led to a U.S. government
antitrust suit in 1974.
In 1982 when AT&T agreed to divest itself of the wholly owned
Bell operating companies that provided local exchange service.
In 1984 Bell was dead. In its place was a new AT&T and seven
regional Bell operating companies (collectively, the RBOCs.)
http://www.corp.att.com/history/history3.html
When monopolies are created with a speciﬁc purpose, that’s good. But when they start to stagnate and restrict competition, we
break them apart.

http://www.ﬂickr.com/photos/ktylerconk/4096965228/
In fact, there’s a lot of antitrust regulation that prevents companies from controlling too much of something because they can
stiﬂe innovation and charge whatever they want. That’s one of the things the DOJ does.

First: Monopoly good.

In other words, early on monopolies are good because they let us undertake hugely beneﬁcial, but largely unbillable, tasks.

Then: Monopoly bad.

Later, however, they’re bad because they reduce the level of creativity and experimentation.

http://www.ﬂickr.com/photos/wikidave/2867257631/

Today, computing is cheap. We can buy many times the compute power of the Apollo missions with a swipe of a credit card.

http://www.ﬂickr.com/photos/mbrubeck/4460320021/

It’s also not complicated. Everyone can use a computer. Because today, the computer is cheap and the human’s expensive we
spend so much time on user interfaces, from GUIs to augmented reality to touchscreens to voice control to geopresence.

http://www.ﬂickr.com/photos/raneko/4203965136/
What used to take a long time to procure, conﬁgure, and deploy is now a mouseclick.

http://www.ﬂickr.com/photos/19646481@N06/4263667827/
The way data centers are designed must reﬂect this shift from IT-as-a-monopoly to IT-as-an-enabler

http://www.ﬂickr.com/photos/seier/3349428961/
That means building a set of platforms that can adapt and adjust:

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From rack-and-stack servers to click-and-drag deployment

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From underused bare metal to on-demand virtual machines

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From procurement and process to self-service and quick decommissioning.

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The lesson of monopolies is an important one. When a monopoly set out to build a railroad, it didn’t spend a lot of time asking
potential travelers what they wanted.

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When you’re building something huge and expensive, you build what you want, and expect people to be grateful for it.

http://www.ﬂickr.com/photos/mmbrown/3102707594/
But today’s IT user is driving IT requirements.

They can shop around—choosing SaaS, clouds, and internal IT according to their business requirements.

http://www.codeproject.com/KB/miscctrl/ScriptStudio.aspx Wufoo.com

They’re increasingly able to build the applications themselves, but expect IT to deliver smooth, fast platforms on which to
experiment.

http://www.ﬂickr.com/photos/commensa/4027055357
As the line of business looks more and more like a consumer in a competitive market—and less and less like a grateful customer
of a monopoly—IT has to change its offerings.

USERS

APPS

PLATFORMS

HARDWARE

It’s an inversion of the traditional IT “pyramid”, where the hardware dictates the platforms, which in turn dictates, the apps,
which dictates what users can do.

USERS

APPS

PLATFORMS

HARDWARE

Today, what users want to do drives the apps they use, which drives the platforms and the hardware.

http://www.flickr.com/photos/scriptingnews/3471500626/

We’ve had big changes since that time. The first was client-server computing: the idea that
not everything lived in a mainframe, and some things worked well on the desktop. Software
like Visicalc—the first spreadsheet—were useful for businesses, even those who couldn’t
afford a mainframe.

http://en.wikipedia.org/wiki/File:NCSA_Mosaic.PNG

A second big change was the Web. This browser-based model made computing accessible to
the masses. As a result, it became part of society, and everyone knew how to work it. These
days, you don’t have to teach a new hire how to use a web browser: they know what links do;
what the back button is; and so on.

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A third change is the move to mobility. This has been bigger overseas, where the mobile
phone is the dominant way of accessing the Internet, but it’s still a shift to the always-
connected, always-on lifestyles we lead today.

http://img.dailymail.co.uk/i/pix/2008/04_01/tornadoDM3030a_800x533.jpg

And now there’s cloud computing. Clouds are as big a shift as client-server, or the web
browser, or mobility.

Part two:
A history of virtualization.


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The
step-‐func-on
nature
of
dedicated
machines
doesn’t
distribute
workload
very
eﬃciently.

http://www.ﬂickr.com/photos/h4ck/2413562108/


Virtualization lets us put many workloads on a single machine

http://www.ﬂickr.com/photos/stawarz/3538910787/
Once
workloads
are
virtualized,
several
things
happen.
First,
they’re
portable

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Second,
they’re
ephemeral.
That
is,
they’re
short-‐lived:
Once
people
realize
that
they
don’t
have
to
hoard
machines,
they
spin
them
up
and
down
a
lot

more.

http://www.ﬂickr.com/photos/genewolf/147722350
Which
inevitably
leads
to
automa3on
and
scrip3ng:
We
need
to
spin
up
and
down
machines,
and
move
them
from
place
to
place.
This
is
hard,
error-‐prone
work
for
humans,
but

perfect
for
automa3on
now
that
rack-‐and-‐stack
has
been
replaced
by
point-‐and-‐click

http://www.ﬂickr.com/photos/pinkmoose/3278324276/
Automa-on,
once
in
place,
can
have
a
front
end
put
on
it.
That
leads
to
self
service.

“Cloudy”
tech.
These
are
the
founda-ons
on
which
new
IT
is
being
built.
Taken
together,
they’re
a
big
part
of
the
movement
towards
cloud
compu-ng,
whether
that’s
in

house
or
on-‐demand.

Virtualization divorces the app from the machine.

One on many (or) Many on one
Physical machine
Virtual machine

Virtual Virtual Virtual
Physical Physical Physical machine machine machine
machine machine machine
Virtual Virtual Virtual
Physical Physical Physical machine machine machine
machine machine machine


Okay, so these things mean we have applications that run “virtually” – that is, they’re divorced
from the underlying hardware. One machine can do ten things; ten machines can do one
thing.

That’s the technical deﬁnition
Virtualization
Automation
Self-service
Elasticity
Usage tracking & billing
Service-oriented article


This is the “technical” deﬁnition of cloud computing: virtualized, automated, self-service
computing resources. Some people call this a “private cloud”; others think it’s just IT-done-
right. Whatever the case, data centers are furiously retooling themselves, much to the
enjoyment of companies like VMWare and Citrix.

Part three:
Stacks and the separation of concerns.


Part three: Stacks and the separation of concerns

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At its most simple, this is all about a “stack” of services. Stacks are a common idea in
computing and networking. Basically, they’re a separation of different tasks.

http://www.ﬂickr.com/photos/easternblot/126112823/

We’re familiar with the idea of a stack. There’s a stack in the postal service.

Your virtual platform

Layer of separation
Their physical infrastructure


You worry about the address, and the stamp. The postal service handles the rest—it doesn’t
care what’s inside your envelope; and you don’t care what route your letter takes to its
destination, as long as it gets there.

Part four:
Clouds as a business model.



But wait -- there’s more! There’s another way to look at cloud computing.

This has all been DIY.


Notice that so far, nothing I’ve said about clouds implies you can’t just run your own. Up until
now, they’ve been DIY.

Clouds
are a
business
model.

This is the clouds-as-a-business-model deﬁnition. In this, cloud computing is a third-party
service.

http://www.ﬂickr.com/photos/laenulfean/479831551/

All of the things we’ve seen about cloud technology make it possible to deliver computing as
a utility -- computing on tap.
The virtualization provides a blood/brain barrier between the application the user is running,
and the machines on which it runs.


That means you can focus on the thing your business does that makes you special


And stop worrying about many of the tasks you really didn’t want to do anyway.

http://www.oncloudcomputing.com/en/2009/07/fronde-back-to-proﬁt-by-cloud-computing/

Sharing and economies of scale keep costs down. Cloud providers are poised to make the
most of these economies of scale. Consider that in July 2008, Microsoft revealed that it had
96,000 servers at the Quincy facility, consuming "about 11 megawatts"
More than 80% dedicated to Microsoft's Live Search and the remaining for Hotmail
In August, a really good discovery was posted to a blog called "istartedsomething.com": a
screen shot of a software dashboard that illustrates power consumption and server count at
each of Microsoft's ﬁfteen data centers, caught in a Microsoft video posted to their web site.

Idle
capacity,
lack of
automation,
etc.
IT server
costs
Ping, power,
pipe,
Private efﬁciencies
cloud
costs Public
cloud
costs


The move towards the cloud business model has a lot to do with the economies of scale that
exist when you can concentrate infrastructure, and put it near dams. (There’s a good—if hotly
debated argument—that clouds-as-a-business-model are inevitable, because of the
economics.)


Cloud providers are thinking at a scale that nearly every enterprise can’t compete with. That’s
because operating efficiency, and accounting for everything, are core to their business;
whereas making widgets is core to yours.


Self-service means customers can deploy and destroy their own machines.

Dedicated On-premise Virtual Third-party
hardware private clouds private clouds public clouds


So while you can build an automated, self-service, on-demand private cloud, there are also
many public options (is that a bad word in DC? )

http://www.ﬂickr.com/photos/carbonnyc/2294144289/

Most of the time, when you hear someone say they’re concerned about the security of cloud
computing, they’re talking about public clouds, and the issues that come with putting your
data somewhere virtually but not knowing where it is physically.

Part ﬁve:
Kinds of clouds.


http://www.eo.ucar.edu/webweather/cloud3.html

So far, while I’ve told you a lot about clouds, I haven’t really told you what they are. That’s
partly because there are many kinds of cloud computing.
We can separate clouds into three distinct groups.

Infrastructure as a Service
Amazon EC2, Rackspace Cloud, Terremark,
Gogrid, Joyent (and nearly every private cloud
built on Zenserver or VMWare.)


The ﬁrst is called Infrastructure as a Service, because you’re renting pieces of (virtual)
infrastructure.

http://aws.amazon.com/ec2/pricing/

This is what IT people think of when you say “clouds” – virtual machines I can use for just an
hour. Here’s Amazon’s “menu” of machines.

• 60 seconds per page
Desktop EC2 • 200 machine
Pages 17,481 17,481 instances
Minutes/page 1 1 • 1,407 hours of virtual
# of machines 1 200 machine time
Total minutes 17,481 • Searchable database
Total hours 291.4 26.0 available 26 hours
Total days 12.1 1.1 later
• $144.62 total cost


A great example of these clouds in action is what the Washington Post did with Hillarly
Clinton’s diaries during her campaign. They needed to get all 17,481 pages of Hillary Clinton’s White House
schedule scanned and searchable quickly. Using 200 machines, the Post was able to get the data to reporters in only 26 hours. In
fact, the experiment is even more compelling: Desktop OCR took about 30 minutes per page to properly scan, read, resize, and
format each page – which means that it would have taken nearly a year, and cost $123 in power, to do the work on a single machine.

Machine Web
Image server
Machine instance


In an IaaS model, you’re getting computers as a utility. The unit of the transaction is a virtual
machine. It’s still up to you to install an operating system, and software, or at least to choose
it from a list. You don’t really have a machine -- you have an image of one, and when you
stop the machine, it vanishes.

DB Machine
Storage
server Image

Machine instance

App Machine
Server Image
Machine instance

Web Machine
server Image
Machine instance


Most applications consist of several machines -- web, app, and database, for example. Each
is created from an image, and some, like databases, may use other services from the cloud to
store and retrieve data from a disk

DB
Storage server

Machine instance
Bigger
App
machine
instance
Server
Machine instance

Web
server
Machine instance


If you run out of capacity, you can upgrade to a bigger machine (which is called “scaling
vertically.”)

DB
Storage
server

Machine instance

App
Server
Machine instance

Web
server
Machine instance

Load
balancer
Machine instance


Or you can create several machines at each tier, and use a load balancer to share traffic
between them. These kinds of scalable, redundant architectures are common -- nay,
recommended -- in a cloud computing world where everything is uncertain.

Platform as a Service
Google App Engine, Salesforce Force.com,
Rackspace Cloud Sites, Joyent Smart Platform,
(and nearly every enterprise mainframe.)


The second kind of cloud is called Platform as a Service. In this model, you don’t think about
the individual machines—instead, you just copy your code to a cloud, and run it. You never
see the machines. In a PaaS cloud, things are very different.

Shared components

Data Processing platform
Storage
API
Others’ Others’
code code
User Auth
database API
Your Others’
code code
Image Image
functions API Others’ Others’
code code
...
Big Blob Governor Console Schedule
objects API

- You write your code; often it needs some customization.
- That code runs on a share processing platform
- Along with other people’s code
- The code calls certain functions to do things like authenticate a user, handle a payment,
store an object, or move something to a CDN
- To keep everything running smoothly (and bill you) the platform has a scheduler (ﬁguring
out what to do next) and a governor (ensuring one program doesn’t use up all the resources)
as well as a console.

http://code.google.com/appengine/articles/load_test_screenshot.jpg

Here’s a shot of some code running in Google App Engine. I only know that I’m paying by
CPU-hour, or for units like bandwidth, email, or storage. This could be one machine whose
CPU was used 8%, or a hundred, or a thousand. I don’t know.

http://code.google.com/appengine/articles/logs_admin.png

I can see the logs for my application. But these aren’t for a single machine -- they’re for the
application itself, everywhere.

http://googleappengine.blogspot.com/2010/03/easy-performance-proﬁling-with.html

I can even ﬁnd out what parts of my code are consuming the most CPU, across all machines.


And even their latency when served to people.

http://www.computerhok.nl/JSPWiki/attach/GoogleAppEngine/GAEQuota.png

It’s a true, pure utility because you pay for what you use.

http://www.ﬂickr.com/photos/olitaillon/3354855989/

This is a very different model from IaaS. On the one hand, it’s more liberating, because you
don’t have to worry about managing the machines. On the other hand, it’s more restrictive,
because you can only do what the PaaS lets you.

IaaS and PaaS differences
IaaS PaaS

Any operating system you Use only selected
want languages and built-in APIs

Limited by capacity of Limited by governors to
virtual machine avoid overloading

Scale by adding more Scaling is automatic
machines
Use built-in storage
Many storage options (ﬁle (Bigtable, etc.)
system, object, key-value)


In the case of Google’s App Engine, you have to use their functions and store things in the
way they want you to. You get great performance from doing so, but it probably means
rewriting your code a bit.

Quota Limit
Governor Apps per developer 10
(usage cap) Time per request 30s
Blobstore (total ﬁle size) 1GB
Maximum HTTP response size 10MB
Datastore item size 1MB
Application code size 150MB

Daily cap Emails per day 1,500
(free quota) Bandwidth in per day 1 GB
Bandwidth out per day 1GB
CPU time per day 6.5h
HTTP requests per day 1,300,000
Datastore API calls per day 10,000,000
URLFetch API calls per day 657,084
http://en.wikipedia.org/wiki/Google_App_Engine

PaaS platforms impose usage caps and billing tiers. Here’s Google App Engine’s set of quotas
and free caps.

i.developerforce.com/index.php/Apex_Code:_The_World%27s_First_On-Demand_Programming_Language

In the case of Salesforce’s Force.com, you have to use an entirely new programming
language, called Apex.


The third kind of cloud is called Software as a Service, or SaaS. Some people argue that this
isn’t a cloud at all, just a new way of delivering software. But it’s also what the masses—the
non-technologists—think cloud computing means.

My mom’s deﬁnition

Cloud = Web = Internet = Useless


(Personally, I think this makes the term “cloud” synonymous with “web” or “Internet”, and
therefore a bit useless.)


SaaS and PaaS are blurring, too, with the advent of scripting languages. Nobody would argue
that Google Apps is a SaaS offering; but now that you can write code for it -- as in this
example of a script that sends custom driving directions to everyone in a spreadsheet -- the
distinction is less and less clear.


But the business model of SaaS is the same as PaaS and IaaS: Sell IT on demand, rather than
as software or machines.


It’s the form of cloud computing that gets the most lip service in areas like government,
particularly with Google Apps.

Part six:
It’s all a blend, really.


Service What it does
Elastic Compute Cloud Virtual machines, by the hour
Elastic Mapreduce Massively parallel data processing
Virtual Private Cloud On demand machines within internal IT
Elastic Load Balancing Traffic distribution
Cloudfront Content delivery acceleration
Flexible Payments Service Funds transfer & payments
SimpleDB Realtime structured data queries
Simple Storage Service Eleven nines redundant storage
Relational Database Service On-demand RDBMS
Elastic Block Store Block-level storage (file system)
Fulfillment Web Service Merchant delivery system
Simple Queue Service On-demand message bus
Simple Notification Service System for sending mass notifications
Cloudwatch Monitoring of cloud resources
Mechanical turk Humans as an API

This division between PaaS and IaaS is a bit of a fiction. In fact, virtual machines are just one
of around twenty “cloud services” Amazon offers – called EC2.

Service What it does
App Engine Executing Python or Java code
Bigtable datastore Store data for very fast retrieval
Calendar Data API Create and modify events
Inbox feed API Read a GMail inbox
Contact data API Interact with someone’s GMail contacts
Documents list API Manage a user’s Google Docs
OpenID single signon Use Google authentication to sign in
Secure data connector Link Google Apps to enterprise apps
Memcache Fast front-end for data
Image manipulation Resize, rotate, crop & ﬂip images
Task queue Queue and dispatch tasks to code
Blobstore Serve large objects to visitors

The same is true of App Engine - though these are functions called from code, rather than
services you pay for separately, they’re still more than just the code.

Clouds
aren’t
just
virtual
machines.

This is a really important concept: Clouds aren’t just virtual machines. Clouds are on-demand
computing services.

http://www.ﬂickr.com/photos/gezellig-girl/4351078755/

To understand this, we need to talk for a minute about “composed designs.”

Query language
Let’s just call
this a database,
Software ‘mmkay?

Operating system

Computer hardware

Storage media


When IT architects want to build something, they have a set of proven designs for doing so. A
database is an example of this—it’s a combination of storage (disk) and a particular way of
arranging things (tables and indexes) and language (structured query language, or SQL).
We’ve learned that a database is a good prefab building block, so we use it. The alternative is
to build it all, from scratch, writing to the disk itself.


There are other examples of “composed designs” in IT, many of them made from several
components. For instance, consider the “message bus.” This is a thing you put messages
into, and anyone who wants them can grab a copy of the message. Stock exchanges use
publish-and-subscribe message busses to move data around.

http://couchdb.apache.org/

A third example is called a key-value data store. In this case, I put in a key (say, ”username”)
and a value (say, “Palin”). Then it’s stored for me. It’s much less fancy than a database, but
also much faster and more scalable, and can be backed up more easily so it’s more reliable.

http://www.ﬂickr.com/photos/jackol/133765382/

When architects want to build an application today, they don’t do so by building everything
from scratch. Today’s applications are built on the shoulders of giants—message busses,
data stores, authentication systems, payment tools, content delivery networks, and so on.


As a result, cloud providers offer a variety of these services. Rackspace has a storage product
called Jungledisk; Amazon has S3. The machines that Rackspace or Amazon offer “chew” on
data from these storage services.

http://aws.typepad.com/ﬁles/JBH_Architecture_Large.png

If you equate cloud computing with just virtual machines, you’re missing the real point.
Clouds applications are built from composed designs, and one of the components happens to
be virtual machines.

Private Public

nt t o SaaS
a
w d s,
o u lo u
y c
If l k
PaaS
rs t.PaaS
t a ne f i
i ck o
IaaS p IaaS

Managed
Virtualization
hosting


So let’s put this in perspective: There are public and private cloud models. Private ones are
about the technology; public ones are about the business of outsourcing at scale.
And there are Infrastructure, Platform, and Software offerings—IaaS, PaaS, and SaaS.
If someone wants to have a conversation with me about clouds, they need to pick a tier, and
a private or public model. Then we can compare facts.

Private Public

SaaS
Lock-in concerns

Long-term
PaaS cost Security fears
inefﬁciencies
High cost of maintaining &
scaling machines
IaaS


Just knowing these two dimensions makes you smarter than nearly everyone in IT right now.
And when you’re discussing IT, insist that others are speciﬁc about what they mean.
Discussions around privacy and security are vital to public clouds, but most people don’t
consider security different in private clouds. Similarly, lock-in is a real concern in PaaS but
negligible in IaaS.

Part seven:
The ecosystem



Lots of people want to move into this space. Some are e-commerce giants (like Amazon) who
know how to run many machines well.


Some are software companies with legions of developers (like Microsoft) who want to move
from software licenses to recurring revenues.


Some are managed hosting companies (like Rackspace, Terremark, and Gogrid) who want to
sell computing by the hour instead of by the month, and want to have more standardized
offerings.


Some are giant service companies (like Google) who want people to create millions of
applications and keep people using the Web.


Some are big systems integrators (like IBM) who want to design and run IT for enterprises.


Some are hardware vendors (like Dell) who want to stay in the computing business as it
shifts.


Some are telecom providers (like AT&T and Verizon) who want to do more than move packets
around, and want to make the best use of their existing data centers.


Some are even government organizations aiming to build infrastructure for the use of the
government itself

http://www.thule-car-roof-boxes.co.uk/pictures/roof-box-with-roof-rack.jpg

This isn’t a comfy place to be right now. Cloud computing has what I call a “roofrack”
problem.

Part eight:
So what do I do now?


http://www.ﬂickr.com/photos/gideon/6582069/

Cloud computing isn’t something you can easily ignore.


For some applications, particularly those that are bursty or seasonal, the economics are
overwhelmingly in its favor.

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Connect times to Amazon Cloudfront from NYC
5%''%,!6%%,($7!0$48#,!9%''%,!,#3'($7:
Cloud Encounters, Peter van Eijk, digitalinfrastructures.nl
Wednesday, May 26, 2010 !
Cloud providers keep making their stuff better. Amazon introduced roughly 40 new features
last year; and in a single month they upgraded their network in New York twice.

http://www.ﬂickr.com/photos/billselak/366692332/


And clouds make organizations more agile, because they take procurement from weeks to
minutes.

Expense
reports
can
no

longer
enforce
IT
policy.

Wiley
GAAP
2010:
Interpreta3on
and
Applica3on
of
Generally
Accepted
Accoun3ng
Principles
(By
Barry

J.
Epstein,
Ralph
Nach,
Steven
M.
Bragg)

They also remove the false sense of security that came from expense limits.

Airfare

DNS

Cloud

Public
transit

Important
research

Hotel

These
days,
supercompu-ng
is
easier
(and
cheaper)
than
booking
a
ﬂight.

We stop worrying about ROI when I is zero.


Because there’s no investment, the concept of an ROI doesn’t really make sense.

http://www.ﬂickr.com/photos/avlxyz/389030408/

Even if you’re only going to run a private cloud, you’re dealing with expectations set by the
public Internet. Consider an ATM – once, we didn’t mind taking all of lunch to get money out;
today, we worry when the bank machine fails to give us our money back in 10 minutes.
That’s a bad thing for organizations that don’t handle IT automatically; humans simply can’t
move that fast. Efficiency isn’t about how fast you do things; it’s about how many things you
don’t have to do because they’re automated.

http://www.ﬂickr.com/photos/stuartpilbrow/2894451883/

The Internet has a way of routing around obstacles, so if you try to block people from using
them, you’ll likely send your stakeholders underground.


The best thing to do is offer people an alternative. Set up self-service computing internally
and see what happens.

Single
Storage
sign on
Image
processing
Mailing
service Virtual
machine
Key/value
Virtual store
load balancer
Parallel
framework


It also means surrounding them with composed services like storage and message queues.
Fortunately, there is a wide variety of offerings to help with this. Hadoop, Cassandra,
CouchDB, Hypertable and others are all tools that handle storage, scaling, and parallel tasks,
and that you can deploy internally for your users.


It also means setting up platforms (such as a web server that can handle PHP code, or a
Drupal platform for creating social sites, or a Status.net instance for microblogging,


or a Wordpress instance for blogs.)


Finally, it means working with SaaS providers when appropriate, but integrating their
applications with your internal data and processes

http://www.ﬂickr.com/photos/jamesjordan/3423905959


For IT, and governments, cloud computing is a trigger. It means it’s time to rebalance your
computing decisions.

http://www.ﬂickr.com/photos/joconnell/504783550/

With clouds, there’s a spectrum of IT options. Different applications live in different places in
this new world.

Data centers Contracts Developers
<script>
Hello, world!
</script>

Mashup,
Bare Virtualization Public/private
IaaS PaaS RESTful
metal hybrid models
services


Different applications live in different places in this new world.

http://www.ﬂickr.com/photos/23912576@N05/347608011


Here’s a ﬁve-step plan for embracing clouds.

http://www.ﬂickr.com/photos/quinnanya/4569703917/

First, you need to assess your existing applications. Make a list of everything you’ve got, or
plan to have. You should also baseline usage, performance, and other “before” metrics so you
can compare them to the results of your efforts after you’ve moved.

http://www.ﬂickr.com/photos/rptnorris/3453936781/

Then, you need to rebalance your applications. Evaluate each application along two
dimensions: how suitable is the application for migration, and what’s the payoff.

http://www.ﬂickr.com/photos/cowcoptim/4104360701/

Some applications, like legacy ERPs or old mainframe tools, won’t migrate easily. They’re not
well suited to a virtualized, on-demand model where users can spin up resources as needed.

http://www.ﬂickr.com/photos/sharif/2423144088/


Others, like web front-ends or parallel data processing tasks like analytics, that can be split
up, work really well in clouds.

Some things
aren’t worth moving.


At the same time, some applications won’t beneﬁt much from a cloud model. Something that
runs constantly may be more affordable to run in-house.

http://www.ﬂickr.com/photos/aprilzosia/3002232587/

Other applications may have a massive budget savings when they move to the cloud.
Something that happens once a year but needs tremendous computing for the three days it
runs is a candidate for clouds. So, too, is something that users are constantly requesting, and
that your IT team spends a lot of time managing. Automate it!

Compute task
(service cloud)

Virtual machine
(infrastructure cloud)

Always on Can be done Always in
premise anywhere cloud

Load/pricing engine
Private
Partner access
Compliance- Testing
enforced Proximity to cloud
Training services (storage,
Policy engine

Need to track and
Prototyping CDN, etc.)
audit
Batch processing Massively grid/
Legislative
Seasonal load parallel (genomic,
Data near local modelling)
computation


Going forward, we’ll see hybrid on-premise/on demand hybrid clouds that can intelligently
move processing tasks between private an public infrastructure according to performance
requirements, pricing policies, and security restrictions.

http://www.ﬂickr.com/photos/rberteig/1451038457/

Third step: You have to migrate things to the new environments. This means moving stuff
around—hopefully the high-payoff, easy-to-move stuff ﬁrst. There’s no magic here: you’ll
need to make your applications portable, which means virtualizing them; and you may need
to modify some code.

http://www.ﬂickr.com/photos/astro-dudes/2424283150/


Step four is to optimize things. In their new homes, some applications won’t perform as well.
You’ll need to compare how they’re doing now to how they were doing before, and tweak
things to ensure equivalent performance, uptime, security, and scalability.

http://www.ﬂickr.com/photos/geoftheref/2253511823/

Finally, in step ﬁve you need to operate things differently. Cloud computing is as much about
a cultural shift in IT: you’re operating a self-service business.

http://www.ﬂickr.com/photos/hojusaram/2527256358/

You’re not doing the IT work any more; you’re managing the scripts and systems that let
users do the IT work themselves. You have a very different relationship with your end users.

http://www.ﬂickr.com/photos/avlxyz/1193082725/

You’re providing the environment for them to innovate, giving them turnkey sets of services
with which to work. Where they come from is immaterial.

http://www.ﬂickr.com/photos/novecentino/2340521934/

You’re ensuring that the systems you’ve built are functioning properly however end users
want to use them, rather than running the applications or data within those systems.

http://www.codeproject.com/KB/miscctrl/ScriptStudio.aspx Wufoo.com

Your end users aren’t necessarily technical -- they’re able to build applications easily,
and want the tools to experiment.

http://www.ﬂickr.com/photos/roebot/4271975019/
At the same time, you’re seeing what tools and processes are getting adopted -- what’s working? what’s popular? -- and
doubling down on those things.

http://www.ﬂickr.com/photos/steven_wong/2440355239/
You’re giving your users places to experiment.

http://www.ﬂickr.com/photos/jelles/2902422030/
To some extent, you’re “paving the cowpaths.”

This is an old civil engineering trick: Watch where people walk, then put paths there.

Part nine:
Conclusions.


Massive disruption on the
horizon
Clouds are extremely disruptive to the way IT
works


Virtualization let the genie
out of the bottle
Clouds arose from virtualization, which made
application workloads portable


Clouds start with separation

Separation is key
Determines economics, lock-in, responsibility, risk


One of the fundamentals of a cloud is the separation of the provider from the user at some
layer in the stack
Where that separation happens determines economics, responsibilities, risk, and lock-in

Business vs. technology

Know the difference
Clouds-as-tech: Virtualized, automated
Clouds-as-business: 3rd party, shared
Force others to be clear


Two main divisions
IaaS/PaaS/SaaS
Public/Private


One size does not ﬁt all
Ultimately, the blend of these different models
will vary from organization to organization


Five steps to cloud migration

Assess Balance Migrate Optimize Operate


Ecosystem is in ﬂux
The ecosystem is competitive and confusing
right now, with few standards and a lot of noise


http://www.ﬂickr.com/photos/sparkys/3434382326/

It will probably wind up looking like airlines.

http://www.cio.gov/documents/
StateOfCloudComputingReport-FINALv3_508.pdf


The big picture
Representation is a hack



Thanks!
@acroll
alistair@bitcurrent.com


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