State of the Cloud presentation from Interop 09 Enterprise Cloud Summit

State of the CloudEnterprise Cloud SummitNew York, NY

November 17, 2009

Wednesday, November 18, 2009

Good morning, and welcome to ECSSome introductory thoughts on clouds, how we got here, where we’re going.

Tagging#interop#ecs{


If you want to post pictures or comments, use #Interop and #ECS


If you want to post pictures or comments, use #Interop and #ECS

A bit about Bitcurrent

Analysis and research of emerging technologies

Cloud computing, web performance, human/computer interaction, emergent communications technology


Vis

ibilit

y

Time

Technologytrigger

Peak of inflatedexpectations

Trough ofdisillusionment

Slope ofenlightenment

Plateau ofproductivity

http://www.gartner.com/pages/story.php.id.8795.s.8.jspWednesday, November 18, 2009

You’re probably all familiar with Gartner’s “Hype curve.” I’m sorry to say that, according to them, we’re at the apogee -- the peak of inflated expectations. Disillusionment awaits us. Then, of course, clouds will become a part of our lives.

http://www.gartner.com/pages/story.php.id.8795.s.8.jsp

http://www.gartner.com/pages/story.php.id.8795.s.8.jsp

The stages of griefThe loss of traditional IT.


I like to look at a slightly different curve. It’s the stages of grief, as IT loses its traditional environments. This loss comes from a number of things:- An inability to compete on cost versus the single-mindedness of cloud providers- The changing patterns of data, storage, and computation that put users everywhere and make workloads bursty- A newfound desire for agility and faster pace of change and experimentation

Vis

ibilit

y

Time

Denial

Anger

Bargaining

Depression

Acceptance

You are here


0

25

50

75

100

http://developer.amazonwebservices.com/connect/thread.jspa?messageID=150461http://www.google.com/insights/search/#q=%22Cloud%20computing%22&cmpt=q

2005 2006 2007 2008 2009

Nov: S

imple

Queue

Servi

ce β

Mar: S

imple

Stor

age S

ervic

e (S3

) β

Aug:

Elasti

c Com

pute

Cloud (

EC2) β

Dec:

Simple

DB an

noun

ced

Mar: E

lastic

IP, Ava

ilabil

ity zo

nes

Aug:

Elasti

c Bloc

k Stor

e

Oct: E

C2 SLA

, Wind

ows S

erve

r

Nov: C

loudfr

ont C

DN anno

unce

d

Jan:

AWSMan

agem

ent a

nnou

nced

Mar: R

eser

ved i

nstan

ces

May: S

calin

g, ela

stic L

B for E

CS

Oct: R

elatio

nal D

B Servi

ce β


Here’s a rough timeline of cloud computing’s growth in recent years.First: Mentions on Google InsightThen: Gartner’s Hype Curve, which they claim is a 2-5 year cycleThen: The introduction of various services from AmazonThen: Big computing companies that have inked deals with AmazonThen: A history of some of the vendors and their initial cloud products

http://developer.amazonwebservices.com/connect/thread.jspa?messageID=150461




What we agree on:


In the last year, we’ve reached agreement on several things.

We have a taxonomy.


For starters, we have a taxonomy -- which is good. Sadly, however, we abandon it at a moment’s notice.

Private Public

SaaS

PaaS PaaS

IaaS IaaS

Managedhosting

If you want

to talk

clouds, pick

one first.


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.

We (sort of) agree on how to classify things.


JBoss ServerApplication instance

Intranet siteApplication code

Support ticketingCustom app, keybusiness process

Infrastructure cloud

(ECS, Joyent, Rackspace, Azure)

Agnostic PaaS(App Engine, Heroku,

Reasonablysmart, Azure)

“Flavored” PaaS(Quickbase, Bungee, Force.com, Webex

Connect)

Port to VM/AMI

Rewrite process

Rewrite code

Port code

Word processingStandard app,

no differentiation

SaaS(Google Apps, Office

Live, Basecamp, Freshbooks, Wufoo)

Copy content


What you want to move into the cloud will affect how you do it and what you move to.

Cloud responsibilities:Who owns what layer?

Hardware

Architecture

Operations

APIs

App logic

?IT user Cloud

This is whyclouds are new


This is managed hosting

Hardware Service provider owns it

Architecture User designs how things fit together

Operations User runs the machines

APIs Users talk to components directly

App logic User defines it, writes code

IT user Cloud


This is strategic outsourcing

Hardware User owns it

Architecture User designs how things fit together

Operations User runs VMs, not physical ones



IT user Cloud


This is an IaaS cloud


Architecture User chooses from predefined menu




IT user Cloud


This is a PaaS cloud




APIs Users only talk to well-defined services


IT user Cloud


This is SaaS




APIs Users only talk to well-defined services

App logic Service provider writes and maintains it

IT user Cloud


This is a private cloud





Users only talk to well-defined services


Internal clients Internal IT


We’ve stopped denying it.


Denial: Just timesharing all over

SOA

Virtualization

Standardization

Automation

Insulates components from functionality

through consistent APIs

Reduces minimum order quantity; turns physical things into logical ones

Means users are OK with a menu of predefined

configurations

Increases the human-to-machine ratio & drives

marginal cost towards 0

Amazon S3 turns storage into a

service

Buy a slice for just an hour

LAMP, Rails, etc.

10x enterprise efficiency ratios


This is the ranting of luddites and server-huggersOf SOA, the insulation of components by consistent APIsOf virtualization,which - Reduces the minimum order quantity - Makes automation possible by making the physical logicalOf platform standardization

Denial: just for startups“[There are] 60,000 different customers across the various Amazon Web Services, and most of them are not the startups that are normally associated with on-demand computing.

Rather the biggest customers in both number and amount of computing resources consumed are divisions of banks, pharmaceuticals companies and other large corporations who try AWS once for a temporary project, and then get hooked.”

http://www.techcrunch.com/2008/04/21/who-are-the-biggest-users-of-amazon-web-services-its-not-startups/


Even as early as last year, Amazon reported that the majority of its users and its compute cycles were consumed by enterprise customers.



Denial: they’re not reliable

! !

""#$%&

""#'%&

""#(%&

""#)%&

""#*%&

""#+%&

""#,%&

""#"%&

-%%#%%&

./0123

452678923:

4;;!4<; =>?@0AB

.C0/0D

=2??2!4<; E4$!F9B5037 G22H5B

.@@E3HD3B

G22H5B!?D:B G22H5B!?D:B

.@9I%" JB@I%"

45267!6@:D/B!D?!@9B::>!H227#!

037!HB::D3H!KB::B9

L?D3H!M2957IMD7B!/23D:29D3H!?:0:D23?!K>!N0:AO=26?BCloud Encounters, Peter van Eijk, digitalinfrastructures.nl


We have decent evidence that they can be relied on. Peter van Eijk is presenting this data at CMG next month, but gave us an early look at some performance benchmarking he’s done on Watchmouse, a European testing platform.

http://digitalinfrastructures.nl/


Denial: they’re slow

Cloud Encounters, Peter van Eijk, digitalinfrastructures.nl

! !

"#$$%&'!'()%*!+,#)!-.!

'#!/)01#$!"2#34+,#$'

5%''%,!6%%,($7!0$48#,!9%''%,!,#3'($7:

;

<

=;

=<

>;

><

?;

?<

@;

@<

<;

>@ABA

>;;C

>DABA

>;;C

>CABA

>;;C

?;ABA

>;;C

=ACA

>;;C

?ACA

>;;C

<ACA

>;;C

DACA

>;;C

CACA

>;;C

==ACA

>;;C

=?ACA

>;;C

=<ACA

>;;C

=DACA

>;;C

!"##"$%&'()$*+'*&'((%&+

Connect times to Amazon Cloudfront from NYC


Peter’s data also shows that Amazon is making significant headway with infrastructure upgrades that improve performance.



Reality is setting in.


Reality:Cloud operators have an unbeatable cost advantage.


At this point, it’s hard to argue that cloud operators will win on a cost basis alone.

How to think about costs

0

200,000

400,000

600,000

800,000

Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4

Cos

t

UpfrontFixedVariable


Any cost model consists of three kinds of spending: Upfront money spent to kick things off; fixed spending that doesn’t change whether you sell one or a billion units; and variable spending associated with the amount you sell.

IT costs: Upfront

Capital investment (often, “capex”)

Don’t overlook rewriting, retooling, retraining, data migration

For many enterprises, this is just the cost of periodic upgrades. They already have equipment.


IT costs: Fixed

Happen no matter what; a measure of leanness

May be shared with other activities, and therefore not eliminated (this is often invoked in defense of jobs)


Then there are the fixed IT costs that you can’t avoid. Clouds can drop these, but if you have IT running internal systems, they won’t magically evaporate when things move to the cloud. What’s more, clouds mean new tasks for IT -- things like provisioning, managing policy, and so on.

IT costs: Variable

Tied to delivery; a measure of efficiency

Needs to be less than the resulting revenue or you’ll be called a cost center

Enterprises underestimate the true costs of service delivery

Barry Lynn of 3Tera

0

125

250

375

500

Enterprise Cloud provider

Ser

vers

per

sys

adm

in


The variable costs are where clouds are really strong. This stuff is the costs that increase with service delivery volumes. Cloud operators can handle 500-1000 servers per person (they have to!) and completely automate everything. They also focus on cost measurement and accounting, which is a luxury for many enterprises but a necessity for clouds. Management software is an afterthought for many IT departments; but it’s a competitive advantage for cloud operators.

Clouds might seem pricey today

£0

£7,500,000

£15,000,000

£22,500,000

£30,000,000

Start up cost Year 2 Year 4 Year 6 Year 8 Year 10

Data Centre Cloud

2009 IDC analysis of running 100% of a big enterprise’s IT in-house vs on-demandUsed with permission. Copyright (c) IDC

Even with 3-yearrefresh cycles of 30%DC remains cheaper

Final score:DC: £15M

Cloud: £26MAfter year 3,cloud costsexceed DC


A naive look at clouds (intentionally naive, we should point out) from IDC says that clouds are expensive

http://www.linux.com/news/featured-blogs/168-brian-proffitt/147898-cloud-computing-too-costly-in-the-long-term


But we’re deluded

£0

£12,500,000

£25,000,000

£37,500,000

£50,000,000

Start up cost Year 2 Year 4 Year 6 Year 8 Year 10

Data Centre Cloud

2009 IDC analysis of running 100% of a big enterprise’s IT in-house vs on-demandUsed with permission. Copyright (c) IDC

Cloud costs are dynamicso even if bad decisions

are made initially, capacitycan be ramped up linearly

Year 6 requires build-out for new facility +expensive refresh due

to limited spaceDC reaches spacecapacity in year 3,

50% refresh to high-end servers needed


Remember: Google gets 38% server utilization, with insane effort. So this is likely unattainable. What’s more, cloud providers are competing, and may (assuming interoperability of some kind) reduce their costs, too.



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


Just how big are clouds? 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 HotmailIn 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.



Are you negotiating with cities & power companies?

“...Microsoft pays an annual utility bill just north of $13 million, which translates to just over 3.8 cents/kwh as opposed to 5.7 cents/kwh for the ELP rate...”

http://www.virtual-strategy.com/Features/Microsoft-and-Google-Cloud-Computing-Dominance-Through-Renewable-Energy/-5.html


Consider a San Antonio, Texas facility from Microsoft. http://ccr.sigcomm.org/online/files/p68-v39n1o-greenberg.pdfif the data center takes the full load of 44 megawatts at a 90% load factor, Microsoft pays an annual utility bill just north of $13 million, which translates to just over 3.8 cents/kwh as opposed to 5.7 cents/kwh for the ELP rate. To prove that these assumptions are in the ballpark, public documents from another SLP customer in the San Antonio area reveal that its overall utility rate is 3.7 cents per kwh.



Three laws


http://www.galleries.com/minerals/elements/silicon/silicon.htm


First, consider silicon. Look at the cost/capacity tradeoff of computing, as described by Moore’s Law.



http://www.flickr.com/photos/monstershaq2000/2162386152/Wednesday, November 18, 2009

Then think about another form of sand – glass. Then look at the cost/capacity tradeoff of networking. Netflix pays $0.06 to send a movie over the Internet today, and will pay $0.03 next year.

http://www.flickr.com/photos/monstershaq2000/2162386152/

http://www.flickr.com/photos/monstershaq2000/2162386152/

http://www.flickr.com/photos/spacepleb/801902842/Wednesday, November 18, 2009

Finally, think about iron. And consider storage – which is dropping just as quickly.

http://www.flickr.com/photos/spacepleb/801902842/

http://www.flickr.com/photos/spacepleb/801902842/

The cloud trifecta


This trifecta of computing, bandwidth, and storage are driving costs down dramatically. Every time Google builds a data center, it can do more than the last one did.

Everything will be free.*

*Some restrictions apply.


Cloud computing is on a breakneck ride to zero marginal costs because of sand, iron, and glass. This means the raw materials of clouds will be free -- or too cheap to bill -- for many of us. (if you want to know more about this, see Chris Anderson’s Free)

So you won’t be building your own data centers

70% of the Global 1000 must

“Modify their data center facilities significantly” by 2012

Increase energy from 35 to 70 watts/sq. ft (sometimes up to 300 watts)

Gartner says to

Monitor energy use

Quantifying all capital and operation changes needed

Deploy virtualization and workload management tools

http://www.virtual-strategy.com/Features/Microsoft-and-Google-Cloud-Computing-Dominance-Through-Renewable-Energy.htmlWednesday, November 18, 2009

Energy is a huge issue. Even Gartner’s recommendations for saving energy will only temporarily solve the problem at hand, because energy costs will have to be cut by more than 50% in order to keep up

http://www.virtual-strategy.com/Features/Microsoft-and-Google-Cloud-Computing-Dominance-Through-Renewable-Energy.html

http://www.virtual-strategy.com/Features/Microsoft-and-Google-Cloud-Computing-Dominance-Through-Renewable-Energy.html


This is a GM prototype of a car that drives itself. It’s actually green technology. Know why? Because in the end, the greenest thing you can do for a car isn’t fuel: It’s making it not crash as much. If cars didn’t crash, we could get rid of most of their weight, which in turn would make them efficient. It turns out that IT is the key to efficiency.

If you’re using others’ servers, you’ll get VMs.


Let’s resign ourselves to the fact that we’ll get hardware from someone else (there’s a reason Intel is investing in cloud companies like Joyent, remember.) So how will that work? You’re going to get virtual machines, because that’s how the operators keep the costs low. IT and management, not cheaper machines, is the key to efficiency.

Reality:Clouds are part of the IT toolbox



Clouds let IT focus on things that actually add business value. Very few companies have a competitive advantage because of their hardware infrastructure.


And they eliminate many of the tasks you really didn’t want to do anyway.

Reality:Security is a pro and a con.


New kinds of attackThird-party access

Traveling across wiresShared infrastructure

The best infosec peopleMore automationHigh-end tools

Billing to catch use spikes


With hypervisors, other people involved, wires to cross, and so on, there are new vectors for attack. Those have to be compared to the more rigorous standardization that a cloud is likely to subject things to.

http://www.thewhir.com/web-hosting-news/102309_IT_Firms_Skeptical_About_Cloud_PEER_1_Study

Reason to avoid clouds23%

No opinion34%

Reason to move to clouds43%


In a study commissioned by PEER 1, users reported security as a big impediment to cloud adoption -- and a reason for doing so!"



Reality:It’s about services, not machines


While virtual machines were easy to understand and embrace, we’ve finally realized that it’s the services, not the machines, that matter.

Embracing clouds means giving up architectural opinions.


SOA may matter more than virtualization

http://www.techcrunch.com/2009/04/16/mckinseys-cloud-computing-report-is-partly-cloudy/

S3

EC2

SimpleDB

CloudFront

SQS

RDB

Elastic MapReduce

Loadbalance

I used to think here...

...now I think out here


What started out as pay-by-the-drink storage (S3) and computational processing (EC2), now includes a simple database (SimpleDB), a content delivery network (CloudFront), and computer-to-computer messaging (SQS). Most recently, Amazon added a web-scale data processing engine with Amazon Elastic MapReduce. (It is a framework for accessing data stored in file systems and databases). It allows developers leverage Amazon’s cloud computing power by creating applications which process huge reservoirs of data (conveniently stored in Amazon S3) in parallel.Developers become systems integrators



Reality:Clouds are ubiquitous.


Cloud processing is everywhere

Cloud Encounters, Peter van Eijk, digitalinfrastructures.nl ! !

"#$$%&'!'()%!'#!*!+($,-%!

.#+'%/!+('%!($&0%*+%+!

1('.!/(+'*$&%2!

"#$$%&'!'()%!'#!'.%!

3##,-%!455!6$,($%!

&-#7/!/#%+!$#'2

"-#7/+!&*$!8%!%9%0:1.%0%; <; =;; =<; >;; ><; ?;; ?<;

$->

$-@

/%

A0

/B

7B

A0

7+C$:

7+CA-

7+C+A

+,

.B

$D

!"#$%"&$#'()%*%$"#

!$++$),-"#.)(%"(-"##,-%

*55!%$,($%;E

A-*'!+('%!2$-

"-#7/!.*+!

4+(*$!

50%+%$&%

"-#7/!.*+!

670#5%*$!

50%+%$&%

F%1!G%*-*$/!

(+!0%*--:!A*0!

*1*:!A0#)!

670#5%

! !

"#$%&'(!%)*!+,#$-

!"##$%$&#'()**+*$,(-$.(//01/21345//)**+*$,(#(6$$6#"(-$.(

)**+*$,(#(6$$6#"(-$.(/01/3/789(:;(<79(<=<

)**+*$,(#(6$$6#"(-$.(/01/3/789(:;(<>;(<=<

./0!,##1$23!4#5!)*,,#6#5,-782232#%79#:!85*!

,#98%&#'!8'-!%&:*!-*2*'-*'%

0?/)''&"++@"+A /B$-),C$D

;<=7>?7@;=7@A@

!

!

!B'%6*52C!D*,(&$:

!E-*338C!F158&'*

!E3,#C!/#568G

;<=7>?7@H?7@A@

!

!

!B:3%*5-8:;C!/*%)*5,8'-3

!I8&48C!J358*,

!K581#6C!L#,8'-

;<=7>?7@?H7@A@ !M$:N8&C!J'-&8

;<=7>?7;;?7@A@ !+)&98(#C!F707B7

;@O7;H=7?=7@A@

!

!

!

!

!

!

!

!B:3%*5-8:C!/*%)*5,8'-3

!+#2*')8(*'C!.*':851

!.$N,&'C!J5*,8'-

!P5#'&'(*'C!/*%)*5,8'-3

!Q#)8''*3N$5(C!0#$%)!B45&98

!MR'9)*'C!P*5:8'G

!0%#91)#,:C!06*-*'

!S$5&9)C!06&%T*5,8'-

OO7@<;7@@7@A@ !M*,N#$5'*C!B$3%58,&8U

V;7@A7;<H7@A@

!

!

!

!

!

!

!B$91,8'-C!/*6!S*8,8'-

!I#'(!K#'(C!+)&'8

!/8(8'#C!Q828'

!08'!W58'9&39#C!F707B7

!0)8'()8&C!+)&'8

!0&'(82#5*C!0&'(82#5*

!0G-'*GC!B$3%58,&8

VA7@;?7H=7@A@

!

!B:3%*5-8:HC!/*%)*5,8'-3

!L85&3C!W58'9*

VA7@;?7AH7@A@

!

!

!

!

!+#,#('*C!P*5:8'G

!X&,,*C!W58'9*

!X#'-#'C!F'&%*-!K&'(-#:

!M#39#6C!"$33&8

!L8-$8C!J%8,G

VA7@;?7A?7@A@ !B$3%&'C!F707B7

VA7@;?7AV7@A@ !W,#5&-8C!F707B7

VA7@;?7O?7@A@ !08'%8!+,858C!F707B7

! !

"#$%&'(!%)*!+,#$-

!"##$%$&#'()**+*$,(-$.(//01/21345//)**+*$,(#(6$$6#"(-$.(

)**+*$,(#(6$$6#"(-$.(/01/3/789(:;(<79(<=<

)**+*$,(#(6$$6#"(-$.(/01/3/789(:;(<>;(<=<

./0!,##1$23!4#5!)*,,#6#5,-782232#%79#:!85*!

,#98%&#'!8'-!%&:*!-*2*'-*'%

0?/)''&"++@"+A /B$-),C$D

;<=7>?7@;=7@A@

!

!

!B'%6*52C!D*,(&$:

!E-*338C!F158&'*

!E3,#C!/#568G

;<=7>?7@H?7@A@

!

!

!B:3%*5-8:;C!/*%)*5,8'-3

!I8&48C!J358*,

!K581#6C!L#,8'-

;<=7>?7@?H7@A@ !M$:N8&C!J'-&8

;<=7>?7;;?7@A@ !+)&98(#C!F707B7

;@O7;H=7?=7@A@

!

!

!

!

!

!

!

!B:3%*5-8:C!/*%)*5,8'-3

!+#2*')8(*'C!.*':851

!.$N,&'C!J5*,8'-

!P5#'&'(*'C!/*%)*5,8'-3

!Q#)8''*3N$5(C!0#$%)!B45&98

!MR'9)*'C!P*5:8'G

!0%#91)#,:C!06*-*'

!S$5&9)C!06&%T*5,8'-

OO7@<;7@@7@A@ !M*,N#$5'*C!B$3%58,&8U

V;7@A7;<H7@A@

!

!

!

!

!

!

!B$91,8'-C!/*6!S*8,8'-

!I#'(!K#'(C!+)&'8

!/8(8'#C!Q828'

!08'!W58'9&39#C!F707B7

!0)8'()8&C!+)&'8

!0&'(82#5*C!0&'(82#5*

!0G-'*GC!B$3%58,&8

VA7@;?7H=7@A@

!

!B:3%*5-8:HC!/*%)*5,8'-3

!L85&3C!W58'9*

VA7@;?7AH7@A@

!

!

!

!

!+#,#('*C!P*5:8'G

!X&,,*C!W58'9*

!X#'-#'C!F'&%*-!K&'(-#:

!M#39#6C!"$33&8

!L8-$8C!J%8,G

VA7@;?7A?7@A@ !B$3%&'C!F707B7

VA7@;?7AV7@A@ !W,#5&-8C!F707B7

VA7@;?7O?7@A@ !08'%8!+,858C!F707B7




Reality:He who owns the storage, owns the computation.


It’s all about the data


Data is the most important part of a cloud. MS fellow Jim Gray, in his 2003 analysis, said that compared to the cost of moving bytes around, everything else is effectively free.The economics of storage services like Flickr don’t hold up well to churn.

58

14 minutes6172001,920,0009600OC 192

2.2 hours1000Gbps

1 day100100 Mpbs

14 hours97631649,000155OC3

2 days2,01065128,00043T3

2 months2,4698001,2001.5T1

5 months360117500.6Home DSL

6 years3,0861,000400.04Home phone

Time/TB$/TBSent$/MbpsRent

$/monthSpeedMbpsContext

Source: TeraScale Sneakernet, Microsoft Research, Gray et. al

Moving data’s not easy


One dirty secret of cloud computing is that from a cost perspective, everything’s pretty much free compared to the price of moving bytes around. This means you can no more build an app that’s “half cloud” than you can be “half pregnant.”


Reality:The big guys are here.


Legitimacy, at the cost of FUD and a slow-down of experimentation because big vendors can promise.

IBM

Replacing Global Services

Architecture defines clouds


Microsoft

SaaS cannibalizes existing software addiction


AT&T

It’s about data centers and connectivity


We’re stalling.


What’s the consensus?(the no clear direction problem)


No straight answer

0% 25% 50% 75% 100%

82%“In trial, implementation, or use of public clouds”

F5 Networks

47%“Won’t consider the cloud in

next 12 months”

ITI38%

“Unsure about adopting cloud services”

CIO.com8%

“Implementing cloud services”

29%“No interest in the cloud”

60%“Actively researching (cloud on

radar)”


What’s included?(the roofrack problem)


http://www.thule-car-roof-boxes.co.uk/pictures/roof-box-with-roof-rack.jpgWednesday, November 18, 2009

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

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



Too much choice(the wait it out problem)


http://www.flickr.com/photos/jumphigh/1565967960/


Jim Sivers reminded me recently of the paradox of choice. http://sivers.org/jamSheena Iyengar has been studying choice. For her research paper, “When Choice is Demotivating”,They set up a free tasting booth in a grocery store, with six different jams. 40% of the customers stopped to taste. 30% of those bought some.A week later, they set up the same booth in the same store, but this time with twenty-four different jams. 60% of the customers stopped to taste. But only 3% bought some!



http://sivers.org/jam

0

15

30

45

60

Stopped to taste Actually bought some

6 jams 24 jams


Both groups actually tasted an average of 1.5 jams. So the huge difference in buying can’t be blamed on the 24-jam customers being full. Lessons learned:Having many choices seems appealing (40% vs 60% stopped to taste)Having many choices makes them 10 times less likely to buy (30% vs 3% actually bought)Surgeon Atul Gawande found that 65% of people surveyed said if they were to get cancer, they’d want to choose their own treatment. Among people surveyed who really do have cancer, only 12% of patients want to choose their own treatment.




35%

65%

Choose their own treatmentHave others choose

87%

13%

General population Cancer patients


Surgeon Atul Gawande found that 65% of people surveyed said if they were to get cancer, they’d want to choose their own treatment. Among people surveyed who really do have cancer, only 12% of patients want to choose their own treatment.



Striking a balanceHow we move ahead


Focus on service architectures


Composed designs replace component architectures

High performance

Compliant

“Embarrassingly distributed”

Bursty/seasonal

Resilient & highly available

Scalable but eventually consistent


Have a hybrid/private strategy


“Private” and “hybrid” concepts emerge

Private cloud: On-premise infrastructure with cloud-like properties

Hybrid cloud: Policy-driven combination of on-premise and on-demand components

Virtual private cloud: On-premise privacy on someone else’s machines


Always on premise

Private

Compliance-enforced

Need to track and audit

Legislative

Data near local computation

Can be done anywhere

Testing

Training

Prototyping

Batch processing

Seasonal load

Always in cloud

Partner access

Proximity to cloud services (storage,

CDN, etc.)

Massively grid/parallel (genomic,

modelling)Lo

ad/p

ricin

g en

gine

Polic

y en

gine

Virtual machine(infrastructure cloud)

Compute task(service cloud)


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.

Reconsider what’s possible


Better economics

Pay-per-use pricing

No capital investment

No long term contracts

Ideal for spiky applications

Optimized for Web 2.0 apps

Scales easily*

James Staten, Forrester* Easy scaling may not be included

Developer empowerment

Self-service portal

Infrastructure managed by cloud provider

Developer-ready framework

For all levels of developers

Cheap test and dev

One button deploy


Clouds promise a lot: James Staten of Forrester loves clouds, not only for the economies of scale they offer, but also for the way in which they empower developers to build and experiment by speeding up the IT cycle time.

Minimize maintenance costs Cooling Electricity Servers maintenance, backups, etc.

Elasticity and scalability Massive scale leads to true economies of scale Eliminate need to build for infrequent peaks Make capacity available on demand

Ops cost reduction Flat data sets Streamlined data management Data availability - enabling information generation

DR cost reduction

Do new things Perform mission tasks that were not able to achieve otherwise New tools like Hadoop and Map Reduce allows for amazing processing

Speed up the organization Faster, cheaper innovation Transform how gov does business Prototyping enablement

Publish databases Reduce start-up

Work differently Realtime collaboration Ubiquitous access to unlimited amount of computing power Ubiquitous access to unlimited amount of storage

Enterprise tech Disruptive tech

Rod Fontecilla, Booz, Allen, HamiltonWednesday, November 18, 2009

•60 seconds per page

•200 machine instances

•1,407 hours of virtual machine time

•Searchable database available 26 hours later

•$144.62 total cost

Desktop EC2

Pages 17,481 17,481

Minutes/page 1 1

# of machines 1 200

Total minutes 17,481

Total hours 291.4 26.0

Total days 12.1 1.1


One of the most interesting uses of cloud computing is time dilation. Okay, not really, but close: The Washington Post, 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.

Two kinds of data centerReally big data centers for really big problems

Tens of thousands or more servers

Tens of Mega-Watts of power at peak

Aimed at massive data analysis applications (search indexes, social media, genomics)

Variety of workloads

Huge amounts of fast RAM

Massive numbers of CPU cycles

High-volume disk I/O bandwidth

Requires lots of communication between servers, so network propagation affects computation speed

Micro data centers for “embarrassingly distributed” applications

Thousands of servers

100s of kilowatts.

Aimed at highly interactive apps (Interactive, office productivity apps)

Placed close to populations to minimize network transit impact

The Cost of a Cloud: Research Problems in Data Center NetworksAlbert Greenberg, James Hamilton, David A. Maltz, Parveen Patel Microsoft Research, Redmond, WA, USA


Think about risk in the context of openness


Sharing > Protection

Drew Bartkiewicz, The Hartford, quoted in Unseen Liability


According to Drew “Bartievitz” of the Hartford, there’s a shift in the value of information assets underway.

Embrace cloud technology even if you don’t use clouds


An example: eventual consistency


Clouds as peripherals

Clouds as IT strategy


Most of the enterprises I’ve spoken with use clouds as peripherals. In the same way we used to plug peripherals into our computers, enterprises plug clouds into their IT. They might have it for backup, or messaging, or content delivery, or for a specific business process. But to really harness the power of cloud computing, enterprises need to embrace it as more than just a bunch of things to plug into the organization. It needs to become part of their strategy.

Support

Onboarding

Contracts

Policies

UI

API

Language

Protocol

ComputingStorageDelivery


You can target a vertical. There are always ways to specialize within a specific industry. This isn’t about the computing -- as we’ve seen, this is a commodity. But you can <click> focus on a specific language or protocol, <click> UI or API, <click>, set of contracts and policies, <click>, or even support and onboarding. Every industry or target customer has specific needs. Maybe it’s the AMQP protocol, or HTML 5 optimization, or JavaScript code, or long contract terms, or high-touch support for small businesses.

Worry about user experience, billing


What user experience can you afford?


Delay (in seconds)Traffic (requests/sec)

Capactity (# of machines)=


There’s a basic equation in computing. Performance equals traffic divided by capacity. Put another way, more users and something gets slower. More machines and something gets faster.


This is an example of that relationship. As usage grows, performance gets worse.


Normally, IT adds capacity to a system and things get better.

Delay (in seconds)Traffic (requests/sec)

Capactity (# of machines)=

∞


But when if the capacity is infinite?


Then you set user experience (“under 1 second”) and the elastic platform adds capacity as needed. The only problem? The bill at the end of the month!

0

25

50

75

100

http://developer.amazonwebservices.com/connect/thread.jspa?messageID=150461http://www.google.com/insights/search/#q=%22Cloud%20computing%22&cmpt=q

2008 2009 2010 2011 2012What is

the cloud?Why

should I use it?

How do I use it?

What new things are possible?

What must I still run in-house?

Taxonomies & layers

ROI, TCO, business

cases

Designs & best

practices

Business strategy

Policy & standards


Here are my predictions for the next few years, and what you’ll see at conferences, in the press, and in the boardroom.





Different Clouds for Different FolksIan Knox (Skytap), Lew Moorman (Rackspace), Sesh Murthy (IBM), Scott Ryan (Asankya)

The Risks of On-Demand ComputingAnthony Arnott (Trend Micro), Drew Bartewicz (The Hartford), Marc Lindsey (Levine, Blaszak, Block & Boothby LLP)

What's Working, What's Not: A Report from Cloud Adopters

Colin Hostert (Grooveshark), Geir Magnusson (Gilt), Dominic Preuss (FiLife), Vince Stephens (Taser)

Cloud Interoperability: Do We Need It? What Would it Look Like?

Chris Brown (Opscode), Jason Hoffman (Joyent), John Willis (Zabovo)

Cloud Computing RoadmapsKen Comee (Cast Iron Systems), Morris Panner (OpenAir), Randy Bias (Cloudscaling)
