McKinsey Cloud Matters

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Last Modified 4/8/2009 9:13:54 PM Eastern Standard Time

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WORKING DRAFT

Clearing the air on cloudcomputing

CONFIDENTIAL

Discussion Document

March 2009

CONFIDENTIAL AND PROPRIETARYAny use of this material without specific permission of McKinsey & Company is strictly prohibited.


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1|McKinsey & Company

For I should not have rightly discovered thingscelestial if I had not suspended the intellect and the

thought in a subtle form with its kindred air. But if,being on the ground, I should never havediscovered them.

Aristophanes "The Clouds"


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Context and objectives of this presentation

The purpose of this report is to focus the nascent cloud industry and its consumers onsetting realistic expectations by taking a hype free approach starting with the mostbasic question of what a cloud actually is

Our specific objectives include

Proposing an industry-standard definition of cloud computing including what makes it uniqueand excitingIdentifying the types of customers that should be early adoptersthose that can benefit from

existing and planned commercial offeringsUnderstanding barriers that prevent large-scale adoption by corporations and government

entities that represent the bulk of IT spending

Using clouds for computing tasks promises a revolution in IT similar to the birthof the web and e-commerceMuch lower costFaster time to marketGreat opportunities for creating new sources of value

While it has great potential, many of the claims being made about cloud computing havelead some to the point of irrational exuberance and unrealistic expectations


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|McKinsey & Company 3

Key findings

Cloud computing is approaching the top of the Gartner Hype-cycle

Getting an industry fix on the definition of what a cloud

actually is would be a good first step and we propose onefor adoption here

Users, hardware vendors and service suppliers can takespecific steps to ensure the successful adoption of cloudtechnologyand prevent it from getting stuck in the trough ofdisillusionment

Clouds already make sense for many small and medium-sizebusinesses, but technical, operational and financial hurdleswill need to be overcome before clouds will be used

extensively by large public and private enterprises

Rather than create unrealizable expectations for internal clouds, CIOsshould focus now on the immediate benefits of virtualizing server storage,network operations, and other critical building blocks


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Cloud computing has tremendous promise

Pay-per-use billingdramatically reducesupfront costs

Enterprises of allsizes can seamlesslyscale their services incorrelation with client

demand

Faster timeto market

Creation ofnew valuedrivers

Cloud computing can lowerIT barriers to innovation and

increase interoperabilitybetween disjoint

technologies. HPsCloudPrint service is an

example

Clouds can provide analmost immediateaccess to hardwareresources

No upfront capitalinvestments for users

Lower upfrontIT costs

Easier toscale-out


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Cloud is quickly becoming top-of-mind in the IT world

Gartner; CIO magazine; IDCSOURCE:

The current U.S. economicwoes will only drive moreenterprises to consider andadopt cloud offerings.Spending on IT cloudservices will hit $42 billionby 2012

58 percent say cloudcomputing will cause a

radical shift in IT and 47percent say they're alreadyusing it or activelyresearching it

Since the publishing ofthe 2008 cycle we have

seen a tremendousincrease in coverage andtalk about cloud

computing.

2008 Gartner IT hype cycle


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|McKinsey & Company 6SOURCE: Press analysis

The tremendous buzz around clouds is being further fueled by intenseanalyst and media speculation

no less influential than e-

business (Gartner, 2008)

Cloud computing achieves a quicker

return on investment (Lindsay Armstrong of salesforce.com, Dec 2008)

economic downturn, the appeal of

that cost advantage will be greatly

magnified" (IDC, 2008)

revolution, the biggest upheaval

since the invention of the PC in the

1970s [] IT departments will have

little left to do once the bulk ofbusiness computing shifts [] into

the cloud (Nicholas Carr, 2008)

Not only is it faster and more flexible, it is

cheaper. [] the emergence of cloud models

radically alters the cost benefit

decision (FT Mar 6, 2009)

The economics are compelling, withbusiness applications made three to five times

cheaper and consumer applications

five to 10 times cheaper (Merrill Lynch,May, 2008)


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and seems to be following the familiar IT hype pattern (for CIOs at least)

SOURCE: McKinsey & Company

Cloud computing can divert

IT departments attentionfrom technologies that canactually deliver sizeablebenefits; e.g., aggressivevirtualization

Initial excitement around a

new technology grows rapidlyinto unrealistic expectations.Early on, the mainbeneficiaries of emergingtechnologies are usually thevendors, not the enterprise

users

Cloud computing has shown

great promise for start-upsand pet projects for largeorganizations. However, it isnot ready to help with the bigchallenges of big companies

Works well in theory The Gold rushLack of interest in

technologies that work

Proble

m

HYPE


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Key findings









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Why is it important to get a fix on clouds?


Allows participants in cloud discussions to share a common

understanding of what is meant by clouds

A rigorous definition allows CIOs to be analytical in their decisionmaking and to make more informed investment decisions

Conversely, clarity also allows technology and service providers tobuild meaningful product, marketing, and sales strategies thattranslate into real value for their customers

Allows an industry to begin moving forward with standards topromote interoperability amongst cloud products


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A recent study has found 22+ definitions of clouds

SOURCE: A Break in the Clouds: Towards a Cloud Definition, 2009; Vaquero, Rodero-Merino, Caceres, Linder

Many definitionsexist on cloud

computing


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Two notable attempts at a rigorous definition that captures keycharacteristics

Clouds are a large pool of easily usable and accessible virtualizedresources (such as hardware, development platforms and/or services).These resources can be dynamically reconfigured to adjust to a

variable load (scale), allowing also for an optimum resource utilization.This pool of resources is typically exploited by a pay-per-use model inwhich guarantees are offered by the Infrastructure Provider by meansof customized SLAs. - Vaquero et al

SOURCE: A Break in the Clouds: Towards a Cloud Definition, 2009; Vaquero, Rodero-Merino, Caceres, Linder

Above the Clouds: A Berkeley View of Cloud Computing, 2009; UC Berkeley Reliable Adaptive Distributed Systems Laboratory

Cloud Computing refers to both the applications delivered as servicesover the Internet and the hardware and systems software in thedatacenters that provide those servicesThe datacenter hardware andsoftware is what we will call a CloudCloud computing has thefollowing characteristics

1. The illusion of infinite computing resources

2. The elimination of an up-front commitment by Cloud users3. The ability to pay for use as needed UC Berkeley RAD Labs

Does not distinguishcloud services fromclouds and does notprovide definitiveeconomic implications

Does not emphasizeabstraction ofinfrastructure explicitly


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How we have defined a cloud


Definition: Clouds are hardware-based services

offering compute, network and storage capacity where:

Hardware management is highly abstracted from thebuyer

Buyers incur infrastructure costs as variable OPEX

Infrastructure capacity is highly elastic (up or down)3

2

1


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Definition: Clouds are hardware-based servicesoffering compute, network and storage capacity where:




2

1


Characteristic: Enterprisesincur no infrastructure capitalcosts, just operational costs andoperational costs are incurred ona pay-per-use basis, with nocontractual obligations

Characteristics of clouds


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2

1




Characteristic: Capacity can

be scaled up or downdynamically, and immediately,which differentiates fromtraditional hosting serviceproviders


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2

1





Characteristic: The

underlying hardwarecan be anywheregeographically



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2

1





Characteristic: The

underlying hardwarecan be anywheregeographically

Characteristic: Architecturespecifics are abstracted. Inaddition, run in multi-tenancymode with multiple usersaccessing the infrastructuresimultaneously



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Many cloud services are confused as clouds

Clouds

A true cloud has tocomply with all threekey requirements. It hasto abstract the

underlying hardwarefrom the buyer, beelastic in scaling todemand and bill buyerson a pay-per-use basis

Infrastructure capacity ishighly elastic (up or down)

Buyers incur infrastructurecosts as variable OPEX

Hardware management ishighly abstracted from thebuyer

Cloud Services

A cloud service onlycomplies with two keyrequirements: It is aservice where the

underlying infrastructureis abstracted and canscale elastically. Itcould run on top of acloud, although it is notrequired to (e.g., Saas)


3

2

1


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Examples of clouds and cloud services

Cloud examples Cloud servicesexamples


Infrastructure capacity ishighly elastic (up or down)

Buyers incur infrastructurecosts as variable OPEX

Hardware management ishighly abstracted from thebuyer

3

2

1


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Key findings









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Cloud offerings currently are most attractive for small and medium-sizedenterprises

T

otalCPU/mon

thcost

SizeLarge

enterprise

SME

Price for

public

cloud

consumers

Amazon Web Site; McKinsey & CompanySOURCE:

Clouds are very cost effective for SMEs

and most customers ofclouds are small businesses


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There are significant hurdles to the adoption of cloud servicesby large enterprises

FinancialCurrent cloud computing offerings are not cost-

effective compared to large enterprise data centers1

TechnicalSecurity and reliability concerns will have to bemitigated and applications re-architected

2

OrganizationalThe IT supply and demand organizations will have toadapt to function in a cloud-centric world

4

OperationalBusiness perceptions of increased IT flexibility andeffectiveness will have to be properly managed

3

Pr

iority


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Current cloud computing services are generallynot cost effective for larger enterprises

Windows

Linux

On-demand

Pre-pay

SOURCE: Amazon Web Services; McKinsey & Company

1 Total Cost of Assets for typical data center: 10% utilization, $20M/MW for facility, $.1kW-hour, $14K/Server (2 CPU, 4 core)

Most EC2 options are more

costly than TCO for a typicaldata center

Enterprises could get lowerTCO through pre-payagreementsbut only for

Linux systems

EC2 Instance Size

$180

$20

$60

$100

$140

Small Medium Large XL

economical

uneconomical The thin green lineTCA for typical data center1 around

$45/month for CPU equivalent

EC2 monthly CPU equivalent price options (virtual cores)$


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However, for smaller compute equivalents, todaysclouds may be attractive for some computing work

Not clear compute units arethe right measure of DCequivalency, as theirequivalent is several years

old Again, pre-pay Linux

agreements show thegreatest promise, with someEC2 options pricedsignificantly lower than TCA

for typical data center

1 Total Cost of Assets for typical data center: 10% utilization, $20M/MW for facility, $.1kW-hour, $14K/Server (2 CPU, 4 core)

2 One EC2 Compute Unit provides the equivalent CPU capacity of a 1.0-1.2 GHz 2007 Opteron or 2007 Xeon processor

Windows

Linux

On-demand

Pre-pay


$180

$20

$60

$100

$140

EC2 Instance Size

Small Medium Large XL

EC2 monthly CPU equivalent price options (compute units2)$

Again, pre-pay Linux

agreements show thegreatest promise, with someEC2 options pricedsignificantly lower than TCOfor typical data center

economical

uneconomical The thin green lineTCA for typical data center1 around

$45/month for CPU equivalent


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The cost of cloud must come down significantly foroutsourcing a complete data center to make

economic senseCPU/month TCODollars

1 Cost for comparable configuration 75% of EC2 Large Standard Windows configuration2 Typical CPU/month cost for 3GHz dual-core Xeon Windows-based servers3 Estimated based on 10% labour savings from moving to a third-party cloud provider

Assumes migration of totalWindows and non-console Linuxcapacity for entire data center

Based on comparable hardwareconfigurations, current pricing forcloud computing services issignificantly higher than the

CPU/month TCO achievable indata centers today.

The key factor is that the majorityof servers that can be migratedare Windows servers

107

432

150

CPU/month costof typical datacenter2

963

2701

Cost of movingto Amazon EC2

366

+144%

Labor costs

Non-labor costs

DISGUISED CLIENT EXAMPLE



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There is a 10-15% total infrastructure labor basesaving potential if moving whole data center to cloud

SOURCE: Client Data; McKinsey & Company

116

1

40

53

673

87

20

257

131

52

45

164

65

116

1

40

53

505

87

8

257

107

52

45

115

63

Management

Real Estate

Quality Assurance

Application Support/Dev

Architecture

Business Analysis

Client Services

DB Admin

Desk Top Support

Facilities

Help Desk

IT Administrator

Telecommunications

Total starting FTEs

Total FTEs after migration

FTEs by role group

DISGUISED CLIENT EXAMPLE

1,448

1,704

Total starting FTEs Total FTEs aftermigration

-15%

Total FTEs

Approx 10-15% of headcount can bereduced by migrating capacity over tothe cloud

Most of this headcount comes fromfacilities and touch labor roles

Consequently, labor savings aremodest, but not insignificant


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Many enterprise (necessarily or unnecessarily) set their SLAs uptimes at99.99% or higher, which cloud providers have not yet been prepared to match

July 20, 2008

Feb 15, 2008

October 2007

October 2006

Amazons cloud outages receive a lot of exposure

SLAs expressed in Monthly Uptime Percentages*

McKinsey & Company; Hyperbic Blog; UC Berkeley RADS Lab, CNet, eWeek; Amazon Web SiteSOURCE:

Failure due to stranded zombies,lasts 5 hours

Authentication overload leads totwo-hour service outage

Service failure lasts two days

Security breach where users couldsee other users data

Amazon EC299.95%

Amazon S399.9%

IT shops do not always deliveron their SLAs but their failuresare less public and theircustomers cant switch easily

It is not clear that allapplications require such highservices levels

and their current SLAs dont match those of enterprises*


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Key findings









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Large enterprises can achieve server utilization rates similar to thosecloud providers are achieving from their platforms

McKinsey & Company;Google/ Barroso & HolzleSOURCE:

38

Typical Utilization

Quickly achievable

Generally achievable withaggressive virtualization

Best-in-Class withaggressive virtualization

Best-in-class withcloud (Google)

35

25

18

10

Average server utilization rates

Most of the gains are achievablethrough standard virtualization

(~250% vs ~280%) However, even if cloud technolo-

gies were well implemented, mostcompanies would not achieve best-in-class due to scale constraints

Public clouds have a great dealmore flexibility to drive higherutilization rates due to greatervariation in capacity requirements,and the use of standard platforms,which allows for better matching ofresources

+280%

+150%

+250%

+80%


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Key value drivers

and, by adopting data center best practices, candrive down server TCO by more than 50%

72.00Typical CPUequivalent cost1

21.50 Virtualization

2.00TCO

transparency

19.00 Lean

1.50 Service catalog

Achievable CPUEquiv. Cost

28.00

-61%

Total monthly cost per CPU equivalent$, including labor

1 TCO for typical data center: 10% utilization, $20M/MW for facility, $14K/Server (2 CPU, 4 core), PUE of 2.0, $.1/kW-hour, facility utilizationof 65%, 30-40 Server/FTE ration, $100K/year/FTE, includes IT support and facility support labor

ILLUSTRATIVE

Drive utilization levels to 25% by leveraging virtualization,stacking, and consolidation

By standardizing on platform, improve facility efficiency 20%and improve IT efficiency 10%, drive down IT capex 10%

Improve labor efficiency by over a third

Drive down demand by 20-30% by creating TCO transparencyat the business level

1

2

3

4



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Publicly-announced privatecloud computing environmentsare not by definition trueclouds because enterprises

cant avoid capitalexpenditures

However, enterprises canrealize significant financialbenefit by implementingaggressive virtualizationprograms

When thinking about clouds,CIOs should think from thebottom of the stack up,whereas providers of cloudservices should take a top-down approach

CIOs should be working the cloud technology stack bottom up; cloudproviders top down

Facilities

IT platform

Virtualizationlayer

Publicly-announced privateclouds are essentially anaggressive virtualizationprogram on top of thetraditional enterprise IT stack


Cloud provider technology stack

Billing

Cloud

Layer

Pricing

Disaster recovery

Mobility

Provisioning

Description

Allows for dynamic provisioning ofvirtual machines

Provides seamless failover capabilities

across geographic regions Provides pricing and billing

functionality

Contains hypervisor and virtual

machines running in hypervisors Also contains OS instances

Highly standardized IT hardware (e.g.,servers, network equipment, storage)

OS that sits on top of hardware

The actual data center facilities Highly efficient and standardized

across regions


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Key findings









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Avoiding the trough of disillusionment will require appropriate actionfrom all players in the cloud computing arena

McKinsey & CompanySOURCE:

Stakehold

ergroups

Develop improved security standards to allay fears of client base Implement technologies that will allow for fine grain billing and management across a

cluster of compute devicesCloud tools andinfrastructure(e.g. HP, IBM)

In the near term, focus on small and medium sized businesses Work on improving uptime rates into the 99.99% range Continue to drive down prices through scale/innovation to increase potential market

Cloud providers(e.g. Amazon,Azure)

Develop an overall strategy for XaaS based on solid business cases not cloud for thesake of cloud

Use modular design in all new and re-architected software to minimize costs when itcomes time to migrate to cloud

Set up Cloud CIO Council to advise industry

Cloud users(e.g. CIOs, CTOs)

The 2000 dot-com bubble provides an extreme example of the dangers of investing in hype

Huge investments were made based largely onhype

Eventually, the inability to generate profits led tothe collapse of most of the boom-time dot-coms

From peak to trough, the NASDAQ-composite lost~ 80% of its value

NASDAQComposite

~-80%

5000

4000

3000

2000

1000

2006200420022000199819961994

NASDAQComposite

~-80%

5000

4000

3000

2000

1000

2006200420022000199819961994


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Will [email protected]

+1 (312) 551-3975

Further information:

ayewill

Media inquiries

Charlie [email protected]+1 (203) 977-6915

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