© Copyright 2011 Hewlett-Packard Development Company, L.P.1

Joe WeinmanWorldwide Lead,

HP Communications, Media, and

Entertainment Business Solutions

joe.weinman@hp.com

CLOUDONOMICS AND THE IMPLICATIONS FOR CSPS, MEDIA, AND ENTERTAINMENT

CTO TELECOM/CIO CME SUMMIT

SEPTEMBER 19, 2011

© Copyright 2011 Hewlett-Packard Development Company, L.P.22

SERVICE PROVIDER CHALLENGES TODAY

NETWORK

SP

• Revenue Growth, Time to Market

• Traffic Growth, CapEx

• Cost Management, Agility

INDUSTRY

• Competition• Regulatory

BACK OFFICESERVICES

© Copyright 2011 Hewlett-Packard Development Company, L.P.33

BACK OFFICEPRIVATE CLOUD

SERVICESCLOUD FORCONSUMERS

CLOUD HAS MULTIPLE APPLICATIONS

SP

NETWORKCLOUD

SERVICESCLOUD FOR

SMBS

SERVICESCLOUD FOR

ENTERPRISES

3RD PARTYCLOUD SERVICES

© Copyright 2011 Hewlett-Packard Development Company, L.P.44

CLOUD BASICS THAT EVERYONE KNOWS…

• Cloud is a brand new technology and business model

• Cloud = Services accessed over the web via a browser

• Cloud = Pay-per-Use = On-Demand

• Large clouds have huge economies of scale & price advantages

• Economies of scale are the key to cloud benefits

• Only the largest providers will thrive and survive

• It is important to replace CapEx with OpEx

• Rational decision-makers will want to save money

• IT is just like electricity: cloud will replace enterprise DCs, hosting

• Cloud cost reduction will drive lower IT spend

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HOW TO QUANTIFY “VALUE”?

1. Unit Cost Reduction

2. Total Cost Reduction

3. Opportunity Cost Reduction

4. Time & Profitability Improvement

5. Market Share / Revenue Growth

6. Customer Experience Enhancement

7. Customer Satisfaction / Loyalty

8. Risk Reduction

9. Competitive Vitality

10. Life or Death – Winner Take All Dynamics

© Copyright 2011 Hewlett-Packard Development Company, L.P.6

PRO FORMA RELATIVE UNIT COSTS OF IT

Consumer TypicalEnterprise

Well-RunEnterprise

Mid-SizedCloud SP

LargestCloud SP

Cost Economies of Scale

Scale-Invariant Costs

Diseconomies of Scale

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PRO FORMA DELIVERED UNIT COSTC

ost

SG&A, Margin,Uncollectibles, …

Consumer TypicalEnterprise

Well-RunEnterprise

Mid-SizedCloud SP

LargestCloud SP

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BUY OR RENT?

CAPACITY

“RENT”

CAPACITY

FROM A

SERVICE

PROVIDER

CUSTOMER

PURCHASE CAPACITY

“RENT” MONEY

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TYPICAL COST CONSIDERATIONS

Physical Hardware

Power & Cooling

Space

Virtualization Software

Networking

Security

Mgt. & Admin. Labor & Tooling

Multitenancy Overhead

Economies of Scale

Learning Curve Effects

Quantization Discontinuities

Statistics of Scale

Utilization Factors

Capacity Planning & Engineering

SG&A

Margin

Uncollectables

Transaction Costs

Switching Costs

GAAP & Tax Laws

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EXAMPLE DEMAND VARIABILITY

Web Traffic Data Courtesy of Alexa, Used with Permission

Excess Capacity

Unserved Demand

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PROVABLY CORRECT

All other things being equal:

1. If cloud services cost less than enterprise IT, then…

…use them

2. If cloud services cost more than enterprise IT, then…

…don’t…

…jump to conclusions, because if demand is “spikier” than the cloud

is “costly,” a pure cloud solution will cost less than a dedicated one

3. If demand has any variation, a hybrid solution is optimal

Joe Weinman, “Time to Do the Math on Cloud Computing,” InformationWeek.com, and“Mathematical Proof of the Inevitability of Cloud Computing.”

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DedicatedCapacity Dedicated

Capacity

DedicatedCapacity

BuildTo

Peak

BuildTo

Baseline

On-DemandCapacity

PureCloud

HybridDelivery

UnservedDemand

On-DemandPay-Per-Use

TYPICAL COMPARISON OF ALTERNATIVESTo

tal C

ost

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RATIONALE FOR HYBRID DELIVERY

STRATEGYCore , Context, Compliance

OPTIMIZATION AND ECONOMICSEnterprise Architecture and Demand Spikiness

PRACTICALITYDue to Legacy Migration Costs

USER EXPERIENCEFor Global Access to Interactive Applications

FREEDOM OF CHOICEDo-It-Yourself and Services Options

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SOME ARCHITECTURE OPTIONS

Cloudbursting Front-End / Back-End

Pure Utility Cloud

CloudEnterprise CloudEnterprise

Mixed-Rate Hosting/Cloud

$ $$ $$$

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DATA REQUIRES CARRIER-GRADE NETWORKS

Enterprise Cloud Provider

Remote Access

Internet

VPN

Optical

Enterprise Cloud Provider

Non-Persistent Session Data

Internet

Enterprise Cloud Provider

Dynamic Migration

Internet

Optical

Enterprise Cloud Provider

Coherent

Internet

OpticalB

A A

B

Source: Joe Weinman, “4 ½ Ways to Deal with Data During Cloudbursts,” GigaOM.com

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CLOUDBURSTING VIA HYBRIDS

Cloud Provider, Utilization - -, Unit Cost++

Enterprise Data Center, Utilization++, Unit Cost - -

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MULTIPLEXING UNCORRELATED BURSTS

Cloud ProviderEnterprise Data Center

Penalty Cost ∝ 1/√n⇒ Penalty Cost 0 as n ∞

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THE STATISTICS OF SCALE

Individual

Random

Demand

Moderate

Aggregation

Of Demand

Aggregate

Demand

At Scale

• Peak near Pro

Forma Maximum

• High Coefficient Of

Variation

• Peak near

Normalized Mean

• Coefficient Of

Variation Approaches

Zero

Mean Capacity

Required

Utilization

100%

© Copyright 2011 Hewlett-Packard Development Company, L.P.19

BEHAVIOR OF 1/√n

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

1 7

13

19

25

31

37

43

49

55

61

67

73

79

85

91

97

103

109

115

121

127

133

139

145

151

157

163

169

175

181

187

193

199

© Copyright 2011 Hewlett-Packard Development Company, L.P.2020

AMDAHL’S LAW

The maximum possible speedup is the inverse of the serial code portion.

S

P

© Copyright 2011 Hewlett-Packard Development Company, L.P.2121

EVOLUTION OF “SAAS”BA

ND

WID

TH

h otmail

h ulu

h ome depot

h alloween costumes

h ollister

h obby lobby

h p

h & m

h urricane earl

h ondaSearch

h|

hertz

heb

hereafter

hell’s kitchen

hershey park

hellcats

heroes

heart

health

heidiSearch

he|

hewlett packard

hewitt associates

hewlett packard printer drivers

hewlett foundation

hewlett packard careers

hewitt school

hewes middle school

hewlett packard customer service

hewescraft

hewes boatsSearch

hew|

INTERACTIVITY

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END-TO-END RESPONSE TIME

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EXAMPLE HTTP RESPONSE TIMES, JAN 2011

0 to 300, (31%)

HTTP Response Time \ ms

300 to 400, (15%)

400 to 500, (13%)

500 to 750, (20%)

>750, (21%)

Source: Marty Kagan, cedexis

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THE COST OF LATENCY

“Users really respond to speed”

Book and Merchandise:

100 ms = “substantial …revenue”

Search: 10 30 results per page 400 ms 900 ms 20% drop in traffic 20% drop in revenue

James Hamilton, http://perspectives.mvdirona.com/2009/10/31/TheCostOfLatency.aspx

© Copyright 2011 Hewlett-Packard Development Company, L.P.2525

THE LAW OF CLOUD RESPONSE TIME

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

Priority of Dispersion

*Joe Weinman, “As Time Goes By: The Law of Cloud Response Time”

T = F + N + PSingle Entities

T = F + N + P__ __√n p

Multiplicity of Nodes and Processors

n = ∛ QN 2

2P( )Minimum Time for a given Quantity of resources

© Copyright 2011 Hewlett-Packard Development Company, L.P.2626

PERFORMANCE VS. COST

Tune YourApplication

Performance

Cost

Performance

Cost

Performance

Cost

Use MoreServers

GeoDisperse

© Copyright 2011 Hewlett-Packard Development Company, L.P.2727

EMERGING ARCHITECTURES/ECOSYSTEM

Enterprise Data Centers Cloud Data Centers

Users

Internet IaaSIntercloud

Intracloud

IP/MPLS/VPLS

OpticalIaaS/

IP, VPNs,Optical

SaaS Intercloud

SaaS/Internet

Mashups/Internet

Agents/Brokers Communities Virtual OperatorsFranchises Alliances

Re-Bursters RegulatorsInsurersPartnershipsBranded Federations

Ratings AgenciesStandards Bodies Trusted 3rd Parties Enabling Vendors

Markets Buyers Co-ops Boutiques/SpecialistsCloud IntegratorsDerivatives

© Copyright 2011 Hewlett-Packard Development Company, L.P.28

HP’S APPROACH

SELF-SERVICE USER

- Infrastructure- Platform

- Applications- Industry

Open Cloud Marketplace

BROKER

Orchestrate

BRIDGE BRIDGE

PRIVATE CLOUDVIRTUAL PRIVATE AND INDUSTRY CLOUDS

PUBLIC CLOUDS

SECURE

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29

HP CLOUDSYSTEM OUT-OF-THE-BOX CLOUD BURSTING

POC now; Solution with Savvis planned to be available by end 2011; Solution with other SP’s, planned to be available in 2012

New Services business model and offering

© Copyright 2011 Hewlett-Packard Development Company, L.P.3030

A VARIETY OF SOLUTIONS FOR SPS

BC/DR

Cloudbursting

WhiteLabeling

Footprint Augmentation

SP HP

Private Cloud

Public CloudSP

HPHP

HP HP

© Copyright 2011 Hewlett-Packard Development Company, L.P.31

SUMMARY

– The cloud generates multiple types of value

– Recognize cloud value is application dependent

– Consider evolving to a single cloud across internal, commercial, network

– CSP’s can achieve competitive price points and succeed

– Leverage existing assets: multi-layer network footprint, customer

relationships, and geo dispersion

– Focus on high bandwidth, interactive apps

– Network intelligence and flexibility can provide an additional edge

– Cloud intelligence and interoperability will be key

© Copyright 2011 Hewlett-Packard Development Company, L.P.32