To_Infinity_and_Beyond_2012_Big_Data_Internet_Scale_Update_4Q12_John_Sing

© 2012 IBM Corporation

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To Infinity and Beyond 2012Big Data Internet Scale Update

John Sing

IBM STG Asia Pacific Technical Symposia – Auckland | New Zealand | November 2012

Opening video: http://www.youtube.com/watch?v=CxQHwmhJXX4

Opening video

© 2012 IBM Corporation2

IBM STG Asia Pacific Technical Symposia – Auckland | New Zealand | November 2012sGE01

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John Sing 31 years of experience with IBM in high end servers, storage, and software– 2009 - Present: IBM Executive Strategy Consultant: IT Strategy and Planning, Enterprise

Large Scale Storage, Internet Scale Workloads and Data Center Design, Big Data Analytics, HA/DR/BC

– 2002-2008: IBM IT Data Center Strategy, Large Scale Systems, Business Continuity, HA/DR/BC, IBM Storage

– 1998-2001: IBM Storage Subsystems Group - Enterprise Storage Server Marketing Manager, Planner for ESS Copy Services (FlashCopy, PPRC, XRC, Metro Mirror, Global Mirror)

– 1994-1998: IBM Hong Kong, IBM China Marketing Specialist for High-End Storage– 1989-1994: IBM USA Systems Center Specialist for High-End S/390 processors– 1982-1989: IBM USA Marketing Specialist for S/370, S/390 customers (including VSE

and VSE/ESA)

[email protected]

IBM colleagues may access my intranet webpage:– http://snjgsa.ibm.com/~singj/

You may follow my daily IT research blog– http://www.delicious.com/atsf_arizona

You may follow me on Slideshare.net:– http://www.slideshare.net/johnsing1

My LinkedIn:– http://www.linkedin.com/in/johnsing



Agenda

1. Exploiting the Big Opportunity: Data, Data, Data! Real-time Data Factories

Bandwidth created “The Cloud”

Internet Scale Data Center architectures house internet scale data

2. Disruptive Innovation in Today’s IT World The Non-Traditional Competitor

The mobile Web 3.0

3. Principles, collaboration for a successful IT Future

Inter-disciplinaryInter-

Disciplinary



Part 1: Exploiting the Opportunity: Data! Data! Data!

1. Exploiting the Big Opportunity: Data, Data, Data!

Real-time Data Factories

Bandwidth created “The Cloud”

Internet Scale Data Center Architectures house internet scale data



The nature of workloads is rapidly shifting….

Rapid unstructured data growth

Unstructured data workloads

=

Traditional OLTP,

database



Humans collecting useful data on massive scale

Chart in public domain: IEEE Massive File Storage presentation, author: Bill Kramer, NCSA: http://storageconference.org/2010/Presentations/MSST/1.Kramer.pdf



Unmanned Aerial Surveillance (UAS)

http://www.hawkeyeuav.com/ , http://www.gatewing.com/ , http://www.sensefly.com/ http://www.aeryon.com/products.html http://www.leptron.com/corporate/products/



http://www.gim-international.com/issues/articles/id1306-Mapping_with_Mobile_Lidar.html

http://www.sparpointgroup.com/News/Vol09No37-New-feature-extraction-tool-for-lidar/

http://www.lidarnews.com/PDF/LiDARMagazine_Amadori-UtilityVegetationManagement_Vol2No5.pdf

Light Detection and Ranging (LiDAR)

http://www.southernmapping.com/methodology.php

http://www.profsurv.com/magazine/article.aspx?i=70599



We are building real-time, integrated stream computing on massive scale

n d

Inter-

Disciplinary

Chart in public domain: IEEE Massive File Storage presentation, author: Bill Kramer, NCSA: http://storageconference.org/2010/Presentations/MSST/1.Kramer.pdf



IBM Predictive Analytics: Movement in a City

•10 minute-ahead volume forecast (blue) vs. actual value (black)

•10 minute-ahead speed forecast (blue) vs. actual value (black).

Blue line: IBM analytics prediction 10 minutes in advanceBlack line: actual result



IBM Predictive Analytics Ensuring Public Safety:Let’s play video 1st

Memphis Blue CRUSH MapMemphis Blue CRUSH Map

http://www.youtube.com/watch?v=_ZyU6po_E74

Blue CRUSH predictive analysis for officer deployment & risk management generated easy-to-read crime maps every four hours

Richmond, VA: Violent crime decreased in the first year by 32%, another 40% thereafter, moving Richmond from #5 on the list of the most dangerous US cities to #99



A new class of data-rich industries is emerging

Today’s Hyperscale Data Companies

New business models: company’s value based on amount of information stored, exploited

Tomorrow’s Hyperscale Data Companies

Aerospace

Banking

Energy

Government

Healthcare

Insurance

Manufacturing

Media andEntertainment

Retail

3.5 PB in 20101 TB CT scanner → 2.5 PB/Year/Scanner

20 PB in 2011Grow 300 TB per month, every month

ExamplesIndustries

Healthcare

Provider

Claims

Processor



McKinsey Global Report on Big Data – May 2011

Number of Big Data scientists and mgrs

needed in USA

http://www.mckinsey.com/mgi/publications/big_data/index.asp



Will Big Data Change the Way We Compete? Already Has!

Finance

Information

Healthcare

Ease ofcapture

Value

http://www.mckinsey.com/Insights/MGI/Research/Technology_and_Innovation/Big_data_The_next_frontier_for_innovation



Glo

bal

Dat

a V

olu

me

in E

xab

ytes

Sens

ors

(Inte

rnet

of T

hing

s)

Multiple sources: IDC,Cisco

100

90

80

70

60

50

40

30

20

10

Agg

rega

te U

ncer

tain

ty %

VoIP

9000

8000

7000

6000

5000

4000

3000

2000

1000

0

2005 2010 2015

The Big Data opportunity is huge

Enterprise Data

2015: # networked devices 2x global population

Social Media

(video, audio and text)

Total # social media accounts > global population.



Worldwide, Broadband Internet Speeds are Zooming

Inter-

Disciplinary

http://gigaom.com/broadband/worldwide-broadband-demand-speeds-are-zooming/



End user average connection speed

State of worldwide Internet: average Internet user connection speed

End user average

connection speed

http://www.akamai.com/stateoftheinternet/



Growth ofThe Cloudby 2016

Mobile

Geo-locational

Real-time data

Shift to cloud mega-data centers

http://www.datacenterknowledge.com/archives/2012/10/23/cisco-releases-2nd-annual-global-cloud-index/

Source:



How Big is the World? - 1

http://wikibon.org/blog/how-big-is-the-world-of-cloud-computing-infographic/

This is significant

Cheaper7.1x5.7x7.3x

NetworkStorageAdmins



Bandwidth Availability created “The Cloud”…………

Worldwide bandwidth

Pervasive web services delivery model –(i.e. “The Cloud”)

Data centers with massive amounts:–Processors–Storage–Network



Bandwidth and the Cloud….. Internet-scale centers…..

Data: –10s / 100s petabytes

Servers: –100,000s ….

Workloads:–Require server clusters of 100s, 1000s, 10,000, more …..



http://wikibon.org/blog/wp-content/uploads/2011/10/5-top-data-centers.html



Large Data Centers in past 2 years

10. SUPERNAP, LAS VEGAS, 407,000 SF

9A and 9B. MICROSOFT QUINCY AND SAN ANTONIO DATA CENTERS, 470,000 S

http://www.datacenterknowledge.com/special-report-the-worlds-largest-data-centers/largest-data-centers-supernap-microsoft-dft/#supernap

http://www.datacenterknowledge.com/special-report-the-worlds-largest-data-centers/largest-data-centers-supernap-microsoft-dft/#quincy



Container Data Center Architecture 7. PHOENIX ONE, PHOENIX, ARIZ. 538,000 SF

5. MICROSOFT CHICAGO DATA CENTER, Chicago 700,000 SF

2. QTS METRO DATA CENTER, ATLANTA, 990,000 SF

Microsoft’s Chicago Container Data Center

http://www.datacenterknowledge.com/special-report-the-worlds-largest-data-centers/largest-data-centers-io-data-centers-microsoft/#phoenixone http://www.datacenterknowledge.com/special-report-the-worlds-largest-data-centers/largest-data-centers-io-data-centers-microsoft/#chicago http://www.datacenterknowledge.com/special-report-the-worlds-largest-data-centers/largest-data-centers-ngd-terremark-qts/#qts



More data centers….

4. NEXT GENERATION DATA EUROPE, WALES 750,000 SF

3. NAP OF THE AMERICAS, MIAMI, 750,000 SF

1. 350 EAST CERMAK, CHICAGO, 1.1 MILLION SQUARE FEET



2012: Other large world data centers

Tulip Telecom, India, Bangalore

China to build 6.2 M sq feet data center by 2016

Amadeus, Erding, Germany

Utah Data Center, US Govt, 1M sq feet

http://www.datacenterknowledge.com/archives/2012/02/08/tulip-ibm-team-on-huge-data-center-in-india/ http://www.youtube.com/watch?v=-h5RYflgBcM



Now….. what about the web giants?

i.e. Apple, Facebook, Google, Amazon, etc?

That’s Big!

http://www.fastcompany.com/magazine/160/tech-wars-2012-amazon-apple-google-facebook



AppleHere’s what powers iCloud, see Jobs at WWDC 2011 iCloud announce (YouTube)

Rendering of Apple's new North Carolina Data Center. Credit: Apple

Apple Data Center

FAQ

Maiden, North Carolina 500K sq ftUSD $1Billion

Apple Data Center Newark, California

Under construction: Prineville, Oregon

iCloud

http://gigaom.com/cloud/apple-launches-icloud-heres-what-powers-it/ http://www.youtube.com/watch?v=IPNZAvX1yEs http://www.theregister.co.uk/2012/02/21/apple_new_data_center/ http://www.datacenterknowledge.com/archives/2011/05/18/apple-adding-data-center-in-silicon-valley/



Facebook

Lulea, Sweden - 290K sq ft (27K sq meters) by late 2012

http://www.datacenterknowledge.com/archives/2012/04/20/facebooks-north-carolina-data-center-goes-live/ http://www.wired.com/wiredenterprise/2011/12/facebook-data-center/all/1 https://www.facebook.com/note.php?note_id=469716398919



Amazon Web Services

Amazon Web Services 1Q12: 450,000 servers

Amazon Perdix Modular Datacenter

EC2 17K core, 240 teraflop cluster 42nd fastest supercomputer in world

450,000servers

905 billionobjects

650Kreq/sec

http://aws.typepad.com/aws/2012/04/amazon-s3-905-billion-objects-and-650000-requestssecond.html http://gigaom.com/cloud/how-big-is-amazon-web-services-bigger-than-a-billion/



What is Google? Google is not a search engine

Google is a real-time “Data Factory” ecosystem

– Defacto organizer of all human internet data

– Worldwide Patterns of Life data

– Android ingest / output devices• Motorola Wireless acquired $12B

– Supporting businesses and ecosystem roles:• Google+, Play, Shop, Books, Gmail, Docs• Voice recognition

The history of search engine http://www.wordstream.com/articles/internet-search-engines-history

Inter-

Disciplinary



Google Data Centers

in 2008:



Google Data Center Photo Gallery

http://www.google.com/about/datacenters/gallery/#/



Google Data Center CAPEX worldwide

Capital expenditures on datacenters:– 1Q12: USD$ 607M– 2011: USD$ 3.4B– 2010: USD$ 4.0B– 2009: USD$ 809M

Each data center between $200M and

$600M

The Dalles, Oregon

http://www.datacenterknowledge.com/archives/2012/04/13/google-data-center-spending-recedes-to-607m/



Traditional IT vs. Internet Scale Workload Data Center

Source: Egan Ford, IBM Distinguished Engineer, Budapest xCL01 OpenStack presentation: http://xmission.com/~egan/cloud/Source: http://it20.info/2012/02/the-cloud-magic-rectangle-tm/



Part 2: Disruptive Innovation

2. Disruptive Innovation in Today’s IT World

The Non-Traditional Competitor

Big Data, mobile Web 3.0



With all this opportunity……. Why is this Disruptive Change flat-lining traditional consumer PC / desktop manufacturers?

PC / laptop stalwarts

Unsuccessful in shift

To mobile

http://gigaom.com/2012/09/01/hp-dell-and-the-paradox-of-the-disrupted/

PC/laptopmarket value

big decreases

Cloud / mobilemarket value

*bigger increases*

Mar

ket

Cap

italiz

atio

n



Observe: how fast mobile internet grows by 2014

By 2014:

Mobile will be main way

Of connecting to Internet

Inter-

Disciplinary

http://www.digitalbuzzblog.com/2011-mobile-statistics-stats-facts-marketing-infographic



Disruptive Innovation

Definition:

Create new market and value

Eventually disrupts existing

Displaces earlier technology

Clayton ChristensenHarvard Business School

http://en.wikipedia.org/wiki/Disruptive_innovation




Not “advanced technologies”

Inferior yet “good enough”

Novel combinations

Starts low end

Grows up-market–“low end

disruption”






Learn lessons

Watch today’s world

Illustrative examples only




“Consumerization”

Not just technology

Delivery models (cloud)

Business models

Ecosystems





Mobile will affect all business models…

Mobile =

Geo-locational superfood

Real-time analytics

http://www.digitalbuzzblog.com/2011-mobile-statistics-stats-facts-marketing-infographic



Cloud-scale Data Centers required for: Data Supertransformagicability

TaxiWiz

HousingMaps

Source: http://mashable.com/2007/07/11/google-maps-mashups-2/

Weatherbug



By 2016, how much mobile data? What kind?

2012:–Mobile-connected

devices > # people

2016:–10 billion mobile devices–(world population: 7.3 B)

http://www.cisco.com/en/US/solutions/collateral/ns341/ns525/ns537/ns705/ns827/white_paper_c11-520862.html

Smartphones 48%

Web data,video70%



Will Big Data, Internet Cloud data centers, mobile-centric business models affect the way we compete? Implement IT?

Yes, it will!

Let’s see one more video

http://www.youtube.com/watch?v=EdSd32nbtoA




Big Data / Cloud on disruptive path

Traditional IT still around but….

Newer technologies disrupt all platforms


What will the effect be on your business model?

Inter-

Disciplinary



It’s NOT your Traditional competitors you need worry about

Blockbuster 2002:

“Online video not viable”

“Niche market”

2011: 24 million Netflix customers

2010: Blockbuster files for bankruptcy

http://hbswk.hbs.edu/item/7007.html



It’s NOT your Traditional competitors you need worry about

Illustrative examples only

http://www.tatango.com/blog/time-spent-on-mobile-devices-outpaces-newspapers-and-magazines/



Today, customers have many non-traditional alternatives

Traditional alternatives:

Other platforms

Other vendors

Non-traditional alternatives: – The Cloud, the Developing World

What will the effect be on your business model?



Internet-scale application stack summary

User Interface LayerReports, Dashboards, Mashups, Search,

Ad hoc reporting, Spreadsheets

Analytic Process LayerReal-time computing and analysis, stream computing, entity analytics, data mining, data proximity, content

management, text analytics, etc.

Infrastructure layerVirtualization, central end to end management, control,

deployment on software, server, storage in a geographically dispersed environment

Users

Secu

rityau

tho

rization

OS software

Location ofcompetitive advantage

applications. Does all workload balance,

redundancy

Cloud infrastructureServers, storage

Unstructured data is the growth workload

Compute power = visualization layer

Data, I/O = analytic layer



You want a partner like IBM that covers the entire modern inter-disciplineIT stack







Users

Secu

rityau

tho

rization

STG Virtualization

IBM Software Group

Big InsightsInfoStreams

IBM Cloud infrastructureSTG Servers, Storage

IBM Analytics

IBM SWG, Services

IBM SWG, Services



Part 3: Principles for a successful IT Future

Plans

Meld / meet / build readiness

Use, exploit, thrive



Big Positioning picture

TraditionalIT

Sto

rag

e r

eq’d

: G

B,

TB

, P

B

$ /

serv

er,

sto

rag

e

DataWarehouse

BigData,

Internetscale

TraditionalIT

DataWarehouse

BigData,

Internetscale



Big Positioning picture

TraditionalIT

Sto

rag

e r

eq’d

: G

B,

TB

, P

B

$ /

serv

er.

stro

age

DataWarehouse

TraditionalIT

DataWarehouse

CurrentIT

architectures

Growth areas

Mobile, Cloud

Growth areas

Mobile, Cloud

BigData

Internetscale

BigData

Internetscale

Current IT architectures



Build new, different skill sets

TraditionalIT

Sto

rag

e r

eq’d

: G

B,

TB

, P

B

$ /

serv

er,

sto

rag

e

DataWarehouse

BigData

Internetscale

TraditionalIT

DataWarehouse

BigData

Internetscale

Current IT architectures

Traditional IT workload

Highly parallelized internet scale architecture

Integrated E2E software centric

Current ITarchitectures



Key strategy

$ /

serv

er,

sto

rag

e

TraditionalIT

DataWarehouse

BigData

Internetscale

Current ITarchitectures Traditional IT

architectures

Internet scale architectures

Continue modernize current traditional IT …

Architect new-gen

connectors, skills Architect future

expandability

Connect with– New generation

mobile-enabled workloads

http://www.slideshare.net/johnsing1/s-bd03-infinitybeyond2internetscaleworkloadsdatacenterdesignv6speaker



To successfully co-exist / thrive with new generation workloads

Understand Big Data / new gen workload environment

Successfully innovate new capabilities

Expand your understanding

Be the change you want your company to be

$ /

serv

er

TraditionalIT

DataWarehouse

BigData

Internetscale

Views new gen as powerful

partner Traditional IT architectures

Internet scale architectures

Views traditional IT as powerful

enabler

http://www.slideshare.net/johnsing1/s-bd03-infinitybeyond2internetscaleworkloadsdatacenterdesignv6speaker



Apply lessons from today to Traditional IT as best possible

Source: Egan Ford, IBM Distinguished Engineer, OpenStack presentation: http://xmission.com/~egan/cloud/Source: http://it20.info/2012/02/the-cloud-magic-rectangle-tm/



How to get ahead and thrive in this new world?

2012: devote 1st hour of day to keeping current

–No longer optional

Establish power-knowledge digital footprint, intelligently sharing what you find

–Don’t email what you find (too much email already)

–Use social networking, social bookmarking, blogs, etc

Become a power user of your smartphone’s ecosystem

Inter-

Disciplinary



Feel freeto use me as aresource

John Sing’sbookmarks

My external sources, daily IT research:– http://delicious.com/atsf_arizona

– http://www.linkedin.com/in/johnsing – http://www.slideshare.net/johnsing1

IBM colleagues may also see my IBM Intranet webpage:– http://snjgsa.ibm.com/~singj/ – http://snjgsa.ibm.com/~singj/public/sonas_index.html

[email protected]



Learning Points

1. Exploitation of the opportunity: Data, Data, Data!

Is being done in real-time Data Factories on internet scale today

Bandwidth will continue to create “The Cloud”

Understand and study how Internet Scale Data Center architectures house internet scale data

2. Hyper-pace of Disruptive Innovation in Today’s IT World

Beware the Non-Traditional Competitor

The Mobile Web 3.0 is already impacting all business models

3. Invest your 1st hour of every day in being a part of the future

Be the change you want your company to be

Inter-disciplinaryInter-

Disciplinary



Inter-disciplinary Disruptive Innovation:

Greatest opportunity to thrive we have yet seen

$ /

s

erv

er

TraditionalIT

DataWarehouse

BigData

Internetscale

Current ITTraditional IT

Internet scale workloads

New gen workloads

Identify inter-disciplinary new generation big data workloads,

business models

Know non-traditional competitors well

Develop / implement to meld, meet, use, exploit, thrive with new

reality

Inter-

discip

lina

ry

Exascale datacenters

Massive parallelism

E2E automation Mobile

Big DataApplications

CloudBusiness

Models

Inter-

Disciplinary



Together, let’s build a Smarter Planet



Recommend you download, read,this very informative IBM book

“Understanding Big Data” – Published April 2012– Free download– Well worth reading to understand components

of Big Data, and how to exploit

Part 1: The Big Deal about Big Data– Chapter 1 – What is Big Data? Hint: You’re a

Part of it Every Day– Chapter 2 – Why Big Data is Important– Chapter 3 – Why IBM for Big Data

Part II: Big Data: From the Technology Perspective

– Chapter 4 - All About Hadoop: The Big Data Lingo Chapter

– Chapter 5 – IBM InfoSphere Big Insights – Analytics for “At Rest” Big Data

– Chapter 6 – IBM InfoSphere Streams – Analytics for “In Motion” Big Data

http://public.dhe.ibm.com/common/ssi/ecm/en/iml14297usen/IML14297USEN.PDFDownload your free copy here



Applying the lessons from

Internet-scale Cloud Computing

to the Traditional data center



Today: two different types of IT

Source: http://it20.info/2012/02/the-cloud-magic-rectangle-tm/

Internet scale wkloadsTransactional IT



Today’s two major IT workload types

Source: http://it20.info/2012/02/the-cloud-magic-rectangle-tm/ Transactional IT Internet scale wkloads



How to build these two different clouds


Transactional ITInternet scale wkloads



What You (Consumer) Get with These Clouds:




Policy-based Traditional IT Clouds and Design-for-fail Internet Clouds are purpose optimized Infrastructure Management solutions

Policy-based Clouds

• Purpose optimized for longer-lived virtual machines managed by Server Administrator

• Centralizes enterprise server virtualization administration tasks

• High degree of flexibility designed to accommodate virtualization all workloads

• Significant focus on managing availability and QoS for long-lived workloads with level of isolation

• Characteristics derived from exploiting enterprise class hardware

• Legacy applications

Design-for-fail Clouds

• Purpose optimized for shorter-term virtual machines managed via end-user or automated process

• Decentralized control, embraces eventual consistency, focus on making “good enough” decisions

• High degree of standardization

• Significant focus on ensuring availability of control plane

• Characteristics driven by software

• New applications



Internet-scale

warehouse-level cloud data center

What’s biggest cost-savings element?



Internet Scale data center power components…

Image courtesy of DLB Associates: D. Dyer, “Current trends/challenges in datacenter thermal management—a facilities perspective,”presentation at ITHERM, San Diego, CA, June 1, 2006.“The Data Center as a Computer: Introduction to Warehouse Scale Computing”, figure 4-1, p.40 Barroso, Holzle

http://www.morganclaypool.com/doi/pdf/10.2200/S00193ED1V01Y200905CAC006



Breakdown of data center energy overheads

Image courtesy of ASHRAE “The Data Center as a Computer: Introduction to Warehouse Scale Computing”, figure 5-2, p.49 Barroso, Holzlehttp://www.morganclaypool.com/doi/pdf/10.2200/S00193ED1V01Y200905CAC006

Chiller alone is 33% of the cost

UPS alone is 18% of

construction cost

Physical cooling, UPS dominates the electrical power cost



construction cost of Internet Scale Data Center is Power / Cooling

Facebook’s North Carolina Data Center Goes Live

Facebook: Lulea, Sweden - 290K sq ft (27K sq meters) by late 2012

Facebook – Prinville, Oregon

Has spent $1B on it’s data centers

Open Compute Project

? Reducing power profile reduces

construction cost



Google claims its data centers use 50% less energy than competitors

Power Usage Effectiveness– PUE=1.14 means power overhead is

only 14%– Industry average is around 1.8

http://venturebeat.com/2012/03/26/google-data-centers-use-less-energy/

Industry average PUE is about 1.8

http://www.datacenterknowledge.com/archives/2011/05/10/uptime-institute-the-average-pue-is-1-8/



Modular Data Center

Value isn’t just time to delivery / flexibility

It’s also Higher Power density = lower construction cost

http://www.youtube.com/watch?v=zRwPSFpLX8I



That’s why you see such a big modern push on Container Data Centers:

7. PHOENIX ONE, PHOENIX, ARIZ. 538,000 SF

5. MICROSOFT CHICAGO DATA CENTER, Chicago 700,000 SF 2. QTS METRO DATA CENTER, ATLANTA, 990,000 SF

Microsoft’s Chicago Container Data Center



State of the Modular Data Center

Cyrus One 1 million sq ft “Massively Modular” data center under construction in Phoenix, Arizona

I/O Modular Data Center Assembly line

http://www.datacenterknowledge.com/archives/2012/05/17/cyrusone-going-massively-modular-in-phoenix/

http://www.datacenterknowledge.com/archives/2012/02/06/the-state-of-the-modular-data-center/

http://www.datacenterknowledge.com/archives/2012/01/30/inside-ios-modular-data-center-assembly-line/

Mismatch between rapid workload churn vs. 10+ year data center lifespan = modular data center characteristics strategic possibilities for

new build data centers



IBM internet-scale modern application stack:







UsersS

ecurity

auth

orizatio

n

User interface



Analytics layer







UsersS

ecurity

auth

orizatio

n

Analytics



IBM Analytics layer







Users

Secu

rityau

tho

rization

Big Data AcceleratorsBig Data Accelerators

Open Source Foundation Components

Big Data Enterprise EnginesBig Data Enterprise Engines

Productivity Tools and OptimizationProductivity Tools and Optimization

InfoSphere BigInsightsInfoSphere Streams

Applications

Text

Image/Video

Financial

Times Series

Statistics

Mining

Geospatial

Mathematical

Workload Management and Optimization

Consumability and Management Tools

IBM Analytics



IBM Big Data Reference Architecture

87

Big Data AcceleratorsBig Data Accelerators

Eclipse Oozie Hadoop HBase Pig Lucene Jaql

Open Source Foundation Components

Big Data Enterprise EnginesBig Data Enterprise Engines

Productivity Tools and OptimizationProductivity Tools and Optimization

InfoSphere BigInsightsInfoSphere Streams

Connectors Applications Blueprints

Text

Image/Video

Financial

Times Series

Statistics

Mining

Geospatial

Mathematical

Acoustic

Workload Management and Optimization

Client and Partner Solutions

IBM Big Data Solutions

Consumability and Management Tools

Data Growth Management

InfoSphere Optim

Database

DB2

Data Warehouse

InfoSphere Warehouse

Master Data Management

InfoSphere MDM

Warehouse Appliance

IBM Netezza

Marketing

IBM Unica

Content Analytics

ECM

Business Analytics

Cognos & SPSS

Info

rSph

ere

Info

rmat

ion

Serv

er



Governance

Security, Resiliency & Performance

Cloud Service Provider

Common CloudManagement Platform (CCMP)

Operational Support Services (OSS)

Operational Support Services (OSS)

Cloud Services

Infrastructure-as-a-ServiceInfrastructure-as-a-Service

Platform-as-a-ServicePlatform-as-a-Service

Software-as-a-ServiceSoftware-as-a-Service

Business-Process-as-a-Service

Business-Process-as-a-Service

Partner CapabilitiesPartner Capabilities

Business Support Services

(BSS)

Business Support Services

(BSS)

Cloud Service

IntegrationTools

ConsumerIn-house IT

Cloud Service

IntegrationTools

Cloud Service

IntegrationTools

ConsumerIn-house ITConsumerIn-house IT

Service Creation

Tools

Service Creation

Tools

InfrastructureInfrastructure

Getting Cloud Right -- IBM Reference Architecture WhitepaperOpen Group Document

IBM’s Cloud Service Reference Architecture



Governance

Security, Resiliency, Performance & Consumability

Cloud ServiceCreator

Cloud Service ProviderCloud ServiceConsumer

Cloud Services

IaaS

PaaS

SaaS

BPaaS

Common CloudManagement Platform

Cloud Service Integration

Tools

Consumer In-house IT

Infrastructure

Middleware

Applications

Business Processes

OSS – Operational Support Services

BSS – Business Support Services

Subscription Management Pricing

Entitlement Management

Metering Rating Billing

Clearing & Settlement

Accounts Payable

Accounts Receivable

Customer Account

Management

Service Offering Catalog

Service Offering

Management

Contracts & Agreement

Management

Service Request

Management

Order Management

TransitionManager

DeploymentArchitect

OperationsManager

Service Provider Portal & API

Consumer Administrator

Consumer BusinessManager

Consumer End user

Service Creation Tools

Service Management Development

Tools

Service Runtime Development

Tools

Software Development

Tools

Image Creation Tools

Service Component Developer

Inf rastructure

Security &Risk Manager

CustomerCare

ServiceManager

BusinessManager

Service Composer

OfferingManager

ServiceIntegrator

Service M

anagement

Service C

onsumer P

ortal & A

PI

Service D

evelopment

Portal &

AP

I

AP

I

AP

I

AP

I

AP

I

Existing & 3rd party services, Partner

Ecosystems

ProvisioningIncident & Problem

Management

IT Service Level

Management

Service Automation Management

Service Delivery Catalog

Service Request

Management

Change & Configuration Management

Image Lifecycle

Management

Monitoring & Event

Management

IT Asset & License

Management

Capacity & Performance Management

Platform & Virtualization Management

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Management Architecture



Acknowledgements, disclaimers and trademarks

Adobe, the Adobe logo, PostScript, and the PostScript logo are either registered trademarks or trademarks of Adobe Systems Incorporated in the United States, and/or other countries. IT Infrastructure Library is a registered trademark of the Central Computer and Telecommunications Agency which is now part of the Office of Government Commerce. Intel, Intel logo, Intel Inside, Intel Inside logo, Intel Centrino, Intel Centrino logo, Celeron, Intel Xeon, Intel SpeedStep, Itanium, and Pentium are trademarks or registered trademarks of Intel Corporation or its subsidiaries in the United States and other countries. Linux is a registered trademark of Linus Torvalds in the United States, other countries, or both. Microsoft, Windows, Windows NT, and the Windows logo are trademarks of Microsoft Corporation in the United States, other countries, or both. ITIL is a registered trademark, and a registered community trademark of the Office of Government Commerce, and is registered in the U.S. Patent and Trademark Office. UNIX is a registered trademark of The Open Group in the United States and other countries. Java and all Java-based trademarks and logos are trademarks or registered trademarks of Oracle and/or its affiliates. Cell Broadband Engine is a trademark of Sony Computer Entertainment, Inc. in the United States, other countries, or both and is used under license therefrom. Linear Tape-Open, LTO, the LTO Logo, Ultrium, and the Ultrium logo are trademarks of HP, IBM Corp. and Quantum in the U.S. and other countries.

Other product and service names might be trademarks of IBM or other companies. Information is provided "AS IS" without warranty of any kind.

The customer examples described are presented as illustrations of how those customers have used IBM products and the results they may have achieved. Actual environmental costs and performance characteristics may vary by customer.

Information concerning non-IBM products was obtained from a supplier of these products, published announcement material, or other publicly available sources and does not constitute an endorsement of such products by IBM. Sources for non-IBM list prices and performance numbers are taken from publicly available information, including vendor announcements and vendor worldwide homepages. IBM has not tested these products and cannot confirm the accuracy of performance, capability, or any other claims related to non-IBM products. Questions on the capability of non-IBM products should be addressed to the supplier of those products.

All statements regarding IBM future direction and intent are subject to change or withdrawal without notice, and represent goals and objectives only.

Some information addresses anticipated future capabilities. Such information is not intended as a definitive statement of a commitment to specific levels of performance, function or delivery schedules with respect to any future products. Such commitments are only made in IBM product announcements. The information is presented here to communicate IBM's current investment and development activities as a good faith effort to help with our customers' future planning.

Performance is based on measurements and projections using standard IBM benchmarks in a controlled environment. The actual throughput or performance that any user will experience will vary depending upon considerations such as the amount of multiprogramming in the user's job stream, the I/O configuration, the storage configuration, and the workload processed. Therefore, no assurance can be given that an individual user will achieve throughput or performance improvements equivalent to the ratios stated here.

Prices are suggested U.S. list prices and are subject to change without notice. Starting price may not include a hard drive, operating system or other features. Contact your IBM representative or Business Partner for the most current pricing in your geography.

Photographs shown may be engineering prototypes. Changes may be incorporated in production models.

© IBM Corporation 2012. All rights reserved.References in this document to IBM products or services do not imply that IBM intends to make them available in every country.

Trademarks of International Business Machines Corporation in the United States, other countries, or both can be found on the World Wide Web at http://www.ibm.com/legal/copytrade.shtml.



Light Detection and Ranging (LiDAR)

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