To_Infinity_and_Beyond_2012_Big_Data_Internet_Scale_Update_4Q12_John_Sing

© 2012 IBM Corporation
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To Infinity and Beyond 2012
Big 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

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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)
 singj@us.ibm.com
 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

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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-disciplinary
Inter-
Disciplinary

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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

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The nature of workloads is rapidly shifting….
Rapid unstructured data growth
Unstructured
data workloads
=
Traditional
OLTP,
database

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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

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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/

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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

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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

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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 advance
Black line: actual result

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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

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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 and
Entertainment
Retail
3.5 PB in 2010
1 TB CT scanner → 2.5 PB/Year/Scanner
20 PB in 2011
Grow 300 TB per month, every month
ExamplesIndustries
Healthcare
Provider
Claims
Processor

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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

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Will Big Data Change the Way We Compete? Already Has!
Finance
Information
Healthcare
Ease of
capture
Value
http://www.mckinsey.com/Insights/MGI/Research/Technology_and_Innovation/Big_data_The_next_frontier_for_innovation

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GlobalDataVolumeinExabytes
Sensors
(InternetofThings)
Multiple sources: IDC,Cisco
100
90
80
70
60
50
40
30
20
10
AggregateUncertainty%
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.

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Worldwide, Broadband Internet Speeds are Zooming
Inter-
Disciplinary
http://gigaom.com/broadband/worldwide-broadband-demand-speeds-are-zooming/

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End user average
connection speed
State of worldwide Internet:
average Internet user connection speed
End user average
connection speed
http://www.akamai.com/stateoftheinternet/

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Growth of
The Cloud
by 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:

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How Big is the World? - 1
http://wikibon.org/blog/how-big-is-the-world-of-cloud-computing-infographic/
This is significant
Cheaper
7.1x
5.7x
7.3x
Network
Storage
Admins

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Bandwidth Availability created “The Cloud”…………
 Worldwide bandwidth
 Pervasive web services delivery model
–(i.e. “The Cloud”)
 Data centers with massive amounts:
–Processors
–Storage
–Network

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Bandwidth and the Cloud…..  Internet-scale centers…..
 Data:
–10s / 100s petabytes
 Servers:
–100,000s ….
 Workloads:
–Require server clusters
of 100s, 1000s, 10,000,
more …..

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

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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

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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

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More data centers….
4. NEXT GENERATION DATA EU
3. NAP OF THE AMERICAS,
MIAMI, 750,000 SF
1. 350 EAST CERMAK, CHICAGO,

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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

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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

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Apple
Here’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 ft
USD $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/

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Facebook
Lulea, Sweden - 290K sq ft (27K sq me
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

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Amazon Web Services
Amazon Web Services 1Q12: 450,000 servers
Amazon Perdix Modular Datacenter
EC2 17K core, 240 teraflop cluster 42
nd fastest supercomputer in world
450,000
servers
905 billion
objects
650K
req/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/

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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

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Google
Data Centers
in 2008:

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Google Data Center Photo Gallery
http://www.google.com/about/datacenters/gallery/#/

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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/

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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/

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Part 2: Disruptive Innovation
2. Disruptive Innovation in Today’s IT World
 The Non-Traditional Competitor
 Big Data, mobile Web 3.0

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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/laptop
market value
big decreases
Cloud / mobile
market value
*bigger increases*
MarketCapitalization

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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

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Disruptive Innovation
Definition:
 Create new
market and value
 Eventually
disrupts existing
 Displaces earlier
technology
Clayton Christensen
Harvard Business School
http://en.wikipedia.org/wiki/Disruptive_innovation

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 Not “advanced
technologies”
 Inferior yet “good
enough”
 Novel combinations
 Starts low end
 Grows up-market
–“low end
disruption”
Clayton Christensen

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 Learn lessons
 Watch today’s
world
Illustrative examples only

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 “Consumerization”
 Not just technology
 Delivery models
(cloud)
 Business models
 Ecosystems
Clayton Christensen

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Mobile will affect all business models…
Mobile =
Geo-locational superfood
Real-time analytics
http://www.digitalbuzzblog.com/2011-mobile-statistics-stats-facts-marketing-infographic

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Cloud-scale Data Centers required for:
Data Supertransformagicability
TaxiWiz
HousingMaps
Source: http://mashable.com/2007/07/11/google-maps-mashups-2/
Weatherbug

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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,
video
70%

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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

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 Big Data / Cloud on
disruptive path
 Traditional IT still
around but….
 Newer technologies
disrupt all platforms
Clayton Christensen
What will the effect be on
your business model?
Inter-
Disciplinary

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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

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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/

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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?

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Internet-scale application stack summary
User Interface Layer
Reports, Dashboards, Mashups, Search,
Ad hoc reporting, Spreadsheets
Analytic Process Layer
Real-time computing and analysis, stream computing,
entity analytics, data mining, data proximity, content
management, text analytics, etc.
Infrastructure layer
Virtualization, central end to end management, control,
deployment on software, server, storage in a
geographically dispersed environment
Users
Security
authorization
OS software
Location of
competitive
advantage
applications. Does all
workload balance,
redundancy
Cloud
infrastructure
Servers, storage
Unstructured data is the
growth workload
Compute power =
visualization layer
Data, I/O =
analytic layer

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You want a partner like IBM that
covers the entire modern inter-discipline
IT stack
Users
Security
authorization
STG Virtualization
IBM Software Group
Big Insights
InfoStreams
IBM Cloud
infrastructureSTG Servers, Storage
IBM Analytics
IBM SWG,
Services
IBM SWG,
Services

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Part 3: Principles for a successful IT
Future
Plans
Meld / meet / build readiness
Use, exploit, thrive

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Big Positioning picture
Traditional
IT
Storagereq’d:GB,TB,PB
$/server,storage
Data
Warehouse
Big
Data,
Internet
scale
Traditional
IT
Data
Warehouse
Big
Data,
Internet
scale

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Big Positioning picture
Traditional
IT
$/server.stroage
Data
Warehouse
Traditional
IT
Data
Warehouse
Current
IT
architectures
Growth areas
Mobile, Cloud
Growth areas
Mobile, Cloud
Big
Data
Internet
scale
Big
Data
Internet
scale
Current IT
architectures

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Build new, different skill sets
Traditional
IT
$/server,storage
Data
Warehouse
Big
Data
Internet
scale
Traditional
IT
Data
Warehouse
Big
Data
Internet
scale
Current IT
architectures
Traditional IT
workload
Highly parallelized internet
scale architecture
Integrated E2E software
centric
Current IT
architectures

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Key strategy
$/server,storage
Traditional
IT
Data
Warehouse
Big
Data
Internet
scale
Current IT
architectures 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

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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
$/server
Traditional
IT
Data
Warehouse
Big
Data
Internet
scale
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

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Apply lessons from today to Traditional IT as best possible
Source: Egan Ford, IBM Distinguished Engineer, OpenStack presentation: http://xmission.com/~egan/cloud/

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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

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Feel free
to use
me as a
resource
John Sing’s
bookmarks

 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
 singj@us.ibm.com

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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-disciplinary
Inter-
Disciplinary

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Inter-disciplinary
Disruptive Innovation:
Greatest opportunity to thrive
we have yet seen
$/server
Traditional
IT
Data
Warehouse
Big
Data
Internet
scale
Current IT
Traditional 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-
disciplinary
Exascale datacenters
 Massive parallelism
 E2E automation Mobile
Big Data
Applications
Cloud
Business
Models
Inter-
Disciplinary

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Together, let’s build a Smarter Planet

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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.PDF
Download your free copy here

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Applying the lessons from
Internet-scale Cloud Computing
to the Traditional data center

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Today: two different types of IT
Internet scale wkloadsTransactional IT

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Today’s two major IT workload types
Source: http://it20.info/2012/02/the-cloud-magic-rectangle-tm/ Transactional IT Internet scale wkloads

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How to build these two different clouds
Transactional IT
Internet scale wkloads

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What You (Consumer) Get with These Clouds:

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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

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Internet-scale
warehouse-level cloud data center
What’s biggest cost-savings element?

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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

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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, Holzle
http://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

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construction cost of Internet Scale Data Center is
Power / Cooling
Facebook’s
North Carolina Data Center Goes Live
Facebook:
Lulea, Sweden - 29
Facebook –
Prinville
, Oregon
Has spent $1B on it’s data centers
Open Compute Project
? Reducing power
profile reduces
construction cost

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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/

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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

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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

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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

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IBM internet-scale modern application stack:
Users
Security
authorization
User interface

85
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Analytics layer
Users
Security
authorization
Analytics

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IBM Analytics layer
Users
Security
authorization
Big Data Accelerators
Open Source Foundation Components
Big Data Enterprise Engines
Productivity 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

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IBM Big Data Reference Architecture
87
Big Data Accelerators
Eclipse Oozie Hadoop HBase Pig Lucene Jaql
Open Source Foundation Components
Big Data Enterprise Engines
Productivity 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
InforSphereInformationServer

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Governance
Security, Resiliency & Performance
Cloud Service Provider
Common Cloud
Management 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
Integration
Tools
Consumer
In-house IT
Cloud
Service
Integration
Tools
Cloud
Service
Integration
Tools
Consumer
In-house IT
Consumer
In-house IT
Service
Creation
Tools
Service
Creation
Tools
InfrastructureInfrastructure
Getting Cloud Right -- IBM Reference Architecture Whitepaper
Open Group Document
IBM’s Cloud Service Reference Architecture

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Governance
Security, Resiliency, Performance & Consumability
Cloud Service
Creator
Cloud Service ProviderCloud Service
Consumer
Cloud Services
IaaS
PaaS
SaaS
BPaaS
Common Cloud
Management Platform
Cloud Service
Integration
Tools
Consumer In-
house IT
Infrastructure
Middleware
Applications
Business
Processes
OSS – OperationalSupport
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
Transition
Manager
Deployment
Architect
Operations
Manager
Service Provider Portal & API
Consumer
Administrator
Consumer
Business
Manager
Consumer End
user
Service Creation
Tools
Service
Management
Development
Tools
Service Runtime
Development
Tools
Software
Development
Tools
Image Creation
Tools
Service
Component
Developer
Infrastructure
Security &
Risk Manager
Customer
Care
Service
Manager
Business
Manager
Service
Composer
Offering
Manager
Service
Integrator
ServiceManagement
ServiceConsumerPortal&API
ServiceDevelopmentPortal&API
API
API
API
API
Existing &
3rd party
services,
Partner
Ecosystems
Provisioning
Incident &
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
Infrastructure
MgmtInterfaces
PlatformMgmt
Interfaces
SoftwareMgmt
InterfacesBPMgmtInterfaces
Management Architecture

90
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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.

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