Atos Origin

Report
Everything as a Service,
including Big Data: BDaaS
Franco-British bilateral workshop on
Big Data
London
November 2012
Mick Symonds
Principal Solutions Architect, Atos MS NL,
7 November 2012
MAS 07 November 2012
Introducing Atos
Franco-British bilateral
workshop on Big Data
Atos is an international information technology services
company, delivering hi-tech transactional services,
consulting, systems integration and managed services.
Atos is focused on business technology that powers progress
and helps organizations to create their firm of the future. It is
the Worldwide Information Technology Partner for the
Olympic Games and is quoted on the Paris Eurolist Market.
Atos operates under the brands Atos, Atos Consulting &
Technology Services, Atos Worldline and Atos Worldgrid.
▶ Annual revenues of € 8,6 billion (pro-forma 2010)
▶ Almost 74,000 business technologists worldwide
in 42 countries
▶ Worldwide headquarters in Bezons / Paris, France
▶ Atos was established on July 1st 2011, following the
successful integration of Atos Origin and Siemens IT
Solutions and Services and the establishment of a global
strategic partnership with Siemens AG
2
Foundation IT Services:
Global Delivery to Trusted Partner
MAS 07 November 2012
Franco-British bilateral
workshop on Big Data
ERP Applications
Data Centers
Enterprise Management Centers
900,000 SAP users
13 Global Data Centers +
50 Local / Regional Data Centers
Desktop
93,000 sq meters Data Center
1.42 average global virtualization ratio
Global EMC’s in Timisoara and Kuala
Lumpur & 15 local EMCs with almost
700 staff
2,4 Million Seats
45 Million calls / year
Server Management
105,000 managed server
instances (74,000 managed
physical servers)
Hosting:
▶ 40,000 MIPS
▶ 41,500 terabytes storage
▶ 6000 COD/IaaS/Cloud instances
Network & Security services
40,000 switches, 6,000 routers,
12,500 WLAN access points, 327,000
voice end users, 350,000 RAS users,
31,000 unified communications end
users, filtering for 146,000 email
mailboxes
3
Powering progress for our clients
Financial Services
Public Sector,
Healthcare &
Transport
Energy & Utilities
Manufacturing,
Retail & Services
Telecom, Media &
Technology
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MAS 07 November 2012
Franco-British bilateral
workshop on Big Data
What I want to tell you about
MAS 07 November 2012
Franco-British bilateral
workshop on Big Data
▶ It feels strange to come and tell Researchers about “Innovation”
▶ Most of our “innovation” is finding out what researchers and vendors are
reporting
– we are a long way down the food chain in most respects
▶ However, we find that one man’s business-as-usual is sometimes another man’s
innovation
▶ The real development in Cloud in general and Helix Nebula in particular is not
really technology
– it is deploying services, between suppliers, and making it work as a business
▶ In Cloud, everything is “as a Service” (XaaS)
– including, potentially, Bid Data storage and management
▶ You can liberate yourselves from the tedious grind of production operations:
– a. by delegating the structured deployment of rules and policies to us
– b. by using us to supply point/niche capabilities
– c. to provide enabling facilities for people who provide real added value
5
What is Big Data, the 3-4 traditional
V’s
Source: Oracle
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MAS 07 November 2012
Franco-British bilateral
workshop on Big Data
From the traditional 3-4 V’s towards
the 5-6 V’s
Value
Viscosity – Viscosity measures the
resistance to flow in the volume of
data. This resistance can come from
different data sources, friction from
integration flow rates, and processing
required to turn the data into insight.
Technologies to deal with viscosity
include improved streaming, agile
integration bus’, and complex event
processing.
Virality – Virality describes how quickly
information gets dispersed across
people to people (P2P) networks.
Virality measures how quickly data is
spread and shared to each unique
node. Time is a determinant factor
along with rate of spread.
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MAS 07 November 2012
Franco-British bilateral
workshop on Big Data
Big Data is transforming business,
as well as research
▶
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▶
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▶
MAS 07 November 2012
Franco-British bilateral
workshop on Big Data
Large Hadron Collider: An example of sensor and machine data is found at the Large Hadron Collider at CERN, the
European Organization for Nuclear Research. CERN scientists can generate 40 terabytes of data every second during
experiments.
Boeing Jets: Boeing jet engines can produce 10 terabytes of operational information for every 30 minutes they turn. A
four-engine jumbo jet can create 640 terabytes of data on just one Atlantic crossing; multiply that by the more than 25,000
flights flown each day, and you get an understanding of the impact that sensor and machine-produced data can make on a
BI environment.
Twitter: The micro blogging site Twitter serves more than 200 million users who produce more than 90 million "tweets" per
day, or 800 per second. Each of these posts is approximately 200 bytes in size. On an average day, this traffic equals more
than 12 gigabytes and, throughout the Twitter ecosystem, the company produces a total of eight terabytes of data per day.
In comparison, the New York Stock Exchange produces about one terabyte of data per day.
Wal-Mart: Transactional data has grown in velocity and volume at many companies. As recently as 2005, the largest data
warehouse in the world was estimated to be 100 terabytes in size. Today, Wal-Mart, the world's largest retailer, is logging
one million customer transactions per hour and feeding information into databases estimated at 2.5 petabytes in size.
Financial services: Discover fraud patterns based on multi-years worth of credit card transactions and in a time scale that
does not allow new patterns to accumulate significant losses. Measure transaction processing latency across many business
processes by processing and correlating system log data.
Internet retailers: Discover fraud patterns in Internet retailing by mining web click logs. Assess risk by product type and
session Internet Protocol (IP) address activity.
Retailers: Perform sentiment analysis by analysing social media data.
Drug discovery: Perform large-scale text analytics on publicly available information sources.
Healthcare: Analyse medical insurance claims data for financial analysis, fraud detection, and preferred patient treatment
plans. Analyse patient electronic health records for evaluation of patient care regimes and drug safety.
Mobile telecom: Discover mobile phone churn patterns based on analysis of call detail records and correlation with activity
in subscribers' networks of callers.
IT technical support: Perform large-scale text analytics on help desk support data and publicly available support forums to
correlate system failures with known problems.
Scientific research: Analyse scientific data to extract features (e.g., identify celestial objects from telescope imagery).
Internet travel: Improve product ranking (e.g., of hotels) by analysis of multi-years worth of web click logs.
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MAS 07 November 2012
Long-term service trends
Shorter lifecycles
Change in
ownership and
business model
Franco-British bilateral
workshop on Big Data
Consult-buildoperate
Rapid assembly and
integration of services,
to address customer’s
changing business needs
and opportunities
Assemble
from stock
Build to order
Assess-composeorchestrate
Bespoke systems, tailored,
put in place and dedicated
to running one application
for one customer, for a
number of years
9
Towards an open future …
▶ As a Tier 1 player in Cloud, Atos is becoming much more
pro-active in moving developments forward
– often in an open and collaborative manner with others,
who may also include our competitors
▶ Examples of this include:
– the Open Data Centre Alliance: a cloud user group,
defining common requirements for how cloud services
are delivered to (initially) large enterprises.
See: https://www.opendatacenteralliance.org
– Helix Nebula: an initiative to deliver cloud services (initially)
to European-based scientific research organisations
▶ Both are cases where an initial development and deployment is
expected to propagate to a much wider community, over time
▶ Another common factor between these developments is the
prevalence of Open Standards and Open Source tooling, and close
involvement with the research community which pioneers them
– Atos have an inside track on these developments with Atos
Research and Innovation (ARI), who live in this world: see
http://www.atosresearch.eu
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MAS 07 November 2012
Franco-British bilateral
workshop on Big Data
Staffing trends and approaches with
Utility and Cloud
MAS 07 November 2012
Franco-British bilateral
workshop on Big Data
▶ Addressing the issue will help avoid local (re-)inventions
▶ What can we do about it?
– Training
+ Increase ability to analyse customer
– Re-deployment
needs (solution architecture)
+ Plan capacity, manage risks
– Recruitment
Design
+ Address governance issues within
– Alliances
customer
+ Develop more flexible services
– Acquisitions
+ Developing and using Solutions
Templates
Administration
- Automate, e.g. using RBA
- Off-shore
+ Monitor operational exceptions
Operations
- Further automate
- Outsource to vendors
11
Big Data competences and roles
▶ New rolls and skills arise:
– Data Scientist
– Data Virtualization Specialist
– Data Stewards
– Big Data Architects
– Big Data Analists
– ….
▶ New knowledge is necessary!
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MAS 07 November 2012
Franco-British bilateral
workshop on Big Data
MAS 07 November 2012
Atos’ services during a migration
and services lifecycle
Solutions architecture
and planning
▶ Opportunity
assessment to
determine business
needs
▶ TCO analysis, norms,
trends, to help build a
business case
Franco-British bilateral
workshop on Big Data
Service implementation and integration
▶ Transition, standardisation, consolidation
▶ Conversion and migration
Customer
to be
▶ Identity management
▶ Service integration
▶ Establish portfolio of
Cloud offerings and
capabilities
▶ Solutions selection,
architecture and
brokerage
▶ Plateau
Planning
Operational
Cloud Services
Customer
as is
Traditional Services
▶
Optimize legacy use
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▶
Infrastructure, Platform,
Software as a Service
▶
Service aggregation
▶
Identity, authorisation,
security monitoring
▶
Contingency, recovery
MAS 07 November 2012
Service component relationships
Governance
Franco-British bilateral
workshop on Big Data
Outcomes
Business (= customers)
Prices
Outputs
What: service portfolio
Demand
Supply
Services
Generic
applications
Database
Middleware
Workplace
Data
centres
Servers
Security
Directories
Environment(s)
to be managed
Specific
applications
Who:
supplier
involvement
and integration
Storage
Networks
Inputs
How:
common
techniques
Processes
Costs
Tools
Organisation
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MAS 07 November 2012
ILM service offerings:
Consult - Build - Operate
Franco-British bilateral
workshop on Big Data
ILM Quick Scan – ILM Assessment – ILM Business Case
ILM Consultancy
Services
Alignment of
Technology
Business Goals
Data/Information
Dynamic Management of Data/Information
ILM Application
Integrated Solutions
Tiered Storage
Solutions
Tier 1
Tier 2
Tier 3
Storage On Demand
Mission
critical
Business
Critical
Productivity
important
Central Backup Services
Archiving on Demand
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Tier 4
Compliant
Archive
Tier 5
Tier 6
Instant
Access
Archive
Archive and
Backup to
tape
Using IaaS as a basis for adding
value
SaaS
SaaS:
use AppStore and DevPay-type facilities
deliver added value information
pay-per-use, with transactional charging
PaaS
PaaS:
test and development facilities
to create added value services
IaaS:
from HN
suppliers
Big Data
Processing facilities
Network access
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MAS 07 November 2012
Franco-British bilateral
workshop on Big Data
MAS 07 November 2012
EO Application Platform
Franco-British bilateral
workshop on Big Data
Data & Catalogue
User (CNR)
public
Sandbox
private
API
Web Interface
OCCI
ESA UNCLASSIED - For Offical Use
05/07/2012
17
Cloud
Controller
EO Application Platform at work
MAS 07 November 2012
Franco-British bilateral
workshop on Big Data
1. Instantiates the virtual machine and a development
environment
2. Uploads his/her software and defines input data
3. Adapts applications to the Cloud to exploit the
distributed computing (PaaS abstraction of the Hadoop
MapReduce model)
4. Uses the available toolbox that makes easier the
transition between the local development environment
(local workstation) and the Cloud
5. Tests, re-test, re-re-test, …
6. Transparently deploys the application and runs in
cluster mode against large archives of data!
User
ESA UNCLASSIED - For Offical Use
05/07/2012
18
For more information
please contact:
Mick Symonds
Principal Solutions Architect/Loose Cannon
Atos
B.5.L08, Papendorpseweg 93, 3528 BJ Utrecht
The Netherlands
[email protected]
m +31 651 755 779
19
More information and details…
▶ More information is documented in various
White Papers
– Shaping the Cloud
▶ And from the scientific community
and others
▶ Cloud Orchestration
– Written in summer 2010
– Proof of concept created with Cordys
and Open Source
▶ Augmented by: A Cloud Message Broker
– Extending connectivity to whatever else
is out there
▶ Downloadable from the Atos web site:
– http://atos.net/en-us/about_us/insights-andinnovation/scientific_community/scientific_comm
unity_whitepapers/default.htm
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MAS 07 November 2012
Franco-British bilateral
workshop on Big Data
MAS 07 November 2012
More on the Atos Cloud platforms…
Platform
Canopy
Yunano
Ownership,
control
Separate
JV with Yunano
company,
with VMware,
EMC
CIS
Trusted Agile A3C, Azure
Infrastructure
Oracle Extreme
Performance
Cloud
Helix Nebula
Atos
Atos
Atos with
Microsoft
partnership
Atos with Oracle
partnership
Consortium:
Atos
Atos prime role
Atos, with
IBM support
Initially Munich
Initially
Paris, UK,
Munich
Initially
Eindhoven
Tbd: Europe
Cloud huba and
satellites
France
-
XenDesktop,
XenApp, App-V,
ThinApp
Location(s) Cloud hubs
?
Cloud hubs and
satellites
SaaS
Yunano,
Zimbra,
ISV’s, via
AppStore
Ufida CRM, ERP
Sharepoint aaS,
Anytime Files,
Enterprise Project
Mgmt
PaaS
Java
development
environment,
vFabric
On Canopy
Web aaS, SAP FH:
Middleware for
SAP hosting, etc.
IaaS
VMware
On Canopy
Hypervisor
VMware
Usages
Yunano
ERP/CRM,
AppStore,
Hosting for
ISV’s, rigid
stack, limited
customisation
SME’s wanting
best-in-class
business
systems as a
service
Franco-British bilateral
workshop on Big Data
ISV’s
Development
environments
Anytime
Workplace
AIX
Azure
Oracle DB
-
-
IBM
development
and
middleware
VMware, Windows, VMware
Linux
-
Oracle Exadata/
Exalogic
Open Nebula
-
AIX as a
Service
VMware
VMware
Hyper-V
Oracle
KVM
XenServer
Professional
hosting for
customer’s
business-critical
systems, flexible
solutions and
customisation
Cloud-based
test and
development
environment
Office 365
and Azure
as a service
on Atos
private
cloud
Performance
boost for Oraclebased systems
Scalable
infrastructure
for scientific
research
organisations
Hosted virtual
workplaces,
XenClient
21
Cloud Services
Enterprises
wanting to
continue use
of AIX in a
flexible
environment

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