BDaaS FrancoBritish bilateral workshop on Big Data London November 2012 Mick Symonds Principal Solutions Architect Atos MS NL 7 November 2012 Introducing Atos Atos is an international information technology services company delivering hitech transactional services consulting system ID: 385225
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Slide1
Everything as a Service, including Big Data: BDaaS
Franco-British bilateral workshop on Big DataLondonNovember 2012
Mick Symonds
Principal Solutions Architect, Atos MS NL,
7 November 2012Slide2
Introducing Atos
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 countriesWorldwide headquarters in Bezons / Paris, FranceAtos 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 AGSlide3
Foundation IT Services:Global Delivery
to Trusted Partner
ERP Applications
Desktop
Server Management
900,000 SAP users
2,4
Million Seats
45 Million calls / year
105,000 managed server instances (74,000 managed physical servers)
Data Centers
13 Global Data Centers +
50 Local / Regional Data Centers
93,000 sq meters Data Center
1.42 average global virtualization ratio
Hosting:
40,000 MIPS 41,500 terabytes storage 6000 COD/IaaS/Cloud instances
Enterprise Management Centers
Global EMC’s in Timisoara and Kuala Lumpur & 15 local EMCs with almost 700 staff
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 mailboxesSlide4
Powering progress for our clients
Financial
Services
Public
Sector, Healthcare & Transport
Energy & Utilities
Manufacturing, Retail & Services
Telecom, Media & TechnologySlide5
What I want to tell you about
It feels strange to come and tell Researchers about “Innovation”Most of our “innovation” is finding out what researchers and vendors are reportingwe are a long way down the food chain in most respectsHowever, we find that one man’s business-as-usual is sometimes another man’s innovationThe 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 managementYou can liberate yourselves from the tedious grind of production operations:a. by delegating the structured deployment of rules and policies to usb. by using us to supply point/niche capabilitiesc. to provide enabling facilities for people who provide real added valueSlide6
What is Big Data, the 3-4 traditional V’s
Source:
O
racleSlide7
From the traditional 3-4 V’s towards
the 5-6 V’s
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.
ValueSlide8
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.
Big Data is transforming business, as well as researchSlide9
Long-term service trends
Shorter lifecycles
Change in ownership and business model
Consult-build-operate
Assess-compose-orchestrate
Assemble
from stock
Rapid assembly and integration of services,
to address
customer’s changing business needs and opportunities
Build to order
Bespoke systems, tailored, put
in place and dedicated to running one application for one customer, for a number of yearsSlide10
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.orgHelix Nebula: an initiative to deliver cloud services (initially) to European-based scientific research organisationsBoth are cases where an initial development and deployment is expected to propagate to a much wider community, over timeAnother common factor between these developments is the prevalence of Open Standards and Open Source tooling, and close involvement with the research community which pioneers themAtos have an inside track on these developments with Atos Research and Innovation (ARI), who live in this world: see http://www.atosresearch.eu Slide11
Addressing the issue will help avoid local (re-)inventionsWhat can we do about it?
TrainingRe-deploymentRecruitmentAlliancesAcquisitions
Staffing trends and approaches with Utility and Cloud
+
Increase
ability to analyse customer
needs
(solution architecture)
+
Plan
capacity, manage
risks
+
Address
governance issues within
customer
+
Develop
more flexible
services
+
Developing
and using Solutions
Templates
-
Automate
, e.g. using RBA
-
Off-shore
+
Monitor
operational
exceptions
-
Further automate
-
Outsource to vendors
Operations
Administration
DesignSlide12
Big Data competences and roles
New rolls and skills arise:Data ScientistData Virtualization SpecialistData StewardsBig Data ArchitectsBig Data Analists
….
New knowledge is necessary!Slide13
Atos’ services during a migration and services lifecycle
Customer
to be
Service implementation and integration
Transition, standardisation
, consolidation
Conversion and migration
Identity management
Service
integration
Infrastructure, Platform, Software
as
a Service
Service aggregation
Identity
,
authorisation, security
monitoring
Contingency,
recovery
Operational
Cloud Services
Optimize
legacy
use
Traditional Services
Solutions architecture and planning
Opportunity assessment to determine
business needs
TCO
analysis, norms,
trends, to help build a business case
Establi
sh portfolio of Cloud offerings and capabilities
Solutions
selection, architecture and brokerage
Plateau
Planning
Customer
as is
9.
Contract, SL different-
iation
8.
Run Book
automation
4. Global sourcing/off-shoring
5. Physical consolidation
6. Demand
/ Supply
structures
7. Rational consolidation
3. Logical
consolid-ation
10. Information lifecycle management
11. On
Demand, Utility Computing
2. Outsourcing
1.
Select standardsSlide14
Service component relationships
Services
What: service portfolio
Who:
supplier
involvement
and integration
Processes
Tools
Organisation
How:
common
techniques
Costs
Prices
Environment(s) to be managed
InputsDemand
SupplyBusiness (= customers)
GovernanceData
centresDirectoriesWorkplace
Storage
Security
Networks
Servers
Database
Middleware
Specific
applications
Generic
applications
Outputs
OutcomesSlide15
Dynamic Management of Data/Information
Tiered
Storage Solutions
Storage On Demand
Central Backup Services
Archiving on Demand
ILM Application Integrated Solutions
Tier 2
Tier 3
Tier 4
Tier 5
Tier 1
Mission
critical
Business
Critical
Productivity
important
Compliant
Archive
Instant
Access
Archive
Tier 6
Archive and Backup to tape
ILM
service offerings:
Consult
- Build - Operate
Business Goals
Data/Information
Technology
Alignment of
ILM
Consultancy Services
ILM Quick Scan – ILM Assessment – ILM Business CaseSlide16
Using IaaS as a basis for adding value
Big DataProcessing facilitiesNetwork access
PaaS:
test and development facilities
to create added value services
SaaS:use AppStore and DevPay-type facilitiesdeliver added value informationpay-per-use, with transactional chargingIaaS:from HN
suppliers
P
aaS
S
aaSSlide17
EO Application Platform
ESA UNCLASSIED - For Offical Use 05/07/2012
Data & Catalogue
User (CNR)
Cloud
Controller
API
OCCI
Web Interface
Sandbox
private
publicSlide18
User
EO Application Platform at work
Instantiates
the virtual machine and a development environment
Uploads
his/her software and defines input dataAdapts applications to the Cloud to exploit the distributed computing (PaaS abstraction of the Hadoop MapReduce model)Uses the available toolbox
that makes
easier the transition
between the local development environment (local workstation) and the Cloud
Tests
, re-test, re-re-test, …
Transparently deploys the application and runs in cluster mode against large archives of data!
ESA UNCLASSIED - For Offical Use 05/07/2012Slide19
For more information please contact:
Mick SymondsPrincipal Solutions Architect/Loose Cannon AtosB.5.L08, Papendorpseweg 93, 3528 BJ Utrecht The Netherlands
michael.symonds@atos.net
m +31 651 755 779
19Slide20
More information and details…
More information is documented in various White PapersShaping the CloudAnd from the scientific community and others Cloud Orchestration
Written in summer 2010
Proof of concept created with
Cordys
and Open SourceAugmented by: A Cloud Message BrokerExtending connectivity to whatever else is out thereDownloadable from the Atos web site:http://atos.net/en-us/about_us/insights-and-innovation/scientific_community/scientific_community_whitepapers/default.htmSlide21
More on the Atos Cloud platforms…
Platform
Canopy
Yunano
CIS
Trusted Agile InfrastructureA3C, Azure
Oracle Extreme Performance Cloud
Helix Nebula
Anytime Workplace
AIX
Owner-ship, control
Separate
company,
with VMware, EMC
JV with Yunano
AtosAtosAtos with Microsoft partnership
Atos with Oracle partnershipConsortium: Atos prime roleAtosAtos, with IBM supportLocation(s)Cloud hubs?Cloud hubs and satellitesInitially MunichInitially Paris, UK, MunichInitially EindhovenTbd: Europe
Cloud huba and satellites
FranceSaaSYunano
, Zimbra, ISV’s, via AppStoreUfida
CRM, ERP
Sharepoint
aaS
, Anytime Files, Enterprise Project
Mgmt
ISV’s
-
XenDesktop
,
XenApp
, App-V,
ThinApp
PaaS
Java development environment,
vFabric
On
Canopy
Web
aaS
, SAP FH: Middleware for SAP hosting, etc.
Development environments
Azure
Oracle DB
-
-
IBM development and middleware
IaaS
VMware
On Canopy
VMware, Windows, Linux
VMware
-
Oracle Exadata/
Exalogic
Open Nebula
-
AIX
as a Service
Hyper-visor
VMware
VMware
VMware
Hyper-V
Oracle
KVM
XenServer
Usages
Yunano
ERP/CRM,
AppStore
, Hosting for ISV’s, rigid
stack, limited customisation
SME’s wanting best-in-class business systems as a service
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 Oracle-based systems
Scalable infrastructure for scientific research organisations
Hosted
virtual
workplaces
,
XenClient
Enterprises wanting to continue use of AIX in a flexible environment
Cloud Services