infrastructure transformation for intelligent data centers of the future

© Copyright 2013 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice.

Intelligent Data Center Infrastructure Big Data IT Transformation

Donald Livengood on behalf of Amos Ferrari June 10, 2013

© Copyright 2013 Hewlett-Packard Development Company, L.P. The information contained herein is subject to change without notice. 3

Forward-looking statements

This document contains forward looking statements regarding future operations, product development, product capabilities and availability dates. This information is subject to substantial uncertainties and is subject to change at any time without prior notification. Statements contained in this document concerning these matters only reflect Hewlett Packard's predictions and / or expectations as of the date of this document and actual results and future plans of Hewlett-Packard may differ significantly as a result of, among other things, changes in product strategy resulting from technological, internal corporate, market and other changes. This is not a commitment to deliver any material, code or functionality and should not be relied upon in making purchasing decisions.

This is a rolling (up to three year) roadmap and is subject to change without notice.


My background

Title

VP, Big Data Services

IT industry experience • Application Services Manager – UPS USA

• Director, Technical Support – UPS USA

• Technical Services Manager – Spain

Professional information • Computer Science engineer

• University of Minnesota

Years at HP

13

Current responsibilities VP, Global Technology Services Consulting Big Data Practice – leads the envisioning, development and implementation of Big Data related services globally

Name: Tom Norton E-mail: [email protected]


My background

Title

Global Consulting Strategist

TS Consulting

IT industry experience • Big Data

• Unified Communications & Collaboration

• Contact Center

• Telco BSS

Professional information • Certified PM

• IT Architect

Years at HP

27

Current responsibilities Responsible for the development, pursuit, and deployment of HP’s Big Data Infrastructure Services for the Strategic & Planning area

Name: Amos Ferrari

E-mail: [email protected]


Big Data & IT


Big Data

Main value for you:

Additional business value

New customer services creation

Differentiator and value creation

Business control

“Big Data is a class of data challenges, due to increasing Volume, Velocity, Variety, and Vulnerability of data being processed and consumed, that are beyond the capabilities of the traditional software, architecture, and processes to effectively manage and utilize.”


Big Data Needs

Scale

Source Speed Security

Volume Variety Velocity Vulnerability


Enterprises can’t keep up

Time consuming Data integration

Real-time Insight needed

Unable to secure

Flash flooding of legacy data bases

Magnitude of the data


New Data Management and analytics technologies

Variety Volume

Velocity

SAP HANA

PDW

Vertica

Hadoop

Autonomy

Semi-Structured

Structured

Unstructured

100% of Data Enable me to: on

Store

Capture

Manage

Analyze

Optimize


To energy and algorithm optimized:

HP Moonshot

From General Purpose architecture

With new Infrastructure technologies

To Software Defined Networks

From hardware networks

From disk

To Virtualized Storage and persistent memory

Today

Physical High performance network

High Performance attached Storage

Today -

Today

Scale Out Architecture

Enabling Real Time Services

Scalable and Cost effective

Managed and Secure

Infrastructure Enable me to: on

Store

Capture

Manage

Analyze

Optimize


Big Data requires Infrastructure Transformation


Today Data Context

Op

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tio

n, G

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ern

an

ce, S

ecu

rity

Op

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tio

n, G

ov

ern

an

ce, S

ecu

rity

Op

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tio

n, G

ov

ern

an

ce, S

ecu

rity

Op

era

tio

n, G

ov

ern

an

ce, S

ecu

rity

Social Media Data

Forum

Blog

Feeds

Web

Clicks

Multi-Media

Audio

Video

Images

Document Management

Content Management

File Sharing

File Hosting

Collaboration

Search

Message Data

IM and VOIP

Messaging System

Sensors Data

GPS

Sensors devices

RFID

Other events

Op

erat

ion

, Go

ver

nan

ce, S

ecu

rity

O

per

atio

n, G

ov

ern

ance

, Sec

uri

ty

Classic ETL Processing

Business Transactions and Interactions


CRM – ERM – SCM FMS – HRM

$ € ¥ Transaction Data

Analytical, Dashboards, Reports, Visualization

Enterprise Data Warehouse

Business Intelligence & Analytics

Internal Content

External Content or Discarded Content

Managed Content Unmanaged Content


Expanding today Data Management Technologies is expensive and in most cases will not solve

Finding out useful information requires powerful and massive processing

Sto

rag

e O

nly

Gri

d (

SA

N/N

AS

)

Moving data to compute

doesn’t scale

Can’t explore original, High

fidelity raw data

Archiving Cheap storage Expensive restore

Today's Data Architecture

Classic ETL Processing




$ € ¥ Transaction Data

Analytical, Dashboards, Reports, Visualization


Business Intelligence & Analytics

Gaps in

Message Data

Document Management

Social Media Data

Multi-Media

Sensors Data

Time consuming Data integration

Flash flooding of legacy data bases

Magnitude of the data

Real-time Insight needed

Unable to secure

Discarded Content, too expensive to retain store manage and analyze


Big Data Transformation Architecture

Big Data infrastructure

Insight Processing

Protection & Compliance Management

Infrastructure Integration


Analytical, Dashboards Reports, Visualization

Business Intelligence


Web, Mobile

CRM – ERM – SCM FMS – HRM Value

Creation

share, refine & development

Message Data

Document Management

Social Media Data

Multi-Media

Sensors Data


Big Data infrastructure Architecture components


Building the Intelligent Data Center


Insight Processing – For fast, flexible and predictable data refinement

Protection & Compliance Management – For secure, compliant and reduced risk data management

Infrastructure Integration – For full integration into the data center, traditional data

platforms and the holistic IT environment

Social Media Data

Multi-Media

Document Management

Message Data

Sensors Data

Cloud


Cloud


Analytical Dashboards and Reporting

Organizational Applications

Operations

Sales and Marketing

Legal

Web and Mobile Interaction Data

CRM – ERM – SCM – FMS - HRM


Components


Big Data Protection

Information Insight Processing

Compute Consumption Collection

Protection and Compliance Management

Information Infrastructure Integration

Security Governance Technology and

Operations Integration

Compliance Protection

Destruction

Security Backup &

Restoration

Governance

Archival Retention


Big Data infrastructure functional architecture

Technology Integration

Se

curi

ty

Op

era

tion

s

Big Data Converged, Automated, Energy efficient infrastructure

Activity logging Intrusion Prevention

Switch virtualization Virtual application network

SSL/VPN Networks Storage replication

Server scale-out management

Collection Compute Consumption

Protection

Big Data Management

Compliance

Big Data Storage

Big Data Processing On Line / Batch Analysis

Internal / External Data

Structured / Unstructured

Real Time

Backup and Recovery

Governance

Privacy and Security

Destruction Archival Retention


Big Data Compute key capabilities

Vertica

…

Private

Hadoop

Cloud

Machine 1

RAM

Processors

Memory

Scale-Out

In-Memory

CPU

CPU

CPU

Rack 1

Se

rve

r S

erv

er

Se

rve

r S

erv

er

Se

rve

r S

erv

er

Se

rve

r S

erv

er

Se

rve

r S

erv

er

serv

er

Se

rve

r

Rack 2

Se

rve

r S

erv

er

Se

rve

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erv

er

Se

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erv

er

Se

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erv

er

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erv

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serv

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Se

rve

r

Rack n

Se

rve

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erv

er

Se

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erv

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erv

er

Se

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erv

er

Se

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erv

er

serv

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Se

rve

r

Hybrid


Big Data Management & Integration key capabilities

• End 2 End Big Data SLA Services • Data in Transit Protection • Platform Management • …

Computation Collection Consumption

Security & Compliance

Converged, Automated, Energy Efficient Infrastructure

Level of service


HP HAVEn Big Data technologies mapping

Information Infrastructure integration

Sec

uri

ty

Op

era

tion

s

Big Data Converged, Automated, Energy efficient infrastructure

Activity logging

Intrusion Prevention

Switch virtualization Virtual application network

SSL/VPN Networks Storage replication

Server scale-out

management

Collection Computation Consumption

Protection

Information Management

Compliance

Information Insight processing

Open Source

Internal / External Data

Structured / Unstructured

Partners

Backup and Recovery

Governance

Privacy and Security

Destruction Archival Retention

Consumption

HP StoreEver HP StoreOnce HP StoreOnce HP StoreAll

OPERATIONS ORCHESTRATION HP DataProtector7

HP FlexFabric

SERVER AUTOMATION

HP

Big Data Governance

SAP- HANA Microsoft PDW

Information Governance

Content Management

eDiscovery


Big Data IT Infrastructure to enable Intelligent Data Center of the future Examples


Transforming Today’s Architecture

Big Data infrastructure example with Hadoop

Insight Processing

Protection & Compliance Management

Kerberos access. Identity management, Network optimization.

Centralized Management


Reports and Interactive Apps

RDBMS (Aggregated data)


Web, Mobile


Message Data

Document Management

Social Media Data

Multi-Media

Sensors Data

Hadoop Explore all original, High fidelity

raw data

Replicate data in Hadoop Archive only value data

Move some data to BI systems and also use

Hadoop MapReduce


Expanding capabilities

Big Data infrastructure example with Hadoop and Vertica

Kerberos access. Identity management, Network optimization. Centralized

Management




Web, Mobile


Message Data

Document Management

Social Media Data

Multi-Media

Sensors Data

Hadoop Explore all

original, High fidelity raw data

Keep data in Hadoop

Cheap store & restore

Vertica Real Time structured Analytics

Move Refined Info to Vertica

Easy protect and comply

Vertica Real Time Analytics

Move some data to BI systems and also use

Hadoop MapReduce


Inserting Intelligence

Big Data infrastructure example with Hadoop and Autonomy

Kerberos access. Identity management, Network optimization. Centralized

Management




Web, Mobile


Message Data

Document Management

Social Media Data

Multi-Media

Sensors Data

Hadoop Explore all

original, High fidelity raw data

Keep data in Hadoop

Cheap store & restore

Au

ton

om

y Id

ol

Autonomy Real Time Search

Access and search all Data

Easy protect and comply

Move some data to BI systems and

also use Hadoop MapReduce Autonomy

Real Time Universal Access


Big Data transformation IT Infrastructure to enable Intelligent Data Center of the future Where to start


Suggested actions

Identify Critical DW systems for potential initial target implementation

Outline today’s data bottlenecks related to Big Data

Evaluate areas where today’s raw data is not used or deleted

! Determine demand for archived data from the business and potential services that you can offer

Determine your IT Big Data Architecture Strategy.


Start today

Where to start

Implement Big Data infrastructure

Determine readiness ,Storage, Governance, Security …

Derive IT Architecture & Roadmap

Derive IT Strategy & define initiative

Identify Big Data Strategy

Information sources

Business and Technical feasibility

!

Business Case

People

Link with BI and Analytics and other business cases

Expand infrastructure

Define Solutions Standards & Design

Plan for Big Data Services


HP Big Data Solutions

Big Data as a Service

HP Big Data Analytics for IT

HP Actionable Intelligence Solutions

HAVEn – HP’s Big data analytics platform

Hadoop • Autonomy • Vertica • Enterprise Security • n of solutions

Big Data Solutions

Vertica Community Edition

Autonomy Legacy Data Cleanup

HP IT Management

HP Big Data Architecture Strategy Services, HP Big Data System Infrastructure services, HP Big Data Protection Services

Operate yourself Consume as a service

Professional Services


Take the lead Providing IT Big Data Services by Transforming data Infrastructure to enable Intelligent Data Center of the future


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Thank you

infrastructure transformation for intelligent data centers of the future

Technology

big data services

vulnerability of data

big data practice

product development

big data main value

new data management

data context operation

class of data challenges