vitaly kozlovsky

1© Copyright 2014 EMC Corporation. All rights reserved.© Copyright 2014 EMC Corporation. All rights reserved.

Концепция третьей платформы информационных систем

Виталий Козловский[email protected]

консультант по развитию продуктов

EMC Center Of Excellence St.Petersburg


The Data Deluge This Decade

20090.8 Zetabytes

INFORMATIONGROWING

2020

44TIMESLARGER35.2 ZB

Source: IDC Digital Universe Study, sponsored by EMC, 2011

WORLDWIDE IT STAFFING WILL GROW BY

LESS THAN 50%


Big data


Many Industries Face Structural Change


Starbucks Mobile Application“The Winning Hand As Mobile, Card & Online Sales Converge”

“Starbucks was prepared for these shifts having invested over many years in the creation & development of proprietary world class digital & mobile payment and card technology & expertise. We are just beginning to appreciate the full magnitude & possibilities of the Starbucks mobile payment platform opportunity.”

10 MILLION MOBILE APPS USERS5 MILLION MOBILE TRANSACTIONS / WEEK$1.6 BILLION ON PAYMENT CARDS IN Q4 ‘13

Howard Schultz - Chairman, President and CEOJanuary 23, 2014


Mainframe, Mini Computer

Terminals

Mobile Cloud Big Data Social

Mobile Devices

1ST PLATFORM

3RD PLATFORM

MILLIONS OF USERS

THOUSANDSOF APPS

LAN/Internet Client/Server

PC

2ND PLATFORMHUNDREDS OF MILLIONS

OF USERSTENS OF THOUSANDS

OF APPS

BILLIONSOF USERS

MILLIONSOF APPS

Source: IDC


SOFTWARE-DEFINED DATA CENTER

Next-Gen Cloud Applications

2016 34M

2013 11M300%

Traditional Applications

2016 120M

2013 91M30%

TODAY’S DATA CENTER

Object/HDFSSoftware-Defined StorageConverged InfrastructurePolicy-Based AutomationData-Driven SecurityOn-Premise & Off-Premise

STORAGE SPAN, WIDTH, OR DISTRIBUTION

Physical Disk Multi-DC GEO-Store Hybrid Cloud

2014 Current State

Storage System

APPLI

CATIO

N D

ISTA

NC

E

PowerPath

Port B Port A

Network Switch C Network Switch D

Application Server

Carrier/Cloud

Virtualization Layer

CPU

APPLICATION

“4”

“3”

“2”

“1”

DATA

$/IOps$/GB

Latency

QoS

RASScales Down

Scales Up

Manageability at Scale

App Integration

0

2

4

“4”“3”“2”“1”


Data Lake

AnalyticsData mining

Reporting

Data Lake

Data Lake substitutes DataWarehouse

VM VM VM VM


Building Data LakesScale-Out In Memory Data Grids, Backed By Scale-Out HDFS

VM VM VM VM


3RD Platform Storage For MobileMoving To Object-based Storage Infrastructure


Cloud Gateway(Storage Tiering)

Cold Core Intelligent TieringDeployed Within The Data Center, Or To The Public Cloud

STO

RA

GE

TIE

RIN

G (

FAS

T) Hot Edge

Cold CoreHDD

Hot Edge

Warm Core(XtremeIO)

Cold CoreHDD

Cold Core

Public Cloud


Dynamic Deployment Of Block/File/Object/SQLStorage “VMs” Deployed By SDS

ViPRData Services

ViPRController

STORAGE CATALOGUE

Block

File

Object

Mobility

Replication

Dedup

SQL


Build/Deploy Apps Faster…...Leveraging Data Fabric Toolsets

VM VM VM VM

APPLICATION FABRIC

DATAFABRIC

PLATFORMAS A SERVICE


Mathematical Workload M&O

Internet

Existing Physical Network

Network Hypervisor

Virtual Networks

VM VM VM VM

VM VM VM VM

VM VM VM VM

VM VM VM VM

VM VM VM VM

VM VM VM VM


Building The BridgeViPR: Storage Arbitration For Both Platforms

PERFORMANCE & MISSION-CRITICAL APPS

Second Platform Infrastructure

VNX Isilon3rd Party

VMAX XtremIO

ViPR Data Services

VIPRController

Third Platform Infrastructure

BIG DATA & ANALYTIC APPLICATIONS


Top IT Spending Priorities For 2014

Source: Barclays CIO Survey, September 2013


Major Players Are Building Technology “Stacks”

Network

Storage

Server

Virtualization

OS

Database

Middleware

Applications


AD

VA

NC

ED

SE

CU

RIT

YPIVOTAL LABSPIVOTAL ONE

CLOUD FOUNDRY

END USER COMPUTINGSOFTWARE-DEFINED DATA CENTER

HYBRID CLOUD - vCHS

INFORMATION STORAGE & PROTECTIONINFORMATION SECURITY

INFORMATION INTELLIGENCE

Best Of Breed. Architected Horizontally, Not Vertically. Choice. Our Strategy: Build A Differentiated Stack


Our Strategy Gives Customers Choice


EMC Global Presence> 65,000 people in 90 countries

Melbourne, Australia

Rio de Janeiro, Brazil

Hopkinton, MAGlobal Headquarters

Bedford, MA

Franklin, MA

Cambridge, MA

Roy, UT

Singapore

Durham, NCApex, NCIrvine, CA

Burlington, Ontario

Duluth, GA

Santa Clara, CAPalo Alto, CA

Pleasanton, CA

Bangalore, India

Brentford, UK Vienna, AustriaPau, France

Rotterdam, Netherlands

St. Petersburg, Russia

Cairo, Egypt

Tel Aviv, Israel

Beijing, China

Shanghai, ChinaTokyo, Japan

Seoul, S. KoreaBe'er Sheva, Israel

R&D Center

Centers of Excellence

Customer Support Center

Executive Briefing Center

Global Solution and Engineering CenterManufacturing Center

Direct Presence

Seattle, WA

Chengdu, China

as of October 18, 2013

Sydney, Australia

Cork, Ireland


Interoperable With Any Cloud Orchestration Platform

ViPRData Services

ViPRControllerViPRData Services

ViPRController


Storage Bandwidth Control With SDNDynamic Control Of Backup, Mobility, & Replication Operations

TIME

BA

ND

WID

TH

Reserved For Other Network Traffic

Reserved For VMware Clustering

Reserved For RecoverPoint

Reserved For Other Application

Reserved For VPLEX

OVERALL CAPACITY

AVAILABLE CAPACITY


Start Building Data LakesScale-Out In Memory Data Grids, Backed By Scale-Out HDFS

VM VM VM VM


Server-Based PersistenceHot Edge & Horizontal Data Stack/Services

Server-BasedVolatile

Server-BasedNon-Volatile

VMware vSANSmall Clusters

ScaleIOThousands

ScaleIO + Cold Core

1000s

vitaly kozlovsky

Engineering

emc corporation

emc center of excellence

hdfs vm vm vm vm

data deluge

mobile apps users

data lakes scale

softwaredefined data

starbucks mobile application