China Research Lab © 2006 IBM Corporation IBM Confidential Introduction to IBM Cloud Products and Cloud- based Analysis Platform Research at CRL Chen Wang

China Research Lab

IBM Confidential © 2006 IBM Corporation

Introduction to IBM Cloud Products and Cloud-based Analysis Platform Research at CRL

Chen Wang ( 王晨 )IBM China Research Laboratory

China Research Lab

© 2003 IBM CorporationIBM Confidential

About Me

Received Ph.D. degree of computer science from Fudan University in 2005

Joined IBM China Research Lab since 2005

Major research areas

– Database and data mining [2002 to 2005]• Focus: to solve scalability and performance issues of querying and mining

over graph like data• Representatives : KDD’04, SIGMOD’05, PAKDD’04, JCST, WWW J, DKE J

– Semantic web and data management [2005 to 2008]• Focus: to develop scalable and efficient RDF data store in a single node• Representatives : SIGMOD’08, ICDE’09, WWW’08, WWW’07, VLDB’07

– Semantic web + data mining + cloud computing [Now!]• Focus: to deliver knowledge discovery system over RDF data in cloud

environment to enable business intelligence in healthcare area• Representatives : …

Homepage– http://www.research.ibm.com/people/w/wang

China Research Lab


Agenda

IBM cloud offerings (1 hour and 30 min)

– CloudBurst (BlueCloud)

– Tivoli service automation management (TSAM)

Break (30 min)

Cloud-based analysis platform research at CRL (50 min)

Q & A (10 min)

China Research Lab


IT infrastructure is reaching a breaking point

85% idleIn distributed computing environments, up to 85% of computing capacity sits idle.

Consumer product and retail industries lose about $40 billion annually, or 3.5 percent of their sales, due to supply chain inefficiencies.

33% of consumers notified of a security breach will terminate their relationship with the company they perceive as responsible.

33% 40 billion

Explosion of information driving 54% growth in storage shipments every year.

1.5x 70¢ per $170% on average is spent on maintaining current IT infrastructures versus adding new capabilities.

China Research Lab


Video: Cloud Computing in IBM Expert’s eyes

Irving Wladawsky-Berger discusses cloud computing with Tech Web TV

China Research Lab


We are talking about a way to significantly lower cost…

Traditional Infrastructure

• x86 servers – one application per server• 5% hardware utilization• Manual operations & maintenance

Internal Private Cloud

• x86 servers – full virtualization • Embedded service management system• Automated self service

versus

Can reduce IT labor cost by 50% in configuration, operations, management and monitoring

Can improve capital utilization by 75%, significantly reducing license costs

Reduce provisioning cycle times from weeks to minutes

Can reduce end user IT support costs by up to 40%

Internal Private Cloud drives cost savings

Scale

Unit cost

Traditional Infrastructure

InternalCloud

(IBM projections based on customer work)

China Research Lab


Agenda

IBM cloud offerings

– CloudBurst

• Hardware• Software• Architecture


China Research Lab


What Is IBM CloudBurst?

IBM CloudBurst leverages an IBM pre-integrated service delivery platform that include the hardware, storage, networking, virtualization and service management software to create a private cloud computing environment.

China Research Lab


An industry standard rack cabinet

External dimensions:

– Height: 1999 mm (78.7 in)

– Width: 605 mm (23.8 in)

– Depth: 1001 mm (39.4 in)

– Weight: 124.7 kg (275 lb)

Comes with a front door, rear doors, and side panels installed.

Has the following features:

– Front stabilizer foot

– Six 1-U side-wall compartments

– Lockable doors and side panels

– Room for cable management

IBM S2 42U

China Research Lab


Housing a cloud computing infrastructure management server …

FRONT VIEW

REAR VIEW

IBM x3650M2 rack-mount server

HDD

Up to 12

x3650M2

– Form:

• 2U

– Processor:

• Dual Quad Core Intel® Xeon® X5520

• 2.26GHz, 8MB L2 cache, 80W

– Memory:

• 24GB RAM

– Storage:

• HDD 6x 146GB SAS 10K

– Ethernet interfaces:

• Four 1 Gbps NICs • Dual port 4 Gbps FC

China Research Lab


… a cloud compute platform …

HS22

– Form:

• 1U

– Processor:

• Dual Quad Core Intel® Xeon ® X5560 4C• 2.8GHz, 8MB L2 cache, 95W

– Memory:

• 48GB RAM

– HDD:

• Diskless

– Ethernet interfaces:

• Two 1 Gbps NICs• Dual port 4Gbps FC

– USB:

• VMware ESXi Hypervisor™ on embedded USB key

IBM BladeCenter HS22

China Research Lab


… imbedded into a chassis

IBM BladeCenter H Chassis

BladeCenter H chassis

– Form:

• 9U

– Features:

• Up to 14 blade bays• Advanced Management Module standard, plus

optional module for redundancy• USB-based keyboard, video, mouse (KVM),

Ethernet, USB• Optical drive and two USB connections• High-speed fabric with eight data channels to

every blade, four of which can be 10 Gb• Supporting industry-standard I/O switches• Light path diagnostics• Predictive Failure Analysis• Support for IBM System Storage solutions

(Including DS and NAS family of products) and many widely adopted non-IBM storage offerings External storage

FRONT VIEW

REAR VIEW

Example: 8 blade servers followed by 6 empty slots

Example: on the left two FC switches and two Ethernet switches.

On the right side a management module with console cables.

China Research Lab


The rack also includes IBM system storage …

DS3400 FC attached storage

– Dual active RAID controller

– Host Interface:

• 4 Gbps Fiber Channel (FC) interface technology

– Direct-attach storage (DAS) or SAN solution—start with a DAS configuration and seamlessly transition to a FC SAN when ready

– Easy to deploy and manage with the DS3000 Storage Manager

– 5.4 TB of storage capacity with twelve 450 GB hot-swappable 15K drives

IBM System Storage DS3400

China Research Lab


… and network components

BladeCenter H (I/O)

– Redundant 4G FC Networking - Qlogic FC SM

• QLogic 20-port 4 Gb Fibre Channel Switch Module

– Redundant 1G Ethernet Networking – SMC 8126L2

China Research Lab


Agenda

IBM cloud offerings

– CloudBurst



China Research Lab


Cloud computing infrastructure management server

* Previous product name was VMware VirtualCenter 2.5u4

Operating System Windows2003R2 Enterprise Edition 32 bit

(includes MS Active Directory)

Database Server MS SQL Server Enterprise Edition

MS SQL Server Express (imbedded w/ VMWare VirtualCenter (now vCenter Server)

Platform Management Tools

BladeCenter Open Fabric Manager (BOFM)

Active Energy Manager

IBM Systems Director 6.1.1

IBM BOFM v3 plugin

IBM Active Energy Manager 4.0

Server Management Tools IBM ToolsCenter 1.1

Storage Management Tools

LSI SMI-S provider for DS3400

IBM DS Storage Manager for DS4000 10.36

LMI SMI-S

Virtualization Management Tools VMware vCenter Server 2.5 *

(requires MS Active Directory)

China Research Lab


CloudBurst software stack Bare Metal Hypervisor on HS22 blade VMWare ESXi 3.5 U4 Hypervisor

Operating System

Network File System

Novell SUSE Linux Enterprise 10 SP 2

NFS

Database Server IBM DB2 Enterprise Server Edition V9.1 for Linux

Web Application Server, including IBM HTTP server

IBM WebSphere Application Server Network Deployment 6.1.0.13

Directory Server IBM Tivoli Directory Server 6.1.0.1

Monitoring IBM Tivoli Monitoring 6.2.1 (OS pack)

IBM Tivoli Monitoring for Energy Mgmt 6.2

Storage Management Client IBM Tivoli Storage Manager client 6.1

Provisioning Management IBM Tivoli Provisioning Manager 7.1

CloudBurst application IBM Tivoli Service Management pack including appliance wizards

China Research Lab


Agenda

IBM cloud offerings

– CloudBurst



China Research Lab


Mid-plane

AM

M2

AM

M2

Mid-plane

Customer SAN NetworkCustomer Ethernet Network

x3650 M2

HS

22 Blade

HS

22 Blade

HS

22 Blade

HS

22 Blade

HS

22 Blade

HS

22 Blade

HS

22 Blade

HS

22 Blade

HS

22 Blade

HS

22 Blade

HS

22 Blade

HS

22 Blade

HS

22 Blade

HS

22 Blade

24 port 1Gps Ethernet Switch

24 port 1Gps Ethernet Switch

1G Ethernet SwitchMSIM-L Bay 9

1G Ethernet SwitchMSIM-L Bay 7

20port FC SM 20port FC SMBay 3 Bay 4

PD

U 1

PD

U 2

Controller A

IBM StorageVMWare ESXi Hypervisor

SUSE & NFS

TPM

ITMWAS ND

DB2 ESE

ITDS

CloudBurst

IBM

Dire

ctor

.

T

ools

Cen

ter

S

QL

Ser

ver

V

irtua

l Cen

ter

BO

FM

A

ctiv

e E

nerg

y

IBM

Sto

rage

Mgr

3650 M2 Server

Windows Server

Controller B

China Research Lab


Built-in Virtualization

Understand virtual and physical resource usage

Dynamically manage virtual workloads to optimize resource usage

Automatically migrate virtual machines across systems to maintain service levels

…Increases utilization for lower capital expense

China Research Lab


42U Standard Rack

3650M2

1 2 3 4 5 6 7 8 9 10 11 12 13 14

BladeCenter H

DS3400

Network Components

1 BladeCenter H with 4 blades*

*First HS22 blade server is reserved for the CloudBurst software stack

Base configuration

China Research Lab


1 2 3 4 5 6 7 8 9 10 11 12 13 14

BladeCenter H

HS22 Blades

Monitoring VM Image Server VM

BlueCode VM

VMWare ESXi Hypervisor

SUSE

TPM

WAS ND

DB2 ESE

ITDS

CloudBurst

CloudBurst VM

BlueCode VM


SUSE

DB2 ESE

ITM

BlueCode VM


SUSE + NFS + TFTP

CloudBurst software stack shipped as VMware images to run on the first HS22 blade server

China Research Lab


Agenda

IBM cloud offerings

– CloudBurst

– BlueCloud


China Research Lab


IBM to Unveil Plans for “Blue Cloud” on 11/15

Family of ready-to-use cloud computing offerings – Based on open standards and open source software together with

IBM software, systems technology and services

– First offering to support Power and x86 processors

– Plans to support System z and highly dense rack clusters

Reduces IT management complexity and increases business responsiveness

Supports both existing and emerging, data-intensive workloads Vietnamese Ministry of Science and Technology plans to leverage

Almaden Research Center’s cloud environment to run country innovation portal

Initial Blue Cloud offering targeted for Spring, 2008 availability

China Research Lab


Forces Driving Cloud Computing

Requires massively scalable cloud infrastructures to serve billions of heterogeneous browser-based clients

Increased network capacity and availability

Fast growth of mobile commerce

Advances in computer

architecture and

price/performance

Explosion of data intensive

applications on Internet

China Research Lab


Blue Cloud Initial Offering – Targeted for Spring 2008Delivers a massively scalable and flexible compute platform for hosting both existing and emerging data-intensive workloads.

IBM Monitoring v.6

DB2

Provisioning Management Stack

Provisioning Manager v.5.1

WebSphere Application Server

MonitoringProvisioning Baremetal & Virtual Machines

Linux with Xen

Tivoli Monitoring Agent

Virtualized Infrastructure Based on Linux & Xen

VirtualMachine

VirtualMachine

VirtualMachine

VirtualMachine

BladeCenterBladeCenter

Apache

•Based on open standards and open source software

•Includes IBM software, systems technology and services

•Supports both Power and x86 processors

•Web 2.0 resource reservation system

China Research Lab


IBM and Massive Scale Computing

IBM is uniquely qualified to lead in cloud computing

Blue Cloud builds off of IBM’s decades of experience developing and leading massive-scale computing:

– Parallel Sysplex

– IBM’s Deep Blue SP Cluster

– Blue Gene

– Grid Computing

China Research Lab


Business Benefits of Blue Cloud

•Cost efficient model for creating and acquiring information services

•Reduces IT management complexity

•Increases business responsiveness with real-time capacity reallocation as demand for compute power grows

•Powers both existing and emerging data-intensive workloads

China Research Lab


70 active incubations10 new products

Technology Incubation Cloud for IBM Employees

China Research Lab


IBM Research Computing Cloud (RC2)

A ‘living lab’ to advance research strategies

Provides self service ‘on demand’ delivery solution for research computing resources

Integrates existing assets and products with SOA

Zero touch support for the full life cycle of service delivery– Order creation– Approval process– E-mail notification– Automated provisioning– Monitoring

RC2

Enterprise Service Bus

Virtualized Infrastructure

Business Process Workflow Management

Business Process Workflow Application

Business Service Platform

Self - Service

Portal

China Research Lab


Vietnam Ministry Leverages Cloud to Run Innovation Program

Students

Teachers

Researchers

VIP pilot hosted on IBM’s Blue Cloud

computing infrastructure at

Almaden

VIP, powered by IBM Innovation Factory, provides a platform to foster collaborative innovation among major universities and research institutes.

VISTA Innovation Portal (VIP)

BlogsBlogs WikisWikis ForumsForums

ProfilesProfiles Social TaggingSocial Tagging

Information DiscoveryInformation Discovery

IBM Innovation Factory

China Research Lab


Summary

IBM unveiling new cloud computing offerings to respond to customer needs:

– Explore extreme scale quickly and easily

– Share infrastructure resources efficiently

– Simplify IT management

– Handle new and emerging workloads

– Provide a platform to encourage open collaboration

A white paper, “Cloud Computing” from High Performance on Demand Solutions available at: http://www.ibm.com/developerworks/websphere/zones/hipods/library.html

China Research Lab


蓝云成功案例 1: 中国无锡科教产业园云计算中心

2008 年 2 月 1 日， IBM在中国无锡太湖新城科教产业园建立第一个云计算中心；该中心将为中国新兴软件公司提供接入一个虚拟计算环境的能力，从而鼎力支持其开发活动；是全球第一个实现商业运营的云计算中心。

China Research Lab


该平台可以直接为园区的软件外包公司以及周边的企业提供数据中心的服务；通过在云计算平台上搭建完整的 IBM Rational 软件交付平台，可以为各软件公司提供高品质的开发和测试等外包服务；该云计算平台可协助园区实现软件许可证租借、培训等商业服务模式。

蓝云成功案例 1: 中国无锡科教产业园云计算中心

China Research Lab

© 2003 IBM CorporationIBM Confidential 35

谷歌

IBM 研究中心

首批入选大学名单

• 倡导大学推动开放式标准和新兴并行计算模型

• 联合提供硬件、软件、服务支持新的并行计算课程

• 三大计算 “云团”

培养具备下一代“云计算”技能的人才

美国华盛顿大学

蓝云成功案例 2 ：与 Google 进行的学术合作

China Research Lab


•连接当地 5 个数据中心

•托管多个客户的业务系统

•基于订阅和使用计费

•基于 IBM System x 和 System p

•增加的蓝云功能– 部署 SAN

– 网络虚拟化– 发布到多个数据中心– 部署复杂应用

优势– 按使用计费，不是一次投入– 设备和位置的独立性

•通过多个数据中心的云计算资源池提供可靠性

•可利用其他数据中心的处理能力增加扩展性

•符合 ISO27002 标准的安全性

商业模式•“ ”按小时计费

•把基础架构作为服务，客户可以迅速获得或释放资源

•云计算作为传统托管服务的补充，并将逐渐增长

蓝云成功案例 3 ：荷兰 iTricity IDC

China Research Lab


Agenda

IBM cloud offerings

– CloudBurst

– BlueCloud


China Research Lab

© 2003 IBM CorporationIBM Confidential 38

Cloud Computing - Definition from IBMs BlueCloud Architecture Board

It is a user experience and a business model• Cloud computing is an emerging style of computing in which applications,

data, and IT resources are provided as services to users over the network.

It is a infrastructure management methodology• Cloud computing is way of managing large numbers of highly virtualized

resources such that from a management perspective, they resemble a single large resource. This can then be used to deliver services.

Service Consumers

Service Catalog,ComponentLibrary

CloudAdministrator

DatacenterInfrastructureMonitor & Manage

Services & Resources

Component Vendors /Software Publishers

Publish & UpdateComponents,Service Templates

AccessServices

IT Cloud

China Research Lab

© 2003 IBM CorporationIBM Confidential August 24, 2008

Architectural Model for Cloud Computing

End User Requests

& Operators

…

Service Request & Operations

Design & Build

Image Library (Store)

Deployment

OperationalLifecycle of Images

IT Infrastructure & ApplicationProvider

ServiceCreation & Deployment

Virtual Image Management

Service CatalogRequest UI

Operational UI

Optimized Middleware(image deployment, integrated security, workload mgmt., high-

availability)

Service Oriented Architecture Information Architecture

User Request Management/Self Service Portal

Security: Identity, Access, Integrity, Isolation, Audit & Compliance

Usage Accounting

License Managemen

t

Image Lifecycle

ManagementProvisioning

Performance

Management

Availability/Backup/ Restore

Service Lifecycle Management

Service Management

Virtual Resources & Aggregations

SMP Servers Network HardwareStorage ServersSystem Resources

Blades Storage


Server Virt. Storage Virt. Network Virt.

China Research Lab


Service Management Center for Cloud Computing

Admin

Service Management Center for Cloud Computing


System p LPARs VMWare

AIX

System z

Linux Linux z/OSWin

Provision a new server with OS and applications

Modify a provisioned server Start/stop a server, change memory and CPUs Add/remove node to cluster

AIXLinux on zLinux on x

End User

China Research Lab


Agenda

IBM cloud offerings

– CloudBurst

– BlueCloud


• Request driven provisioning• Service lifecycle manager• User experience

China Research Lab


Request Driven Provisioning (RDP2)

ProjectProject

Virtual ServerVirtual Server

SW StackSW Stack

1

n

1

1

End UserEnd User

P5/6 LPARs with AIX, RH LinuxIntel VMWare ESX with RH Linux or Windows

Request for Provisioning

China Research Lab


RDP Scenarios

Create virtual servers within a new project

Deploy new virtual servers in an existing project

Install a SW stack (OS and applications)

Destroy a virtual server

Increase/decrease CPU of a virtual server

Increase/decrease RAM of a virtual server

Cancel a project and destroy all associated virtual servers

China Research Lab


Create Virtual Servers in a new Project

End UserEnd User 1

The End User logs into TSAM

List of offerings:

Create new Project

Add server to existing project

SRM Catalog 2

Selects “Create a new Project”

ProjectNameDescriptionuserGroup

ServerType# of servers# CPUsMemory

4

Specifies Project details

List of SW stacks

5

Specifies Server Details

DSL

6

Select SW stack

7

Submit Request

China Research Lab


Add Server to an Existing Project

End UserEnd User 1


List of projects

SLM

List of offerings:

Create new Project

Add server to existing project

SRM Catalog

2

Selects “Add Server to an Existing

Project” ProjectNameDescriptionuserGroup

3

Selects an existing project

ServerType# of servers# CPUsMemory

4

Specifies Project details

List of SW stacks

5

Specifies Server Details

DSL

6

Select SW stack

7

Submit Request

China Research Lab


Modify a Server

End UserEnd User 1


List of projects

SLM

List of offerings: Modify a Server Delete a Server Cancel Project

SRM Catalog2

Selects “Modify a Server”

List of Servers in the project

3

Selects an existing project

Server# CPUsMemory

4

Selects a specific Server

5

Modify Server Details

7

Submit Request

China Research Lab


Agenda

IBM cloud offerings

– CloudBurst

– BlueCloud



China Research Lab


Sample Configuration SLM R1

Management Server on AIX or z/Linux

End User

Administrator

System p LPAR

AIX

IBM HTTP Server

System p LPAR

AIX

WAS DeploymentManager

WAS-based Application Service(structure + mgmt plans defined within template used for instantiation)

manages

• WAS Cluster

System p LPAR

AIX

WAS ClusterMember

System p LPAR

AIX

WAS ClusterMember

Monitored by ITM / OmegamonProvisioned &

Configured accordingto best practices

zOS

DB2

z/VM or zLPAR

Central TPAP (aka Maximo)-based GUI

“Launch in Context” to other Mgmt Software

China Research Lab


Some sample Topologies and Monitors

z/VM

Linux

IBM HTTP Server


WAS ClusterMember

DB2

z/VM

z/Linux

IBM HTTP Server


System p LPAR

AIX

WAS ClusterMember

System p LPAR

AIX

WAS ClusterMember

zOS

DB2

z/VM

Linux

IBM HTTP Server

z/VM

Linux


System p LPAR

AIX

WAS ClusterMember

System p LPAR

AIX

WAS ClusterMember

zOS

DB2

System z LPAR

z/VM

Linux

IBM HTTP Server

z/VM

Linux

WAS DeploymentManager (standby)

zOS

DB2

Parallel Sysplex

Development System

Test-system

Pre-Production

system

z/VM

China Research Lab


Application Landscape Manager

Assembles topology information, build and management plans, best practices templates, thresholds and policies to initiate deployment

Example: Deployment of an Application Landscape – System z

Work Order “IT Service Order”

1Lacking z skills (network, security, monitoring, etc.) , Tim is pleased to see a complete WebSphere landscape offered - exactly what he needs for an upcoming test of his newly developed SOA application. Tim doesn’t want to bother with the details of the underlying topology

Automation for service fulfillment, services inventory, tracking, work order, approvals

2

TPM provisions all landscape components including OS, DB, MW, etc. together with management agents and best practices templates, thresholds and policies

After Ann verified the validity of Tims request, she initiated the automated deployment of the landscape.

3

Tim receives notification that the landscape is ready for use

Service work order process

TPM

TPM workflow, best practice mgmt configurations, install images ( OS, middleware, mgmt agents)

Serice Definitions Inventory

Install Images, best practice configuration

Tim’s request together with all parameters describing service levels and other details about the desired WebSphere Landscape are routed to Ann for approval.

Service Management

Center for System z

Landscape Mgr Process

Ann,Service Landscape Deployment Planner

Tim, Application Test Team (End User)

4

DB2 on z/OS

OMEGAMON

WebSphere

z/VM

z/OS Linux on System z

OMEGAMON

Work order

Deployment automation

DB2 on z/OS

OMEGAMON

z/OS

China Research Lab


Service Definition and Provisioning

Same Service Definition Process can be used to

– Build and manage a (Development-)System that can be ordered and gets instantiated right-away (Request Driven Provisioning)

– Define a (Production-)System that is mapped to the infrastructure involving various subject matter experts ( security, HA, performance ….) and gets instantiated in the next maintenance window

The Service Instantiation time and quality is improved by

– Collecting all required parameters upfront

– Using a standardized and repeatable process

– Using Automation where possible / desired

China Research Lab


Managing the IT Landscape for a Service

Management can be done on a Service Instance

– that was build using the Service Definition / Request process

Typical Management Actions

– Start / Stop

– Resizing ( add/remove Cluster-Member )

– Incident Handling (next chart)

Adaptable Framework

– Customer can include existing management tools

– Customer can adopt to existing processes

China Research Lab


Operational Management ScenarioThreshold exceeded indicating a potential Response Time Problem

2

3a

CMDB

MBOs

1

John, Operations Specialist Analyze Incident Select Automation Packages or route Problem

ITM Agent:

Threshold exceeded

Close incident automatically or through user after manual action6

Ticket handling through service process (out of scope)

Composite Application - Distributed WAS on p, DB2 on z

TPAP

ISM Job Plan Execution

1. Identify and stop ran-away pid

2. Add Application Server

3. <customer best practice>

4. Adapt WAS Heap Size

Ann: DB SpecialistAnalyze Problem on DB

No, must be a

DB Problem

Yes, Management Plan

abc solves problem

Service Lifecycle Manager

Correlate with information about service, proposed

Mgmt. Plans, etc. 3b

4

Changes

Close ticket

5

Simplify typical operational management scenarios by providing

Best Management Practices for the specific

application landscape across the entire

spectrum including OMPs, thresholds,

policies, job plans, etc.

China Research Lab


Agenda

IBM cloud offerings

– CloudBurst

– BlueCloud



China Research Lab


Logon / Select Service Defintion

China Research Lab


Management Plans

China Research Lab


Monitoring and Event Management

Good Practices for determining the

cause of the Event and possible

corrective actions (if required)

Good Practices for corrective

management actions

China Research Lab


Resource / Topology Defintion

WebSphere Cell

WebSphere Cluster

IBM HTTP

Server

Deployment

Manager

Managed Node

AppServer

Instance

Managed Node

AppServer

Instance

......(1 .. 5)(1 .. 5)

DBMS Server

Database

Instance

China Research Lab


Resource Definitions – Connection to DB2

DBMS Server

Database

Instance

China Research Lab


Topology Node OperationsDeployment

Manager

China Research Lab


Service Instances

Existing InstancesExisting Instances

Self Service GUI

China Research Lab


WebSphere Cell

Instantiation Steps 1/3

WebSphere Cluster

IBM HTTP

Server

Deployment

Manager

Managed Node

AppServer

Instance

......(1 .. 5)(1 .. 5)

DBMS Server

Database

Instance

Topology CustomizationTopology Customization

CardinalityCardinality

Resource Allocation TemplateResource Allocation Template

22

Managed Node

AppServer

Instance

Managed Node

AppServer

Instance

zLinux zLinux

zLinux zLinux

ColocationColocation

Logical Server 1 Logical Server 2

Monitoring Configuration (optional)Monitoring Configuration (optional)

China Research Lab


LNXSOA04LNXSOA02

Instantiation Steps – Step 2/3IBM HTTP

Server

Deployment

Manager




Managed Node

AppServer

Instance

Managed Node

AppServer

Instance

zLinux zLinux

zLinux zLinux


Logical Server 1 Logical Server 2


CMDB

Resource AllocationResource Allocation

China Research Lab


LNXSOA04LNXSOA02

Instantiation Steps – Step 3/3IBM HTTP

Server

Deployment

Manager




Managed Node

AppServer

Instance

Managed Node

AppServer

Instance



Resource AllocationResource Allocation

Edit Job Plan (optional)Edit Job Plan (optional)

ApprovalApproval

DBMS Server

Database

Instance

(Scheduled) Provisioning(Scheduled) Provisioning

To TPMTo TPM

China Research Lab


Shortcuts for less complex / controlled Environments

Preapproved Instantiation

Fixed Cardinality of cluster members / target OS

Fixed server layout

Fixed monitoring setup

Non-editable TPAP job plans

China Research Lab


30 Min Break

IBM cloud offerings (1 hour and 20 min)

– CloudBurst (BlueCloud)


Break (30 min)

Cloud-based analysis platform research at CRL (1 hour)

Q & A (10 min)

China Research Lab


Agenda

Cloud-based analysis platform research at CRL

– Semantic web

– Healthcare applications

– Clod based analysis platform

China Research Lab


Today’s Web

Most of today’s Web content is suitable for human consumption

– Even Web content that is generated automatically from databases is usually presented without the original structural information found in databases

Typical Web uses today people’s

– seeking and making use of information, searching for and getting in touch with other people, reviewing catalogs of online stores and ordering products by filling out forms

China Research Lab


New Challenge

What We Say to Dogs

– from Gary Larson cartoon (local link) ...

• "Stay out of the garbage! Understand, Ginger? Stay out of the garbage!"

– What Dogs Understand

• "... blah blah blah blah GINGER blah blah blah blah ..."

What Computers Understand on Current Web

– " ... blah blah blah <a href=http://www.xwz.com/foo.html> link </a> blah blah blah . . . ."*

China Research Lab


Semantic Web

The Semantic Web provides a common framework that allows data to be shared and reused across application, enterprise, and community boundaries.

“Facilities to put machine-understandable data on the Web are becoming a high priority for many communities. The Web can reach its full potential only if it becomes a place where data can be shared and processed by automated tools as well as by people. For the Web to scale, tomorrow's programs must be able to share and process data even when these programs have been designed totally independently.”

W3C Semantic Web Activity

China Research Lab


What Does RDF Data Look Like

University:Person1

University:hasName

“Jack”^xsd:String

University:Person2

University:hasName

“Rose”^xsd:String

University:hasGender

Male^xsd:BooleanUniversity:hasGender

Female^xsd:Boolean

University:CourseA

University:teachOf University:takeCourse

University:hasCourseName

“Maths”^xsd:String

University:Professor

University:GraduateStudent

University:Person

University:Course

RDF:typeOf

RDF:typeOfRDF:typeOf

University:teachOf

University:takeCourse

University:hasName

University:hasName

xsd:String

xsd:Boolean

rdfs:subClassOf

rdfs:subClassOf

University:hasCourseName

Subject Predicate Object

University:Person1 University:hasName “Jack”^xsd:String

University:Person1 University:hasGender Male^xsd:Boolean

University:Person2 University:hasName “Rose”^xsd:String

University:Person2 University:hasGender Female^xsd:Boolean

University:Person1 University:teachOf University:CourseA

University:Person2 University:takeCourse University:CourseA

University:CourseA University:hasCourseName “Maths”^xsd:String

University:Person1 RDF:typeOf University:Professor

University:Person2 RDF:typeOf University:GraduateStudent

University:CourseA RDF:typeOf University:Course

University:Professor rdfs:subClassOf University:Person

University:GraduateStudent rdfs:subClassOf University:Person

University:Professor University:teachOf University:Course

University:GraduateStudent University:takeCourse University:Course

……

courseDPhTake ..

rdfs:subClassOf

China Research Lab


LOD (Linking Open Data), DBpedia, IMDb, Freebase…… LOD: over 30 datasets which consisted of 2

billion triples till Apr 2008

DBpedia: over 100 million triples till Sep 2008– Entities (over 2 million), e.g.,

• 80,000 persons• 70,000 places• 35,000 music albums• 12,000 films

– Relationships, e.g.,• 657,000 links to images• 1,600,000 links to relevant external web pages• 180,000 external links into other RDF datasets

– Classifiers, e.g.,• 207,000 Wikipedia categories • 75,000 YAGO categories

Freebase:– Over 4 million resources.

IMDb (LinkMDM): over 30K overlapping movies, soundtracks

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RDFS RDF Schema is a Vocabulary

Description Language

– it allows specification of domain vocabulary and a way to structure it

– Class, Property, subClassOf, subPropertyOf, domain, range

Formal semantics add simple reasoning capabilities:

– class and property subsumption

– domain and range inference

person001

Researcher

Person

name

rdf:Property

rdfs:Class

rdf:type

rdf:type

rdf:type

rdfs:domainrdfs:subClassOf

China Research Lab


OWL<?xml version="1.0" encoding="UTF-8" ?>

<rdf:RDF

xml:base = "http://www.ibm.com/crl#"

xmlns:rdf = "http://www.w3.org/1999/02/22-rdf-syntax-ns#"

xmlns:rdfs="http://www.w3.org/2000/01/rdf-schema#"

xmlns:owl="http://www.w3.org/2002/07/owl#">

<owl:Ontology rdf:about="">

<rdfs:comment>An example to show differences between owl-lite, DLP and owl-DL</rdfs:comment>

</owl:Ontology>

<owl:Class rdf:about=#Faculty>

<owl:unionOf rdf:parseType="Collection">

<owl:Class rdf:about="#Professor" />

<owl:Class rdf:about="#Post-Doc" />

<owl:Class rdf:about="#Lecturet" />

</owl:unionOf>

</owl:Class>

<owl:Class rdf:ID=“Ph.D Student">

<rdfs:subClassOf>

<owl:intersectionOf rdf:parseType="Collection">

<owl:Class rdf:about="#Person" />

<owl:Restriction>

<owl:onProperty rdf:resource="#take" />

<owl:someValuesFrom>

<owl:Class rdf:about="#Ph.D course" />

</owl:someValuesFrom> </owl:Restriction>

</owl:intersectionOf>

</rdfs:subClassOf>

</owl:Class> courseDPhTake ..

Faculty

LectureProfessor

OWL:UnionOf

Ph.D Student

Blank node

Person

rdfs:subClass

OWL:intersectionOf

Post-Doc

China Research Lab


Agenda


– Semantic web



China Research Lab


Scenario: Adverse Effect Discovery for DrugsThe Pharmacovigilance Process (FDA)

Detect SignalsTraditional Methods

DataMining

Generate Hypotheses

Refute/Verify

Type A (Mechanism-based)

Type B(Idiosyncratic)

Insight from Outliers

EstimateIncidence

Public HealthImpact, Benefit/Risk

Act

Inform

Change LabelRestrict use/

withdraw

China Research Lab


Scenario: Adverse Effect Discovery for DrugsAERS Schema Pieces (FDA)

Reporter country

Receipt date

Qualification

– Physician

– Pharmacist

– Health professional

– Lawyer

– Consumer

Patient set age

Patient weight

Patient gender

Patient death date

Seriousness

– death

– lifethreatening

– hospitalization

– disabling

– congenitalanomaly

– Other

Medicinal product

Drug batch numb

Reaction medDRA PT

China Research Lab


Scenario: Adverse Effect Discovery for DrugsStatistical Methodology

Most use variations of 2-way table statistics

No. Reports Target AE Other AE

Total

Target Drug a b nTD

Other Drug c d nOD

Total nTA nOA n

Some possibilities Reporting Ratio: E(a) = nTD nTA/nProportional Reporting Ratio: E(a) = nTD c/nODOdds Ratio: E(a) = b c/d

Basic idea:

Flag when R = a/E(a) is “large”

China Research Lab


Scenario: Adverse Effect Discovery for DrugsAERS Data Statistics (FDA)

Spontaneous Reporting System began in late 1960’s, and had received over 2.7 million reports till June, 2004.

For now, 300,000 reports per year were added continuously (approximately 1,000 reports per day) .

> 9,000 event codes (MedDRA Preferred Terms)

> 7,000 drug/biological products by trade names

> 3,000 by generic names (generic names + combination products), from health professionals, suspect products only

> 63,000,000 drug-event combinations possible!

For all possible quadruples (e.g., drug-drug-drug-event or drug-drug-event-event) 20,000,000,000,000,000 combinations are possible!

China Research Lab


Agenda


– Semantic web



China Research Lab


Application

Repository

HTTP Server

Distributed File System (HDFS)

IDB

I1 I2

P2

g2g1

gk

P1

g2g1

gk

Pn

g2g1

gk…

Master

HBase

Map/Reduce Running System (Hadoop)

RDF2X

PMML+ ParsingData Requirement Parsing

Mining

In-memory Data Model In-memory Analysis Model

SeDA

SPARQL Queries

Queries Results DataImport

Importing & Mining

QueryGen

RDF2File

RDF2Flattentable

Architecture

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Example Data

ISR Drug Seq Reaction PT Outcome Cod

Age Gender Wt. Occu.

5701501 1009771744 PNEUMONIA DE 83 M MD

HO

5710206 1009806917 ABDOMINAL DISCOMFORT HO 49 M 103KG CN

ABDOMINAL PAIN UPPER

DIZZINESS

HYPOTENSION

NAUSEA

VOMITING

5908666 1010540206 DEAFNESS DS 68 F 142LBS MD

SYNCOPE

HO

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Lifecycle of a Cloud Service

Def

initi

onO

ffer

ing

Subscription &

InstantiationProduction

Term

inatio

n

IBM / ISV /IT Dept

Subscriber (e.g. Line of Business)

Administrator / SLM

Service Template Definition

•Create Build- and Management Plans for Service

Service Offering Creation & Registration

•Define Service based on Template and register it in the Catalog

Service Catalog Manager

Service Offering Subscription & Instantiation

•Select Service, specify parameters and SLA’s•Automatically instantiate the Service

Subscriber (e.g. Line of Business)

Service Instance Termination

Destroy Service and free up resources

CloudServiceCloud

Service

Ensemble Hardware Ensemble Hardware

System z Ensemble Power Ensemble System x Ensemble

Ensemble Hardware

Virtualizers (e.g. z/VM) Virtualizers (e.g. PHYP) Virtualizers (e.g. Xen)

Individual Servers Storage Ensembles

Ap

p

Ap

p

Man

agem

ent

LP

AR

/ V

M

…

Ap

p

Ap

p

Ap

p

Ap

p

Man

agem

ent

LP

AR

/ V

M

…

Ap

p

Ap

p

Ap

p

Ap

p

Man

agem

ent

LP

AR

/ V

M…

Ap

p

Ap

p

OS OS OS OS OS OS

Manual or Autonomic Execution of Management Plans leveraging Automation and Virtualization

Ensure SLA Conformance

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Q & A

China Research Lab


Documents

China Research Lab © 2006 IBM Corporation IBM Confidential Introduction to IBM Cloud Products and Cloud- based Analysis Platform Research at CRL Chen Wang