CLOUD COMPUTING

CLOUD CLOUD COMPUTINGCOMPUTING

1. Nguyễn Anh Tài

2. Nguyễn Phương Duy

3. Phạm Thanh Phương

CONTENTSCONTENTS

Introduction to Cloud Computing

Cloud Implementations

Market-Oriented Clouds

Comparing Grids and Clouds2

INTRODUCTION (1)INTRODUCTION (1)

Issues before cloud

Cost (hardware, software, maintain, …)

recession

Scalable

Technology

……

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““Cloud computing is hinting at a Cloud computing is hinting at a futurefuture in which we won’t in which we won’t

compute on compute on local computerslocal computers, , but on centralized facilities but on centralized facilities

operated by operated by third party third party compute and storage utilitiescompute and storage utilities.”.”

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DEFINITIONSDEFINITIONS

“Cloud computing is a style of computing in which dynamically

scalable and often virtualized resources are provided as a

service over the Internet” – Wikipedia.

“A style of Computing where scalable and elastic IT

capabilities are provided as a service to multiple customers

using Internet technologies” – Gartner.

“A large scale distributed computing paradigm that is driven by

economics of scale, in which a pool of abstracted, virtualized,

dynamically – scalable, managed computing power, storage,

platforms, and services are delivered on demand to external

customers over the Internet” – Ian Foster. 5

Users need not have knowledge of, expertise in, or control over the technology infrastructure "in the cloud" that supports them.

Cloud computing services usually provide common business applications online that are accessed from a web browser, while the software and data are stored on the servers.


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Cloud computing is often confused with

grid computing

utility computing

autonomic computing

many cloud computing deployments as of 2009 depend on

grids, have autonomic characteristics and bill like utilities

cloud computing can be seen as a natural next step from the

grid-utility model

≠ P2P networks (BitTorrent), volunteer computing (SETI@home)


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8

Trends


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Overview


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Economics

INTRODUCTION (9)INTRODUCTION (9)ISSUESISSUES

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Cloud computing shines in the recession, vnunet.com, 04/28/2009 The most popular applications are data storage (27.7%

of respondents), financial applications (17%) and email (12.8%)

Issues Intellectual property Privacy Security Not control Latency Enclosure services Ready Laws


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Companies IBM (Blue Cloud) Amazon (EC2) Google (G. Apps) Microsoft (M. Azure) Yahoo Salesforce ……

CLOUD COMPUTING CLOUD COMPUTING IMPLEMENTATIONS IMPLEMENTATIONS CATEGORIESCATEGORIES

3 categories of cloud computing services: Infrastructure-as-a-Service (IaaS): raw infrastructure and

associated middleware Amazon EC2/S3, Elastra (Beta 2.0 2/2009), Nirvanix, AppNexus

Platform-as-a-Service (PaaS): APIs for developing

applications on an abstract platform Mosso (2/2008), Google App Engine, Salesforce, Heroku, Engine

Yard

Software-as-a-Service (SaaS): support for running

software services remotely 3Tera (2/2006), Salesforce

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CLOUD COMPUTING CLOUD COMPUTING IMPLEMENTATIONSIMPLEMENTATIONSPRICING MODELPRICING MODEL

Pricing model:

Tired pricing: each tier offer fix computing

specification (i.e. memory allocation, CPU type and

speed, etc.)

Per-unit pricing: is normally applied to data transfers

or memory usage, memory allocation is more

flexible than tire pricing

Subscription base pricing: most-widely use for SaaS

– user predict periodic expenses of using cloud

application (lack of accuracy)

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CLOUD COMPUTING CLOUD COMPUTING IMPLEMENTATIONSIMPLEMENTATIONSAMAZONE ELASTIC COMPUTE AMAZONE ELASTIC COMPUTE CLOUD (EC2)CLOUD (EC2)

Infrastructure-as-a-Service

Compute, Storage

Instance: Xen Virtual

machine

5 instance types: CPU, RAM,

Arch, I/O performance, Disk

Cost (each instance - $/h)

User requires instances

(instance type & VM Image)

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CLOUD COMPUTING CLOUD COMPUTING IMPLEMENTATIONS IMPLEMENTATIONS GOGRIDGOGRID


"world's first multi-server control

panel” provide server image with

preinstalled software

Load balancer (virtual IP), Web-based

control panel, API, and .NET SDK

1 Server RAM-hour = 1GB of RAM

deployed for 1 Hour16

CLOUD COMPUTING CLOUD COMPUTING IMPLEMENTATIONSIMPLEMENTATIONSMICROSOFT LIVE MESHMICROSOFT LIVE MESH


Compute

OS Level

Provide a centralized location for a user to store

applications and data that can be accessed

across required devices (such as computers and

mobile phones)

User access interface: Web-based Live Desktop

and any Live Mesh installed devices17

CLOUD COMPUTING CLOUD COMPUTING IMPLEMENTATIONSIMPLEMENTATIONSSUN GRID (NETWORK.COM)SUN GRID (NETWORK.COM)


Compute

Job management system

Sun Grid Engine

User access interface: Job submission

scripts, Sun Grid Web portal

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CLOUD COMPUTING CLOUD COMPUTING IMPLEMENTATIONS IMPLEMENTATIONS GOOGLE GOOGLE APP ENGINEAPP ENGINE

Platform-as-a-Service

Platform

Lets user run web app on Google’s infrastructure

These apps run in a sandbox:

No local files, App Engine datastore request within a limited

period

AppLogic: appliances run inside VM, configured by user

Hadoop (implementation of MapReduce) vast amount of data19

CLOUD COMPUTING CLOUD COMPUTING IMPLEMENTATIONS IMPLEMENTATIONS GOOGLE GOOGLE APP ENGINEAPP ENGINE

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CLOUD COMPUTING CLOUD COMPUTING IMPLEMENTATIONS IMPLEMENTATIONS GOOGLE GOOGLE APPSAPPS

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CLOUD COMPUTING CLOUD COMPUTING IMPLEMENTATIONSIMPLEMENTATIONSSALESFORCESALESFORCE

AppExchange

On-demand

application sharing

service

Applications that run

entirely within a web

browse

Force.com

On-demand platform

Provide Web Service API: Force.com Web Services

API Salesforce Object Query

Language (SOQL) Salesforce Object Search

Language (SOSL) Etc.

Software-as-a-Service Platform-as-a-Service

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CLOUD COMPUTING CLOUD COMPUTING IMPLEMENTATIONSIMPLEMENTATIONSSALESFORCESALESFORCE

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CLOUD COMPUTING CLOUD COMPUTING IMPLEMENTATIONSIMPLEMENTATIONS3TERA3TERA

Software-as-a-Service

Launch AppLogic (grid OS)

package an entire N-tier application or service into a

logical entity and manage it as a single system

Application run on a grid of commodity servers

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CLOUD COMPUTING CLOUD COMPUTING IMPLEMENTATIONSIMPLEMENTATIONSRIGHTSCALERIGHTSCALE MultipleMultiple Clouds Work (9/2007) Managing clouds:

Amazon’s Web Service GoGrid FlexiScale Mosso

4/2009 extend to Private and Hybrid Cloud 3 types of Cloud

Public cloud (external cloud): traditional mainstream sense

Private cloud Hybrid cloud: consisting of multiple internal and/or

external providers25

CLOUD COMPUTINGCLOUD COMPUTINGMARKET ORIENTED (1)MARKET ORIENTED (1)

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CLOUD COMPUTINGCLOUD COMPUTINGMARKET ORIENTED (2)MARKET ORIENTED (2)

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User/Broker

SLA Resource

Allocator

Interface

External Users/Brokers

Cloud service Provider

Virtual Machines (VM)

Physical Machines

CLOUD COMPUTINGCLOUD COMPUTINGMARKET ORIENTED (3) MARKET ORIENTED (3) - - SLA SLA RESOURCE ALLOCATORRESOURCE ALLOCATOR

Service Request Examiner and Admission Control ensure nooverloading

Pricing decide charge fee (time, rate, availbility)

Accounting maitain usage of resource

VM Monitor keep VMtrack Dispatcher execute

progress of service on VM Service Request Monitor

keep track of executing service 28

CLOUD COMPUTINGCLOUD COMPUTING MARKET MARKET ORIENTED (4)ORIENTED (4)RESOURCE MANAGEMENT RESOURCE MANAGEMENT STRATEGIESSTRATEGIES

Customer: keep inform and obtain feedback

Management risk: establish context of risk

and identify the risks involved

User requirement change overtime: Dynamically change service demand User can broke system acting to select suitable

provider and negotiation

Virtualization: configure VM as different

partitions of resources 29

CLOUD COMPUTINGCLOUD COMPUTINGGLOBAL CLOUD EXCHANGE AND GLOBAL CLOUD EXCHANGE AND MARKETSMARKETS

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GRIDS AND CLOUDS GRIDS AND CLOUDS OVERVIEWOVERVIEW Is “Cloud Computing” just a new name for Grid ?

Yes: They are the same – to reduce the cost of

computing, increase reliability, flexibility by transforming

computers from something that we buy and operate

ourselves to something that is operated by third party.

No: Things are different now than they were 10 years

ago.

So we are operating at a different scale, and operating at

these new, more massive scales can demand fundamentally

different approaches to tackling problems.31

GRIDS AND CLOUDS OVERVIEWGRIDS AND CLOUDS OVERVIEW

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The definition of

Cloud Computing overlaps with many

existing technologies,

such as Grid

Computing, Utility

Computing, Services

Computing, and

Distributed Computing

in general.

COMPARING GRIDS AND CLOUDSCOMPARING GRIDS AND CLOUDS

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Business Model1

Architecture2

Resource Management3

Programming Model4

Security Model6

Application Model5

BUSINESS MODELBUSINESS MODEL

The business model for Clouds:User will pay the provider on a consumption

basis, such as electricity, gas, and water.The prospect of needing only a credit card to get

on demand access to 100000+ processors in tens of data centers distributed throughout the world.

The business model for Grids: It is project-oriented in which users or community

represented by that proposal have certain number of services units (i.e. CPU hours) they can spend.

A Grid economy for a global Grid ? 34

ARCHITECTUREARCHITECTURE

Grids started off in the mid-90s to address large scale computation problems using a network of resource sharing commodity machines Focus on integrating existing resources.

Clouds are developed to address Internet scale computing problems (homogeneous). Usually referred to as a large pool of computing

and/or storage resource.

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Architecture

Cloud protocol ArchitectureGrid protocol Architecture

Application

Collective

Resource

Connectivity

Fabric Fabric

Unified Resource

Application

Platform

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RESOURCE MANAGEMENTRESOURCE MANAGEMENT

1. Compute Model

2. Data Model

3. Data Locality

4. Combining compute and data

management

5. Virtualization

6. Monitoring

7. Provenance37


1.1. Compute ModelCompute Model

Most Grids use a batch-scheduled compute

model. A grid site use a local resource manager

such as PBS, Condor, SGE.

Resources in Cloud Computing are shared by all

users at the same time (in contrast to dedicated

resources governed by a queuing system).

one of the major challenges for Cloud Computing38


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DataData

Cloud ComputingCloud Computing Client ComputingClient Computing

2.2. Data ModelData Model Cloud Computing

Storage, computing and all

kind of other resources will

mainly be provisioned by

the Cloud !!!

Grid Computing

Data Grids have been

designed to tackle data

intensive applications in

Grid environment.


3.3. Data LocalityData Locality

In Grids:

Data storage usually relies on a shared file systems

(NFS, GPFS, PVFS…) where data locality cannot be

easily applied.

In Clouds:

One approach is to improve schedulers to be data-

aware, and to be able to leverage data locality

information when scheduling computational tasks.40


4.4. Combine compute and data Combine compute and data

managementmanagement

Data-aware schedulers and dispersing data

close to processors is critical in achieving good

scalability and performance.

Grids have been making progress in combining compute

and data management with data-aware scheduler.

Clouds will face significant challenges in handling data-

intensive applications.41


5.5. VirtualizationVirtualization Clouds need to run multiple applications, and all

the applications appear to the users as if they

were running simultaneously and could use all

the available resources in the Cloud.

Grids do not rely on virtualization as much as

Clouds do, but that might be more due to policy

and having each individual organization maintain

full control of their resources. (i.e. by not

virtualizing them).

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6.6. MonitoringMonitoring Grids in general have a different trust model in which users

via their identity delegation can access and browse

resources at different Grid sites and Grid resources are

not highly abstracted and virtualized as in Clouds.

Example: Ganglia-distributed monitoring system.

Virtualization brings to Clouds the potential difficulty in fine-

control over the monitoring of resources.

A significant challenge for Clouds, but it will become less important as

Clouds become more sophisticated and more less self-maintained and

self-healing.

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7.7. ProvenanceProvenance Provenance refers to the derivation history of

a data product, including all the data sources,

intermediate data products, and the procedures

that were applied to produce the data product.

Ex: Scientists can debug workflow execution,

validate or invalidate scientific results. In Grids, provenance management has been in general built

into a workflow system.

Provenance is still an unexplored area in Cloud

environments.44

PROGRAMMING MODELPROGRAMMING MODEL

Clouds have generally adopted Web Services

APIs where users access, configure and

program Cloud services using pre-defined APIs.

Although Clouds adopted some common

communication protocols such as HTTP and

SOAP, the integration and interoperability

of all the services and applications remain the

biggest challenges.

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APPLICATION MODELAPPLICATION MODEL

Grids generally support many different kinds

of applications: from high performance

computing (HPC) to high throughput

computing (HTC).

Loosely coupled and tightly coupled applications

Cloud computing can support a similar set of

applications.

The one exception that will be hard to achieve in Cloud

Computing are HPC applications that require fast and

low latency network interconnects for efficient scaling

to many processors

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APPLICATION MODELAPPLICATION MODEL

“ A Science Gateway is a community-

developed set of tools, applications and

data collections that are integrated via

a portal or a suite of applications. ”

Grid gateways interact with services and provide

rich user interactivity.

Cloud gateways have almost no interaction

between end-user.

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SECURITY MODELSECURITY MODEL

Clouds mostly comprise dedicated data

centers belonging to the same organization.

Clouds environments is more homogeneous than Grids is.

The security model for Clouds seems to be

relatively simpler and less secure than the

security model adopted by Grids.

Security is one of the largest concerns for the

adoption of Cloud Computing.

Seven risks a Cloud user should raise with vendors before

committing ?48


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Security

Long-term viability

Privileged user access

Regulatory compliance

Data Location

Data segregation

Recovery

Investigative support


1.Privileged user access: sensitive data

processed outside the enterprise needs the assurance

that they are only accessible and propagated to

privileged users.

2.Regulatory compliance: a customer needs to

verify if a Cloud provider has external audits and

security certifications and if their infrastructure

complies with some regulatory security requirements.

3.Data location: It is important that a Cloud

provider commit to storing and processing data in

specific jurisdictions and to obey local privacy

requirements on behalf of the customer.50


4.Data segregation: one needs to ensure that one customer’s data is fully segregated from another customer’s data.

5.Recovery: It is important that a Cloud provider has an efficient replication and recovery mechanism to restore data if a disaster occurs.

6.Investigative support: Cloud services are especially difficult to investigate, if this is important for a customer, then such support needs to be ensured with a contractual commitment.

7.Long-term viability: your data should be viable even the Cloud provider is acquired by another company. 51

REFERENCEREFERENCE R. Buyya et al., 2008, Market-Oriented Cloud Computing: Vision,

Hype, and Reality for Delivering IT Services as Computing Utilities, in Proceedings of the 2008 10th IEEE International Conference on High Performance Computing and Communications, HPCC '08, Page(s):5 – 13

Simon Ostermann, Alexandru Iosup, Nezih Yigitbasi, Radu Prodan, Thomas Fahringer, and Dick Epema, An Early Performance Analysis of Cloud Computing Services for Scientific Computing

Ian Foster, Yong Zhao, Ioan Raicu, Shiyong Lu, Cloud Computing and Grid Computing 360-Degree Compared

Mladen A. Vouk, Cloud Computing – Issues, Research and Implementations

www.ibm.com/developerworks/websphere/zones/hipods/ Internet (Product related homepage and review)

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Q & AQ & A

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Thank youThank you

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CLOUD COMPUTING