An Introduction to Cloud Computing

Robert Grossman

December 8, 2009

Part 1

Introduction

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What is a Cloud? Clouds provide elastic, on-demand resources

or services over a network, often the Internet, with the scale and reliability of a data center.

The NIST definition has become standard. Cloud architectures are not new. What is new:

– Scale– Ease of use– Pricing model.

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Scale is new.

Elastic, Usage Based Pricing Is New

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1 computer in a rack for 120 hours

120 computers in three racks for 1 hour

costs the same as

Elastic, usage based pricing turns capex into opex. Clouds can manage surges in computing needs.

Simplicity Offered By the Cloud is New

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+ .. and you have a computer ready to work.

A new programmer can develop a program to process a container full of data with less than day of training using MapReduce.

Two Types of Clouds

On-demand resources & services over a network at the scale of a data center

On-demand, elastic computing instances (IaaS)– IaaS: Amazon EC2, S3, etc.; Eucalyptus– supports many Web 2.0 applications/users

Large data clouds (Large Data PaaS)– GFS/MapReduce/Bigtable, Hadoop, Sector, …– Manage and compute with large data (say 100+ TB)

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Ease of use – With Google’s GFS & MapReduce, it is simple to compute with 10 terabytes of data over 100 nodes. With Amazon’s AMIs, it is

simple to respond to a surge of 100 additional web servers.

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Cloud Architectures – How Do You Fill a Data Center?

Cloud Storage Services

Cloud Compute Services (MapReduce & Generalizations)

Cloud Data Services (BigTable, etc.)

Quasi-relational Data Services

App App App App App

App App

App App

on-demand computing capacity

App App App…

on-demand computing instances

Varieties of Clouds Architectural Model

– Computing Instances vs Computing Capacity

Economic Model– Elastic, usage based pricing,

lease/own, … Management Model

– Private vs Public; Single vs Multiple Tenant; …

Programming Model– Queue Service, MPI,

MapReduce, Distributed UDF10

Computing instances vs computing capacity

Private internal vspublic external

Elastic, usage-based pricing or not

All combinations occur.

Payment Models

Buying racks, containers and data centers Leasing racks containers and data centers Utility based computing (pay as you go)

– Moves cap ex to op ex– Handle surge requirements (use 1000 servers for 1

hour vs 1 server for 1000 hours)

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Management Models

Public, private and hybrid models Single tenant vs multiple tenant (shared vs

non-shared hardware) Owned vs leased Manage yourself vs outsource management All combinations are possible

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Programming Model

Amazon’s Simple Queue Service

MPI, sockets, FIFO

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MapReduce Distributed UDF

on-demandcomputing instances

on-demand computing capacity

DryadLINQ Azure services

Storage Services

Compute Services

Applications

Virtual Network Manager

Data Services

Network Transport

Virtual Machine Manager

Metadata Services

Identity Manager

IaaS

PaaS

Apps

Instances, Services & Frameworks

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instance(IaaS)

service framework(PaaS)

operating system

Hadoop DFS & MapReduce

Amazon’s EC2

Amazon’s SQSAzure Services

single instance

Google AppEngineMicrosoft AzureForce.com

VMWareVmotion…

many instances

S3

Part 2. Cloud Computing Industry

“Cloud computing has become the center of investment and innovation.”Nicholas Carr, 2009 IDC Directions

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Cloud computing is approaching the top of the Gartner hype cycle.

Cloud Computing Eco-System No agreed upon terminology Vendors supporting data centers Vendors providing cloud apps & services to

end users Vendors supporting the industry i.e. those

developing cloud applications and services for themselves or to sell to end users

Communities developing software, standards, benchmarks, etc.

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Cloud Computing Ecosystem

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Providers of Cloud Services

Consumers of Cloud Services

Providers of Software as a Service

Consumers of Software as a Service

Berkeley RAD Report on cloud computing divides industry into these layers.

Data Centers

Transition Taking Place A hand full of players are building multiple data

centers a year and improving with each one. This includes Google, Microsoft, Yahoo, … A data center today costs $200 M – $400+ M Berkeley RAD Report points out analogy with

semiconductor industry as companies stopped building their own Fabs and starting leasing Fabs from others as Fabs approached $1B

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Data Center Operating Systems

Data center services include: VM management services, business continuity services, security services, power management services, etc.

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workstation

VM 1 VM 5

…VM 1 VM 50,000

…

Data Center Operating System

Building Data Centers

Sun’s Modular Data Center (MD)

Formerly Project Blackbox

Containers used by Google, Microsoft & others

Data center consists of 10-60+ containers.

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Mindmeister Map of Cloud Computing

Dupont’s Mindmeister Map divides the industry:– IaaS, PaaS, Management, Community

http://www.mindmeister.com/maps/show_public/15936058

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Part 3

Virtualization

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Virtualization Virtualization separates logical infrastructure

from the underlying physical resources to decrease time to make changes, improve flexibility, improve utilization and reduce costs

Example - server virtualization. Use one physical server to support multiple logical virtual machines (VMs), which are sometimes called logical partitions (LPARs)

Technology pioneered by IBM in 1960s to better utilize mainframes

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Idea Dates Back to the 1960s

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IBM Mainframe

IBM VM/370

CMS

App

Native (Full) VirtualizationExamples: Vmware ESX

MVS

App

CMS

App

Two Types of Virtualization

Using the hypervisor, each guest OS sees its own independent copy of the CPU, memory, IO, etc.

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Physical Hardware

Hyperviser

Unmodified Guest OS 1

Unmodified Guest OS 2

Native (Full) VirtualizationExamples: Vmware ESX

Apps

Physical Hardware

Hyperviser

Modified Guest OS 1

Modified Guest OS 2

Para VirtualizationExamples: Xen

Apps

Four Key Properties

1. Partitioning: run multiple VMs on one physical server; one VM doesn’t know about the others

2. Isolation: security isolation is at the hardware level.

3. Encapsulation: entire state of the machine can be copied to files and moved around

4. Hardware abstraction: provision and migrate VM to another server

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Managing Virtual Machines

Provision VM Schedule VM Monitor VM Self-service portal for VM

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Part 4

Technical differences between clouds for data intensive computing, databases and supercomputers

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Supercomputer Center Model

or

Data Center Model

What Resource is Managed? Scarce processors wait for data

– Manage cycles– wait for an opening in the queue– scatter the data to the processors– and gather the results

Persistent data wait for queries– Manage data– persistent data waits for queries– computation done locally– results returned

Supercomputer Center Model (local)

HPC Grid(distributed)

Data Center 2.0 Model

Distributed 2.0Data Centers

Trading functionality for scalability.

DatabasesvsData Clouds

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Trading Functionality for ScalabilityDatabases Large Data Clouds

Scalability 100’s TB 100’s PBFunctionality

Full SQL-based queries, including joins

Optimized access to sorted tables (tables with single keys)

Optimized Databases are optimized for safe writes

Clouds optimized for efficient scans reads

Consistency model

ACID (Atomicity, Consistency, Isolation & Durability) – database always consist

Eventual consistency – updates eventually propagate through system

Parallelism Difficult because of ACID model; shared nothing is possible (Graywolf)

Basic design incorporates parallelism over commodity components

Scale Racks Data center

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Not Everyone Agrees

David J. DeWitt and Michael Stonebraker, MapReduce: A Major Step Backwards, Database Column, Jane 17, 2008

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Part 5. Standards Efforts

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Change of gauge at Ussuriisk (near Vladivostok) at the Chinese –Russian border

Train gauge in China is 1435 mm

Train gauge in Russia is 1520 mm

How can a cloud application move from one cloud storage service to another?

Standards Efforts for Clouds

Distributed Management Task Force (DMTF) Storage Network Industrial Association (SNIA) Cloud Computing Interoperability Forum (CCIF) Open Cloud Consortium (OCC) Open Grid Forum (OGF) Plus several others…

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