lecture course service-oriented computing 11: cloud...

Fuyuki Ishikawa （石川冬樹）[email protected]

Lecture CourseService-Oriented Computing

11: Cloud Computing (1): Overview2012/06/22

1 Introduction

2 Basics: Distributed Objects

3 Basics: XML

4 Web Services: Foundations

5 Web Services: Composition

6 Web Services: Implementation

7 Related Topics (1): Reliability

SOC'12 @ Sokendai 2Fuyuki Ishikawa

Course Plan

8 Related Topics (2): Security

9 Related Topics (3): Engineering

10 Related Topics (4): Semantic Web

11 Cloud Computing (1): Overview

12 Cloud Computing (2): Experience

13 Discussion and Summary

14 Students’ Presentation


Course Plan

Overview of Cloud ComputingOverview & ImpactsExample of IaaS: Amazon EC2Example of PaaS: Google App EngineTechnical Notes

TOC

4Fuyuki IshikawaSOC'12 @ Sokendai

Eric Schmidt (Google CEO, 2006)“… It starts with the premise that the data services and architecture should be on servers. We call it cloud computing ‒ they should be in a "cloud" somewhere. ““… There are a number of companies that have benefited from that. ““… This is the same talk that I gave in this room 10 years ago about something they called the network computer ‒ which, I can assure you, none of you are using, because it didn't work.”


Cloud Computing: Overview

Internet-based computing, using computational resources, data, functionality, etc. on serversParadigm shift of “from own to use”Computation as public utility Somewhat common features:Scale for large amount of data/processing, often automaticallyPay per useMuch cheaper to use than to own by yourselfcf. http://csrc.nist.gov/groups/SNS/cloud-computing/index.html


Cloud Computing: Overview

The NIST Definition of Cloud ComputingDefinition: Cloud computing is a model for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction. This cloud model promotes availability and is composed of five essential characteristics, three service models, and four deployment models.


Cloud Computing: Definition

Cont’dEssential characteristicsOn-demand self-serviceBroad network accessResource poolingRapid elasticityMeasured Service

Service modelsSaaS, PaaS, IaaS

Deployment modelsPrivate, Community, Public, Hybrid


Cloud Computing: Definition

SaaS (Software-as-a-Service)Package softwareGmail, Salesforce CRM, Microsoft Online Services, etc.

PaaS (Platform-as-a-Service)Platform often including automated management middleware for specific programming languagesForce.com, Google App Engine, Windows Azure, etc.

IaaS (Infrastructure-as-a-Service)Infrastructure including virtual machines and storages for free use casesAmazon EC2, Nifty Cloud, etc.


Cloud Computing: Representatives

Difficult (and not essential) to distinguish IaaSand PaaSNot binary: what the provider prepares and what the user preparese.g., Azure is said to be at the middle level

Sometimes considered together as “providing resources” (while SaaS can be considered “using resources to provide application-level services”)e.g., [Report by M. Armbrust et. al. (UC Berkeley)]


Notes: IaaS and PaaS

[Report by M. Armbrust et. al. (UC Berkeley)]


Notes: IaaS and PaaS

Animoto: made its movie creation/browsing service open to Facebook users (2008)Amazon EC2: 4,000 servers (originally 50) to handle 250 thousands users (originally 25 thousands) after 3 days

White House: prepared a questionnaire web site (2009)Google App Engine: 100 thousands questions and 3.6 million answers in 2 days (max 600 query/second)

Twitter, Nasdaq, …Scaling


Cloud Computing: Application (1)

New York Times: converted newspaper images of 100 years (several TBs) into PDF (2007)Amazon EC2: 100 virtual machines for 24 hours (about $1,250)

Japanese ministry/city: prepared systems for emergent and temporal requirements (e.g., 定額給付金) (2009)Force.com

Quick start up and withdraw


Cloud Computing: Application (2)

More amount, less cost

[Report by M. Armbrust et. al. (UC Berkeley)]Amazon has more traffic for EC2/S3 than for its book commerce (since 2008)More and more benefits in its original business


Cloud Computing: Economics of Scale

1,000 servers 50,000 serversNetwork (per 1M/sec) $95 $13Storage (per 1G) $2.2 $0.4Management (per 1 supervisor) 140 servers 1000 servers

Original concept of Grid

Also holds for clouds


cf. Clouds and Grids

Grid(ron)： networks (e.g., of pipes) for electricity, gas, etc.

Connect and use(without caring about the source, place, or realization means)

[By Ian Foster]Cloud, Grid, and Services can make us smarterServices make distributed resources and capabilities accessible over the networkGrid assists with integration via standardized service interfaces and collective VO servicesCloud provides for scalable hosting of collective services

VO: Virtual Organization


cf. Clouds and Grids


TOC


Amazon EC2 (Elastic Compute Cloud)provides servers (processors and memories)(IaaS: Infrastructure-as-a-Service)Operated with Xen (open source virtualization software)Allow for deployment of third-party images with operation systems and software packagese.g., Windows Server 2008 + SQL Server 2005

You can pick up a disk image from the catalog (thousands) and run/stop it whenever you want


Amazon EC2: Overview

Example of price settings:Virtual machine type “Small”1 core of 1 ECU(corresponding to 1.0-1.2GHz Opteron/Xeon)1.7GB Memory

$0.085/hour (Linux), $0.12/hour (Windows)( * 24h * 30days = $61.2, $86.4/month)Data download from EC2If 0-10 Tbyte in the month $0.15/GB

Data upload to EC2 $0.1/GB


Amazon EC2: Pricing (1)

Various choices1-3.25 ECU * 1- 8 cores, 1.7-68.4GB memory

Pay per usee.g., pay only for business hours (9am-5pm, 8 hour)

SLA: Service Level Agreement10% back if the annual availability is less than 99.95%

Other discountsReserved instances: if you pay for 1 year or 3 years, discount by about 2/3Spot instances: automatically make a bid for unused resources (actually the price said to be about 1/4-1/3)


Amazon EC2: Pricing (2)

Options Elastic IP Address: use fixed IP addressesAvailability Zone: operate virtual machines in different management zones in a data center (to avoid “all got down”)

API for “programmable data center”A variety of third-party management tools (e.g., visualization of server statuses)

API for interoperabilityEucalyplus-based (NII cloud, NASA cloud, etc.)


Amazon EC2: Options and Other services


Amazon: Whole Picture

[J. Varia, Architecting for The Cloud: Best Practices, 2010]


TOC


GAE (Google Application Engine)provides platforms for web applications(PaaS: Platform-as-a-Service)Dedicated mechanisms for scaling web serversAvailability and redundancy managementScalable programming

You can run scalable web applications using Google’s resources by following the given design strategies


GAE: Overview

Free use amount1.3 million HTTP requests10 GB for each of inbound/outbound6.5 CPU hours12 GB writing and 115 GB reading in data storeThousands of API calls (data store, mail, image, etc.)

Pay for increaseCPUBandwidthStorage


GAE: Pricing

Run a program in Python (or Java)Makes a response to a HTTP requestWithin 30 secondsWithout writing on file systems, directly using sockets or making sub processes or threads

Also possible to use other kinds of programsRun periodically by cronRun by email receiptPut into and run by task queues


GAE: Programming

Uses key-value data structures for persistent storage (Datastore)Uses BigTable developed for Google’s search indexingOperates on entities that have one or more key-value pairs (properties)

Distributed and replicated automaticallyNeeds to explicitly define groups of entities located “physically and logically nearby”Transactions can only be defined for entities in the same groupA too large group leads to bad performance


GAE: Datastore

Needs to follow the specific designs (to obtain the benefits of scalability and availability)Key-value DB (not RDB)Cannot efficiently count the number of data itemsCannot efficiently implement the join operation

Needs dedicated programsNo threads, no file system accesss, …

Existing web frameworks are often not optimal e.g., eager caching of libraries can lead to timeout and often not make effective results due to more frequent swap on memories


GAE: Specific Constraints


TOC


To handle more and more amounts of processing (e.g., requests)Scale Up: use stronger serversUsed in traditional on-premise servers

Scale Out: use large number of servers with management software toolsFor web-scale data sets (e.g., search engines)Based on an assumption that always there are some servers that do not workUses specific mechanisms for data and functionality (e.g., key-value DB, map reduce)


Scale Up and Scale Out

Key-Value DB are actively discussed for scaling out (often called NoSQL)


Key-Value DB v.s. RDB

Name Place RoleTom Tokyo DeveloperBob New York Manager

Name PlaceTom TokyoBob New York

Name RoleTom DeveloperBob Manager

RDB Key-Value Pairs

joinnormalize

Key ValueTom Place: Tokyo

Role: DeveloperAgency: CompanyA

Bob Place: New YorkRole: Manager

Advantages of key-value DBEfficient full-text search by parallel processingEfficient read operations by load distributionHigh availability by replication

Disadvantages of key-value DBDifficulties or inefficiency in keeping data consistencies and in transactions, due to large number of replications and optimistic (non-blocking) writing mechanisms often used


Key-Value DB v.s. RDB

Distributed frameworks for parallel processing of large data setsSplit large data sets and process on the large number of serversMap: a data chunk -> key-value listReduce: [key, list of values] -> list of values

A lot of implementationOrigin: Google’s MapReduce Framework(was used for re-indexing the WWW data)Hadoop open source framework…


Map Reduce

Word Count Example: (1)


Map Reduce

abc def hij …………… xyz

abc def …… pqr

def stu …… def

…

vwx abc…… xyz

[abc, 1][def, 1]…

[pqr, 1][def, 1][stu, 1]…

[def, 1]

…

[vwx, 1][abc, 1]…

[xyz, 1]

Split

Map



Map Reduce

[abc, 1][def, 1]…

[pqr, 1][def, 1][stu, 1]…

[def, 1]

…

[vwx, 1][abc, 1]…

[xyz, 1]

[abc, [1, 1, …, 1]][def, [1,1, …, 1]]

…[xyz, [1, 1, …, 1]]

Group

…

[abc, [1, 1, …, 1]]…

[def, [1, 1, …, 1]]…

[xyz, [1, 1, …, 1]]…

Partition



Map Reduce

…

[abc, [1, 1, …, 1]]…

[def, [1, 1, …, 1]]…

[xyz, [1, 1, …, 1]]…

…

[abc, 346212]…

[def, 96521]…

[xyz, 260412]…

Reduce

[abc, 346212][def, 96521]

…[xyz, 260412]

Output

New services and new providerse.g., AWS Marketplace (Apr 2012)

Standard software implementations for building cloudse.g., OpenStack, CloudStack

New software and applications…

At NIIedubase Cloud: http://edubase.jp/cloud/ (Ja)


Many Ongoing Efforts

July 7Cloud Computing: InsideRun a simple example to see “quick, flexible self-service” as well as pros and cons in terms of distributed processing

38Fuyuki Ishikawa

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lecture course service-oriented computing 11: cloud...

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