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Yeah! That’s what I’d like to know.

Indranil Gupta (Indy)Lecture 2

What(’s in) the Cloud?January 21, 2010

CS 525 Advanced Distributed

SystemsSpring 2010

All Slides © IG

2

Clouds are Water Vapor

• Oracle has a Cloud Computing Center.

• And yet…

• Larry Ellison’s Rant on Cloud Computing

2

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The Hype!• Gartner - Cloud computing revenue

will soar faster than expected and will exceed $150 billion within five years.

• Forrester - Cloud-Based Email Is Often Cheaper Than On-Premise Email

• Vivek Kundra, CTO of Obama Government: “Growing adoption of cloud computing could improve data sharing and promote collaboration among federal, state and local governments.” E.g: fedbizopps.gov

• Merrill Lynch: “By 2011 the volume of cloud computing market opportunity would amount to $160bn, including $95bn in business and productivity apps (email, office, CRM, etc.) and $65bn in online advertising.”

• IDC: “Spending on IT cloud services will triple in the next 5 years, reaching $42 billion and capturing 25% of IT spending growth in 2012.”

Sources: http://www.infosysblogs.com/cloudcomputing/2009/08/the_cloud_computing_quotes.htm and http://www.mytestbox.com

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Ha ha hype! It’s a bunch of tripe, since no one is

probably making or saving money.

5

$$$

• Ingo Elfering, Vice President of Information Technology Strategy, GlaxoSmithKline:“With Online Services, we are able to reduce our IT operational costs by roughly 30% of what we’re spending now and introduce a variable cost subscription model for these technologies that allows us to more rapidly scale or divest our investment as necessary as we undergo a transformational change in the pharmaceutical industry”

• Jim Swartz, CIO, Sybase: “At Sybase, a private cloud of virtual servers inside its data centre has saved nearly $US2 million annually since 2006, Swartz says, because the company can share computing power and storage resources across servers.”

• Dave Power, Associate Information Consultant at Eli Lilly and Company: “With AWS, Powers said, a new server can be up and running in three minutes (it used to take Eli Lilly seven and a half weeks to deploy a server internally) and a 64-node Linux cluster can be online in five minutes (compared with three months internally). The deployment time is really what impressed us. It's just shy of instantaneous."

Sources: http://www.infosysblogs.com/cloudcomputing/2009/08/the_cloud_computing_quotes.htm and http://www.mytestbox.com

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Alright, alright. But for heaven’s sake, can someone tell

me what is a cloud?

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What is a Cloud?

• It’s a cluster! It’s a supercomputer! It’s a datastore!

• It’s superman!

• None of the above• All of the above

• Cloud = Lots of storage + compute cycles nearby

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What is a Cloud?

• A single-site cloud (aka “Datacenter”) consists of– Compute nodes (split into racks)– Switches, connecting the racks– A network topology, e.g., hierarchical– Storage (backend) nodes connected to the network– Front-end for submitting jobs– Services: physical resource set, software services

• A geographically distributed cloud consists of– Multiple such sites– Each site perhaps with a different structure and

services

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A Sample Cloud Topology

Top of the Rack Switch

Core Switch

Servers

Rack

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Scale of Industry Datacenters

• Microsoft [NYTimes, 2008]– 150,000 machines– Growth rate of 10,000 per month– Largest datacenter: 48,000 machines– 80,000 total running Bing

• Yahoo! [Hadoop Summit, 2009]– 25,000 machines– Split into clusters of 4000

• AWS EC2 (Oct 2009)– 40,000 machines– 8 cores/machine

• Google– (Rumored) several hundreds of thousands of machines

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OK, they are massive. But it is still called a “cluster”! And

that’s not a new concept!

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1940

1950

1960

1970

1980

1990

2000

Timesharing Companies & Data Processing Industry

2010

Grids

Peer to peer systems

Clusters

The first datacenters!

PCs(not distributed!)

Clouds and datacenters

“A Cloudy History of Time” © IG 2010

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Timesharing Industry (1975):•Market Share: Honeywell 34%, IBM 15%, •Xerox 10%, CDC 10%, DEC 10%, UNIVAC 10%•Honeywell 6000 & 635, IBM 370/168, Xerox 940 & Sigma 9, DEC PDP-10, UNIVAC 1108

Grids (1980s-2000s):•GriPhyN (1970s-80s)•Open Science Grid and Lambda Rail (2000s)•Globus & other standards (1990s-2000s)

First large datacenters: ENIAC, ORDVAC, ILLIACMany used vacuum tubes and mechanical relays

P2P Systems (90s-00s)•Many Millions of users•Many GB per day

Data Processing Industry - 1968: $70 M. 1978: $3.15 Billion.

Berkeley NOW ProjectSupercomputersServer Farms (e.g., Oceano)

“A Cloudy History of Time” © IG 2010

Clouds

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Why did all of this happen?

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Trends: Technology

• Doubling Periods – storage: 12 mos, bandwidth: 9 mos, and (what law is this?) cpu speed: 18 mos

• Then and Now

Bandwidth– 1985: mostly 56Kbps links nationwide– 2004: 155 Mbps links widespread

Disk capacity– Today’s PCs have 100GBs, same as a 1990

supercomputer

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Trends: Users• Then and Now Biologists:

– 1990: were running small single-molecule simulations – 2004: want to calculate structures of complex

macromolecules, want to screen thousands of drug candidates, sequence very complex genomes

Physicists– 2008 onwards: CERN’s Large Hadron Collider will

produce 700 MB/s or 15 PB/year

• Trends in Technology and User Requirements: Independent or Symbiotic?

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Prophecies

In 1965, MIT's Fernando Corbató and the other designers of the Multics operating system envisioned a computer facility operating “like a power company or water company”.

Plug your thin client into the computing Utilityand Play your favorite Intensive Compute &Communicate Application

– [Have today’s clouds brought us closer to this reality?]

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So, clouds have been around for decades! But

aside from massive scale what’s new about today’s

cloud computing?!

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What(’s new) in Today’s Clouds?Three major features:I. On-demand access: Pay-as-you-go, no upfront

commitment.– Anyone can access it (e.g., Washington Post – Hillary Clinton

example)

II. Data-intensive Nature: What was MBs has now become TBs.

– Daily logs, forensics, Web data, etc.– Do you know the size of Wikipedia dump?

III. New Cloud Programming Paradigms: MapReduce/Hadoop, Pig Latin, DryadLinq, Swift, and many others.

– High in accessibility and ease of programmability

Combination of one or more of these gives rise to novel and unsolved distributed computing problems in cloud computing.

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I. On-demand access: *aaS Classification

On-demand: renting a cab vs (previously) renting a car, or buying one. E.g.: – AWS Elastic Compute Cloud (EC2): $0.086-$1.16 per CPU hour – AWS Simple Storage Service (S3): $0.055-$0.15 per GB-month

• HaaS: Hardware as a Service– You get access to barebones hardware machines, do whatever you want with

them– Ex: Your own cluster, Emulab

• IaaS: Infrastructure as a Service– You get access to flexible computing and storage infrastructure. Virtualization is

one way of achieving this. Often said to subsume HaaS.– Ex: Amazon Web Services (AWS: EC2 and S3), Eucalyptus, Rightscale.

• PaaS: Platform as a Service– You get access to flexible computing and storage infrastructure, coupled with a

software platform (often tightly)– Ex: Google’s AppEngine

• SaaS: Software as a Service– You get access to software services, when you need them. Often said to

subsume SOA (Service Oriented Architectures).– Ex: Microsoft’s LiveMesh, MS Office on demand

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II. Data-intensive Computing

• Computation-Intensive Computing– Example areas: MPI-based, High-performance computing, Grids– Typically run on supercomputers (e.g., NCSA Blue Waters)

• Data-Intensive– Typically store data at datacenters– Use compute nodes nearby– Compute nodes run computation services

• In data-intensive computing, the focus shifts from computation to the data: CPU utilization no longer the most important resource metric

• Problem areas include– Distributed systems– Middleware – OS– Storage – Networking– Security– Others

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III. New Cloud Programming Paradigms

Dataflow programming frameworks• Google: MapReduce and Sawzall• Yahoo: Hadoop and Pig Latin• Microsoft: DryadLINQ• Facebook: Hive• Amazon: Elastic MapReduce service (pay-as-you-go)• Google (MapReduce)

– Indexing: a chain of 24 MapReduce jobs– ~200K jobs processing 50PB/month (in 2006)

• Yahoo! (Hadoop + Pig)– WebMap: a chain of 100 MapReduce jobs– 280 TB of data, 2500 nodes, 73 hours

• Facebook (Hadoop + Hive)– ~300TB total, adding 2TB/day (in 2008)– 3K jobs processing 55TB/day

• Similar numbers from other companies, e.g., Yieldex, eharmony.com, etc.

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This is all confusing. Can you give me some

examples of clouds?

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Two Categories of Clouds• Industrial Clouds

– Can be either a (i) public cloud, or (ii) private cloud– Private clouds are accessible only to company employees– Public clouds provide service to any paying customer:

• Amazon S3 (Simple Storage Service): store arbitrary datasets ,pay per GB-onth stored

• Amazon EC2 (Elastic Compute Cloud): upload and run arbitrary images, pay per CPU hour used

• Google AppEngine: develop applications within their appengine framework, upload data that will be imported into their format, and run

• Academic Clouds – Allow researchers to innovate, deploy, and experiment– Google-IBM Cloud (U. Washington): run apps programmed atop

Hadoop– Cloud Computing Testbed (CCT @ UIUC): first cloud testbed to support

systems research. Runs: (i) apps programmed atop Hadoop and Pig, (ii) systems-level research on this first generation of cloud computing models (~HaaS), and (iii) Eucalyptus services (~AWS EC2). http://cloud.cs.illinois.edu

– OpenCirrus: first federated cloud testbed. http://opencirrus.org

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Academic Clouds

• CCT = Cloud Computing Testbed– NSF infrastructure– Used by 10+ NSF projects, including several non-UIUC

projects– Housed within Siebel Center (4th floor!)– Accessible to students of CS525!

• Almost half of SP09 course used CCT for their projects

• OpenCirrus = Federated Cloud Testbed– Contains CCT and other sites

• If you need a CCT account for your CS525 experiment, let me know asap! There are a limited number of these available for CS525

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Cloud Computing Testbed (CCT)

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•128 compute nodes = 64+64

•500 TB & 1000+ shared cores

CCT Hardware in more Detail

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Goal of CCT: Support both Systems Research and Applications Research

in Data-intensive Distributed Computing

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CCT Software Services

Accessing and Using CCT:

I. Systems Partition (64-8 nodes):– CentOS machines– Dedicated access to a subset of machines (~

Emulab), with sudo access– User accounts

• User requests # machines (<= 64) + storage quota (<= 30 TB)

• Machine allocation survives for 4 weeks, storage survives for 6 months (both extendible)

II. Hadoop/Pig Partition and Service (64 nodes)

III. Eucalyptus Partition (8 nodes)

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Accessing and Using CCT:I. Systems Partition (64-8 nodes)II. Hadoop/Pig Partition and Service (64 nodes):

– Looks like a regular shared Hadoop cluster service• Users share 64 nodes. Individual nodes not directly

reachable.• 4 slots per machine• Several users report stable operation at 256 instances• During Spring 09, 10+ projects running simultaneously

– User accounts• User requests account + storage quota (<= 30 TB)• Storage survives for 6 months (extendible)

III. Eucalyptus Partition (8 nodes)

CCT Software Services

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Accessing and Using CCT:

I. Systems Partition (64-8 nodes)

II. Hadoop/Pig Partition and Service (64 nodes):

III. Eucalyptus Partition (8 nodes): • Based on open-source version of

Eucalyptus from UCSB (Rich Wolski)• Exports same interface as AWS EC2 and

S3.

CCT Software Services

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• Some Services running inside CCT– ZFS: backend file system. – Zenoss: Systems Monitoring. Shared with

department’s other computing clusters– Hadoop + HDFS– Ability to make datasets publicly available

• How do users request an account: two-stage process (go to http://cloud.cs.illinois.edu )1. User account request – require background check

2. Allocation request

CCT Software Services

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Founding 6 sites

Open Cirrus Federation

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34 April 20, 2023

HP

UIUC

IntelKIT (de)

IDA (sg)

Yahoo

First open federated cloud testbed

Shared: research, applications, infrastructure (9*1,000 cores), data sets

Global services: sign on, monitoring, store, etc., Federated clouds, meaning each is different

CMU

RAS

ETRI

MIMOS

Grown to 9 sites, with more to come

Open Cirrus Federation

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OK, so that’s what a cloud looks like today. Now,

suppose I want to start my own company, Devils Inc.

Should I buy a cloud and own it, or should I outsource to a

public cloud?

Next Week

• We will continue discussion of cloud computing– How MapReduce works– What is PlanetLab and Emulab– What is Grid computing

• Then we will start to discuss Basics of P2P systems

• Please read at least one paper from each session

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Administrative Announcements

Student-led paper presentations (see instructions on website)• Start from February 11th• Groups of up to 2 students present each class, responsible

for a set of 3 “Main Papers” on a topic– 45 minute presentations (total) followed by discussion– Set up appointment with me to show slides by 5 pm day prior to

presentation– Select your topic by Jan 31st

• List of papers is up on the website• Each of the other students (non-presenters) expected to read

the papers before class and turn in a one to two page review of the any two of the main set of papers (summary, comments, criticisms and possible future directions)– Email review and bring in hardcopy before class

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Announcements (contd.)

Projects• Groups of 2 (need not be same as

presentation groups)• We’ll start detailed discussions “soon” (a few

classes into the student-led presentations)