An Introduction to Cloud Computing by Robert Grossman 08-06-09 (v19)

An Overview of Cloud Computing:My Other Computer is a Data Center
Robert GrossmanOpen Data Group &
University of Illinois at Chicago
IEEE New Technologies Conference
August 6, 2009

Part 1What is a Cloud?
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What is a Cloud?
3
Software as a Service

What Else is a Cloud?
4
Platform as a Service

Is Anything Else a Cloud?
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Infrastructure as a Service

Are There Other Types of Clouds?
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ad targeting
Large Data Cloud Services

One Definition
Clouds provide on-demand resources or services over a network, often the Internet, with the scale and reliability of a data center.
No standard definition.
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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costs the same as
1 computer in a rack for 120 hours
120 computers in three racks for 1 hour

Elastic, usage based pricing turns capex into opex.
Clouds can be used to 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.

Part 2Varieties of Clouds
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Varieties of Clouds
Architectural Model
On-demand computing instances vs large data cloud services
Payment Model
Elastic, usage based pricing, lease/own, …
Management Model
Private vs Public; Single vs Multiple Tenant; …
Programming Model
Queue Service, MPI, MapReduce, Distributed UDF
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Computing instances vs large data cloud services
Private internal vspublic external
Elastic, usage-based pricing or not
All combinations occur.

Architectural Models:How Do You Fill a Data Center?
large data cloud services
App
App
App
App
App
on-demand computing instances
Cloud Data Services (BigTable, etc.)
Quasi-relational Data Services
App
App
…
Cloud Compute Services (MapReduce & Generalizations)
App
App
App
App
App
Cloud Storage Services

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 Models
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on-demand
computing instances
large data cloud services
Amazon’s Simple Queue Service
MPI, sockets, FIFO

DryadLINQ
Azure services
MapReduce
Distributed UDF

Part 3. 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.

SaaS
PaaS
IaaS
IaaS, PaaS and SaaS Point of View
Software as a Service
PRODUCT: Finished application available on demand to end user
USERS: Software consumer
Platform as a Service
PRODUCT: storage, compute and other services to simplify application development, especially of web applications.
USERS: Application Developers
Infrastructure as a Service
PRODUCT: Compute power, storage and networking infrastructure over the internet, provided as a virtual machine image
USERS: Developers

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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Data Center Operating Systems
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…
…
VM 50,000
VM 1
VM 1
VM 5
Data Center Operating System
workstation
Data center services include: VM management services, business continuity services, security services, power management services, etc.

Berkeley View of Cloud Computing
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Consumers of Software as a Service
Providers of Software as a Service
Data Centers
Consumers of Cloud Services
Providers of Cloud Services
Berkeley Report on cloud computing divides industry into these layers & concentrates on public clouds.

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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Mindmeister Map of Cloud Computing
Dupont’sMindmeister Map divides the industry:
IaaS, PaaS, Management, Community
http://www.mindmeister.com/maps/show_public/15936058
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Part 4
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.
Technology pioneered by IBM in 1960s to better utilize mainframes
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Idea Dates Back to the 1960s
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App
App
App
CMS
CMS
MVS
IBM VM/370
IBM Mainframe
Native (Full) Virtualization
Examples: Vmware ESX

Two Types of Virtualization
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Apps
Apps
Unmodified Guest OS 1
Unmodified Guest OS 2
Modified Guest OS 1
Modified Guest OS 2
Hyperviser
Hyperviser
Physical Hardware
Physical Hardware
Native (Full) Virtualization
Examples: Vmware ESX
Para Virtualization
Examples: Xen
Using the hypervisor, each guest OS sees its own independent copy of the CPU, memory, IO, etc.

Four Key Properties
Partitioning: run multiple VMs on one physical server; one VM doesn’t know about the others
Isolation: security isolation is at the hardware level.
Encapsulation: entire state of the machine can be copied to files and moved around
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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Large Data Clouds
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Part 5

The Google Data Stack
The Google File System (2003)
MapReduce: Simplified Data Processing… (2004)
BigTable: A Distributed Storage System… (2006)
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Map-Reduce Example
Input is file with one document per record
User specifies map function
key = document URL
Value = terms that document contains
“it”, 1“was”, 1“the”, 1“best”, 1
(“doc cdickens”,“it was the best of times”)
map

Example (cont’d)
MapReduce library gathers together all pairs with the same key value (shuffle/sort phase)
The user-defined reduce function combines all the values associated with the same key
key = “it”values = 1, 1
“it”, 2“was”, 2“best”, 1“worst”, 1
key = “was”values = 1, 1
reduce
key = “best”values = 1
key = “worst”values = 1

Generalization: Apply User Defined Functions (UDF) to Files in Storage Cloud
map/shuffle
reduce
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UDF
UDF

Google’s Layered Cloud Services
Table Services
Compute Services
Storage Services
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Applications
Google’s BigTable
Google’s MapReduce
Google File System (GFS)
Google’s Stack

Hadoop’s Layered Cloud Services
Table Services
Compute Services
Storage Services
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Applications
Hadoop’sMapReduce
Hadoop Distributed File System (HDFS)
Hadoop’s Stack

Sector’s Layered Cloud Services
Table Services
Compute Services
Storage Services
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Applications
Sphere’s UDF
Sector’s Distributed File System (SDFS)
UDP-based Data Transport Protocol (UDT)
Routing & Transport Services
Sector’s Stack

Hadoop & Sector
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MalStone Benchmark
Benchmark developed by Open Cloud Consortium for clouds supporting data intensive computing.
Code to generate synthetic data required is available from code.google.com/p/malgen
Stylized analytic computation that is easy to implement in MapReduce and its generalizations.
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MalStone B
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entities
sites
dk-2
dk-1
dk
time

MalStone B Benchmark
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Trading Functionality for Scalability
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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 6. Standards Efforts
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Train gauge in Russia is 1520 mm
Train gauge in China is 1435 mm
How can a cloud application move from one cloud storage service to another?
Change of gauge at Ussuriisk (near Vladivostok) at the Chinese –Russian border

Standards Efforts for Clouds
Cloud Computing Interoperability Forum (CCIF)
Open Cloud Consortium (OCC)
Open Grid Forum (OGF)
Distributed Management Task Force (DMTF)
Storage Network Industrial Association (SNIA)
Plus several others…
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www.opencloudconsortium.org
Supports the development of standards.
Supports reference implementations for cloud computing, preferably open source.
Manages a testbed for cloud computing called the Open Cloud Testbed.
Supports the development of benchmarks.
Sponsors workshops and other events related to cloud computing.
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Activities Currently Focused Around Five Use Cases
Moving an existing cloud application from Cloud 1 to Cloud 2 without changing the application.
Providing surge capacity for an application on Cloud 1 using any of the Clouds 2, 3, … (without changing the application).
Migrate / port
Surge / burst
Cloud 2
Cloud 1

Large Data Cloud Use Cases
Moving a large data cloud application from one large data cloud storage service to another.
Moving a large data cloud application from one large data cloud compute service to another.
App 1
App 2
Large Data Cloud Compute Services
Large Data Cloud Storage Services

Inter-Cloud Use Case
Inter-cloud communication between two HIPAA compliant clouds.
Cloud 2
Cloud 1

OCC Welcomes New Members
Companies and organizations are welcome to join the Open Cloud Consortium (OCC)
www.opencloudconsortium.org/membership.html
Join one of our working groups
Large Data Clouds Working Group
Standard Cloud Performance Measurement (SCPM) Working Group
Information Sharing & Security Working Group

For More Information
Contact information:
Robert Grossman
rlg@opendatagroup.com
blog.rgrossman.com
Web sites
www.opendatagroup.com
www.ncdm.uic.edu
www.opencloudconsortium.org
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