This is an extract from great presentation by Pat Helland. I just extracted some slides to present Cloud Computing fast. When you have time, read the entire presentation and the relative paper.
Book Report” on the UC Berkeley Paper “Above the Clouds: a Berkeley View of Cloud Computing”
http://blogs.msdn.com/pathelland/archive/2009/04/10/book-report-on-the-uc-berkeley-paper-above-the-clouds-a-berkeley-view-of-cloud-computing.aspx
http://cid-84f3c5ef51d06e8b.skydrive.live.com/self.aspx/.Public/2009/Above-the-Clouds-090401k.pptx
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2010 03 31 Marco Parenzan An Extract From Above The Clouds By Pat Helland
1. Some slides from
"Above the Clouds:
a Berkeley View of Cloud Computing"
Created by:
Pat Helland
Partner Architect (SQL SIA)
Presented by:
Pat HellandMarco Parenzan
Partner Architect (SQL SIA)
Clarification:
• I did NOT write this paper – I am reporting on some excellent work.
• Much of this paper’s content is well known to the folks working
in the cloud computing space.
• Hats off to the folks from Berkeley for such a crisp and thoughtful paper!
•I’m a programmer and I think that this kind of documents are written better by other people
•Original Slide Deck
•http://cid-84f3c5ef51d06e8b.skydrive.live.com/self.aspx/.Public/2009/Above-the-Clouds-
1 090401k.pptx
2. Dilbert on Cloud Computing
Novembre 18th, 2009
http://www.dilbert.com/strips/comic/2009-11-18/
Novembre 19th, 2009
http://www.dilbert.com/strips/comic/2009-11-19/
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3. MyPat Helland’s Experiences with “Cloud Computing”
Over 25 Years Working in Distributed Computing
Tandem Computers HaL Computers Microsoft
(1982-1990) (1991-1994) (1994-2005 and 2007-Present)
Message Based Microsoft Transaction Server (MTS):
Multiprocessor Chief Architect: Transactional RPC and N-Tier Apps
Cache-Coherent
WAN Distributed DB Non-Uniform Distributed Transaction Coordinator
Chief Architect: Fault- Memory Arch SQL Service Service Oriented
Tolerant TX Platform Multi-Processor Broker Architectures (SOA)
2 Years at Amazon (2005-2007)
Worked to Make Saw “Cloud Computing” Firsthand
Software Accept Low
Extensive Monitoring Multiple Datacenters
Availability Datacenters
Drive to Commonality Pressure on Availability
Worked On Product Drive to Commodity Creation of Dynamo
Catalog: 10s of Millions
of Product Descriptions Internals of AWS Cost Pressure on Services…
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4. Cloud Computing: Confusion
The interesting thing about cloud computing is that we’ve redefined
Cloud Computing to include everything that we already do… I don’t understand
what we would do differently in the light of Cloud Computing than change
some of the words in our ads.
Larry Ellison (Oracle CEO) , quoted in the Wall Street Journal, Sept 26, 2008
A lot of people are jumping on the [cloud] bandwagon, but I have not heard
two people say the same thing about it. There are multiple definitions
out there of “the cloud”
Andy Isherwood (HP VP of European Software Sales), in ZDNews, Dec 11, 2008
It’s stupidity. It’s worse than stupidity: it’s a marketing hype campaign.
Somebody is saying this is inevitable – and whenever you hear somebody saying
that, it’s very likely to be a set of businesses campaigning to make it true.
Richard Stallman (“free software” advocate), in The Guardian, Sept 29, 2008
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5. What Is Cloud Computing?
Cloud Computing: App and Infrastructure over Internet
Software as a Service: Applications over the Internet
Utility Computing:
“Pay-as-You-Go” Datacenter Hardware and Software
Three New Aspects to Cloud Computing
The Illusion of Infinite Computing Resources Available on Demand
The Elimination of an Upfront Commitment by Cloud Users
The Ability to Pay for Use of Computing Resources
on a Short-Term Basis as Needed
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6. New Application Opportunities
Gray’s Observation: Jim Gray Looked at Trends in 2003 Wide-Area Networking
Falling Slower than
Costs Require Putting the Data Near the Application! Other IT Costs
Some Interesting New Types of Applications Enable By the Cloud:
Mobile Interactive Apps: Applications that respond in real time but work with lots of
data. Cloud computing offers highly-available large datasets.
Parallel Batch Processing: “Cost Associativity” – Many systems for a short time.
Washington Post used 200EC2 instances to process 17,481 pages of Hillary Clinton’s
travel documents within 9 hours of their release.
Rise of Analytics: Again, “Cost Associativity” – Many systems for a short time.
Compute intensive data analysis which may be parallelized.
Compute Intensive Desktop Apps: For example, symbolic mathematics requires lots of
computing per unit of data. Cost efficient to push the data to the cloud for computation
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7. A Spectrum of Application Models
Less More
Constrained Constraints in the App Model Constrained
Microsoft Azure Google App Engine
Amazon AWS .NET CLR/Windows Only Traditional Web Apps
VMs Look Like Hardware Choice of Language Auto Scaling/Provisioning
No Limit on App Model Some Auto Failover/
User Must Implement Scale (but needs Force.Com
Scalability and Failover declarative application SalesForce Biz Apps
properties) Auto Scaling/Provisioning
Less More
Automation Automated Management Services Automation
Which Model Will Dominate?? High-Level Languages
Analogy: Programming Languages and Frameworks and Frameworks Can Be
• Low-Level Languages (C/C++) Allow Fine-Grained Control Built on Lower-Level
• Building a Web App in C++ Is a Lot of Cumbersome Work More-Constrained
• Ruby-on-Rails Hides the Mechanics but Only If You Follow Clouds May Be Built on
Request/Response and Ruby’s Abstractions Less-Constrained Ones
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8. Conclusions and Questions about the
Cloud of Tomorrow
Utility Computing: It’s Happening!
Grow and Shrink on Demand
Pay-As-You-Go
Cloud Provider’s View
Huge Datacenters Opened Economies and Possibilities
Cloud User’s View
Startups Don’t Need Datacenters
Established Organizations Leverage Elasticity
UC Berkeley Has Extensively Leveraged Elasticity to Meet Deadlines
Cloud Computing: High-Margin or Low-Margin Business?
Potential Cost Factor of 5-7X
Today’s Cloud Providers Had Big Datacenter Infrastructure Anyway
Implications of Cloud:
Application Software: Scale-Up and Down Rapidly; Client and Cloud
Infrastructure Software: Runs on VMs; Has Built-in Billing
Hardware Systems: Huge Scale; Container-Based; Energy Proportional
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9. Top 10 Obstacles and Opportunities
Obstacle Opportunity
1 Availability of Service Use Multiple Cloud Providers;
Use Elasticity to Prevent DDOS
2 Data Lock-In Standardized APIs; Compatible Software
to Enable Surge Computing
3 Data Confidentiality and Deploy Encryption, VLANs, Firewalls;
Auditability Geographical Data Storage
4 Data Transfer Bottlenecks FedExing Disks; Data Backup/Archival;
Higher Bandwidth Switches
5 Performance Unpredictability Improved VM Support; Flash Memory;
Gang Scheduling VMs
6 Scalable Storage Invent Scalable Store
7 Bugs in Large Distributed Systems Invent Debugger that Relies on Dist VMs
8 Scaling quickly Auto-Scaler; Snaphots for Conservation
9 Reputation Fate Sharing Reputation Guarding Services
10 Software Licensing Pay-for-Use Licenses; Bulk Use Sales
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10. #3 Obstacle:
Data Confidentiality and Auditability
“My sensitive corporate data will never be in the cloud!”
Current Clouds Are Auditability Is Required
Essentially Public Sarbanes-Oxley
They Networks to
Are Exposed
More Attacks HIPAA
Berkeley Believes There Are No Fundamental Obstacles
to Making Cloud Computing as Secure as Most In-House IT
Encrypted Storage Virtual LANs Network Middleboxes (Firewalls, Packet Filters)
Encrypted Data in the Cloud Is Likely More Secure than Unencrypted Data on Premises
Maybe: Cloud More Focus Concerns over USA PATRIOT Act
Provided Auditability on Virtual National Boundaries Gives Some
Auditing Below VMs Capabilities… Foreign Subpoenas Europeans
Worries over
Maybe More Tamper Resistant Blind Subpoenas SaaS in the USA
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11. #4 Obstacle: Data Transfer Bottlenecks
Problem: At $100 to $150 per Terabyte Transferred,
Data Placement and Movement Is an Issue
Opportunity-1: Sneaker-Net Opportunity-2: Keep Data
Jim Gray Found Cheapest Transfer in Cloud
Was FedEx-ing Disks If the Data Is in the Cloud,
1 Data Failure in 400 Attempts Transfer Doesn’t Cost
Amazon Hosting Large Data
Example: Ship 10TB from
UC Berkeley to Amazon E.g. US Census
-- WAN: S3 < 20Mbits/sec: Free on S3; Free on EC2
10TB 4Mil Seconds > 45 Days Entice EC2 Business
$1000 in AMZN Net Fees Opportunity-3: Cheaper WAN
-- FedEx: Ten 1TB Disks via Overnight Shipping High-End Routers Are a Big Part
< 1 Day to Write 10TB to Disks Locally of the Cost of Data Transfer
Cost ≈ $400 Research into Routing using
Effective BW of 1500Mbits/Sec Cheap Commodity Computers
“NetFlix for Cloud Computing”
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12. To better undestand, read the originals...
Above the Clouds: a Berkeley View of Cloud Computing
http://www.eecs.berkeley.edu/Pubs/TechRpts/2009/EECS-2009-28.pdfCloud
Computing
Book Report” on the UC Berkeley Paper “Above the Clouds: a Berkeley View
of Cloud Computing”
http://blogs.msdn.com/pathelland/archive/2009/04/10/book-report-on-the-uc-
berkeley-paper-above-the-clouds-a-berkeley-view-of-cloud-computing.aspx
http://cid-84f3c5ef51d06e8b.skydrive.live.com/self.aspx/.Public/2009/Above-the-
Clouds-090401k.pptx
Demystifying the Cloud (Simon Guest)
http://simonguest.com/blogs/smguest/archive/2009/05/14/Slides-from-TechEd-
2009.aspx
An introduction to Cloud Computing
http://s3.amazonaws.com/ppt-download/ima-cloud-computing-mar2010-v8-
100320181538-
phpapp02.pdf?Signature=GhK3ogCr2Z%2FzhWFa%2F%2BJUr1cT1eg%3D&Expires
=1269958049&AWSAccessKeyId=AKIAJLJT267DEGKZDHEQ
…and many others
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