Do Clouds Compute? A Framework for Estimating the Value of Cloud Computing.

Do Clouds Compute? A Framework for Estimating the Value of Cloud Computing (WeB 2008 – The Seventh Workshop on e-Business) Markus Klems , Jens Nimis, Stefan Tai Forschungszentrum Informatik, Karlsruhe (Germany)

Observations

“ Cloud Computing” very popular in 2007 and 2008

Rich ecosystem of Cloud providers, enablers and users

Our understanding: Cloud != Grid

Research questions

What is Cloud Computing?

What is the value proposition of Cloud Computing?

Our approach & contribution

Collect real-world use cases where Cloud Computing is applied

Develop a structured, systematic framework to assist decision makers in valuating benefits specific to Cloud Computing technology

Introduction

Since Cloud Computing addresses different usage scenarios than Grid Computing we need a new way to valuate this technology.

A Short History of Cloud Computing Amazon EC2 (August 2006) Google App Engine (April 2008) Microsoft Azure (Oct 2008) Facebook Platform (May 2007) Amazon S3 (March 2006) Salesforce AppExchange (March 2006) Our Definition Building on compute and storage virtualization technologies, and leveraging the modern Web, Cloud Computing provides scalable and affordable compute utilities as on-demand services with variable pricing schemes, enabling a new consumer mass market.

The classical problem

Under-utilized server resources waste computing power (and energy)

Over-utilized servers cause interruption or degradation of service levels

The promise:

Server resources are delivered on-demand as usage-metered compute utilities

Cloud-user does not need to forecast demand

Turn fixed costs into variable costs

Promises of Cloud Computing

The emerging problems

Highly dynamic scalability demands

Time to market

Leveraging the modern Web

Evolution of Desktop apps to Software-as-a-Service

Programmable Web

The promise:

Reduced provision lead times

Scalability

Sophisticated infrastructure is available as Services

The promise:

A stable, reliable platform to develop, test and deploy network-centric end-user applications

We propose a basic framework for estimating value and determine benefits from Cloud Computing as an alternative to conventional IT infrastructure, such as on-premise infrastructure.

Our Framework: Overview 1. Business Scenario 2. Cost Comparison Value of Cloud Computing Service in opportunity costs

Qualitative Analysis 1. Business Scenario Create a list of Cloud Computing providers and their services and evaluate the services that meet your business scenario requirements according to the following criteria. 1.1 Business Case 1.2 Organization 1.3 Compliance 1.4 Business Objectives 1.5 Strategy 1.6 Demand 1.7 Application 1.8 Non-Functional Requirements 1.9 Finance

Example: Animoto* *http://aws.typepad.com/aws/2008/04/animoto---scali.html 1.1 Business Case

Animoto Videos Facebook application

1.2 Organization

Start-up company

1.3 Compliance

(data ownership and privacy regulations)

1.4 Business Objectives Drastically increase user base 1.5 Strategy Viral marketing 1.6 Demand

Linear growth in the first month up to 25,000 users

After a feature change: increase to 250,000 users within three days (1000%)

1.7 Application

Generate personalized music videos from users’ images and music files

1.8 Non-Functional Requirements

Scalability

High availability

1.9 Finance Low liquidity, tie costs to growth

Quantitative Analysis 2. Cost Comparison ** e.g. Amazon EC2 and S3, FlexiScale, Mosso (Rackspace), Joyent, etc. * e.g. on-premise IT infrastructure Infrastructure #1* (world without Cloud Computing) Infrastructure #2** (world with Cloud Computing) Define a cost metric for each attribute Calculate a cost estimate for #1 for each attribute Define a cost metric for each attribute Identify comparable infrastructure attributes Calculate a cost estimate for #2 for each attribute Aggregate the cost estimates Aggregate the cost estimates Value of Cloud Computing Services in terms of opportunity costs

Quantitative Analysis: Example 2. Cost Comparison ** e.g. Amazon EC2 and S3, FlexiScale, Mosso (Rackspace), Joyent, etc. * e.g. on-premise IT infrastructure Infrastructure #1* (world without Cloud Computing) Infrastructure #2** (world with Cloud Computing) Define a cost metric for each attribute Calculate a cost estimate for #1 for each attribute Define a cost metric for each attribute Identify comparable infrastructure attributes Calculate a cost estimate for #2 for each attribute Aggregate the cost estimates Aggregate the cost estimates Value of Cloud Computing Services in terms of opportunity costs e.g. processing power (ECU), storage capacity, … On-premise infrastructure Amazon EC2 Cumulative costs for attribute “processing power” Cumulative costs for attribute “processing power” Weigh costs for “processing power” with 100% Weigh costs for “processing power” with 100% Compare costs

Conclusion

Clouds provide scalable, abstracted IT infrastructure as Services

We propose a structured, systematic framework to value benefits from using Cloud Computing technology

Future Work

Further categorize use cases and apply our framework

Identify more valuation methods to extend the framework

Develop tools to compare different Cloud offerings and provide decision support

More information

http://cloudwiki.fzi.de

http://www.eOrganization.de (powered by Google App Engine)

http://www.cloudytimes.com (my blog)

Conclusion & Future Work

Thank you! Questions & Discussion

The Beauty of Simplicity

Web Development

Infrastructure

complex, error-prone, hideous spaghetti code simple, test-driven, elegant, stable, agile Web development framework complex, error-prone, fragile IT infrastructure simple, elegant, stable, scalable, pay-per-use IT infrastructure (as a Service)

End-user applications, Software-as-a-Service (SaaS)

Platform-as-a-Service (PaaS)

Infrastructure-as-a-Service (IaaS)

Cloud Ecosystem Google App Engine Platform as a Service (PaaS) End-User Applications Salesforce AppExchange Facebook Platform Facebook Apps Live Mesh AppExchange Apps OpenSocial Apps Amazon Web Services Rackspace 3tera Joyent Infrastructure as a Service (IaaS) Brokers, Tools and Frameworks End-User Applications flexiscale NASDAQ Market Replay Jungle Disk Powerset Mosso cohesiveFT RightScale MLB zimory enomaly Aptana cloud

Grid vs. Cloud Grid Cloud Underlying concept Utility Computing Utility Computing Main benefit Solve computationally complex problems Provide a scalable standard environment for network-centric application development, testing and deployment Resource distribution / allocation Negotiate and manage resource sharing; schedulers Simple user <-> provider model; pay-per-use Domains Multiple domains Single domain Character / history Non-commercial, publicly funded Commercial

Animoto Use Case http://www.animoto.com

Simple Cost Calculation (1) Amazon EC2 Extra-large standard instance 1 ECU / instance 8 ECU 8 * http://aws.amazon.com/ec2/#instance Price 0.8 $ / (extra-large standard instance * hour) Additional services 0.2 * assumed to be additional 25% of the ECU price Total costs 0.125 $ / (ECU * hour) On-Premise Servers 1 dell.com: Quad Core Intel Xeon 5405 ECUs / server 8 dell.com: Quad Core Intel Xeon 5405 ECU 8 Price / server 1700 dell.com: Quad Core Intel Xeon 5405 Additional infrastructure 850 * assumption: 50% of server costs CapEx 850 $ / year (straight line depreciateion over 3 years, no discounting) CapEx / hour 0.10 $ / hour Power 213 * assumption: 25% of infrastructure costs / year IT management 85 * assumption: 10% of infrastructure costs / year Network fees 85 * assumption: 10% of infrastructure costs / year OpEx 383 $ / year OpEx / hour 0.04 $ / hour Total costs 0.018 $ / (ECU * hour)

Simple Cost Calculation (2) * plus additional infrastructure, power, networking and IT staff; keep 20% empty space buffer to max. predicted demand Cost Comparison: IT infrastructure #1 IT infrastructure #2 Description Quad-core servers* Amazon EC2 Scenario Starting with 400 ECU in the first month; 1000% instant traffic increase in the second month; then back to 400 Metric: USD / (ECU * h) 0.02 0.125 Cum. costs of 1 st month 56,729 USD 33,600USD Cum. costs of first 6 months 340,373 USD 277,200 USD

Simple Cost Calculation (3) Time (month) Demand (predicted) Cloud Cloud costs Cum Cloud costs Cloud infrastructure / demand On-premise infrastructure On-premise infrastructure costs Cum on-premise costs On-premise infrastructure / demand 1 400.00 400 8400 8400 100% 4800 14182 14182 1200% 400.00 400 8400 16800 100% 4800 14182 28364 1200% 400.00 400 8400 25200 100% 4800 14182 42547 1200% 400.00 400 8400 33600 100% 4800 14182 56729 1200% 2 4000.00 4000 84000 117600 100% 4800 14182 70911 120% 4000.00 400 8400 126000 10% 4800 14182 85093 120% 4000.00 400 8400 134400 10% 4800 14182 99275 120% 4000.00 400 8400 142800 10% 4800 14182 113458 120% 3 400.00 400 8400 151200 100% 4800 14182 127640 1200% 400.00 400 8400 159600 100% 4800 14182 141822 1200% 400.00 400 8400 168000 100% 4800 14182 156004 1200% 400.00 400 8400 176400 100% 4800 14182 170186 1200% 4 400.00 400 8400 184800 100% 4800 14182 184368 1200% 400.00 400 8400 193200 100% 4800 14182 198551 1200% 400.00 400 8400 201600 100% 4800 14182 212733 1200% 400.00 400 8400 210000 100% 4800 14182 226915 1200% 5 400.00 400 8400 218400 100% 4800 14182 241097 1200% 400.00 400 8400 226800 100% 4800 14182 255279 1200% 400.00 400 8400 235200 100% 4800 14182 269462 1200% 400.00 400 8400 243600 100% 4800 14182 283644 1200% 6 400.00 400 8400 252000 100% 4800 14182 297826 1200% 400.00 400 8400 260400 100% 4800 14182 312008 1200% 400.00 400 8400 268800 100% 4800 14182 326190 1200% 400.00 400 8400 277200 100% 4800 14182 340373 1200% Sum 24000.00 13200 277200 115200 340373

(Fictional) Example: Large-Scale Enterprise 1.1 Business Case

Internet-scale testing environment

1.2 Organization

Complex and heterogeneous IT infrastructure

1.3 Compliance

Industry-dependent, e.g.

Financial / accounting: SOX, Basel II

Health care: HIPAA compliance

…

1.4 Business Objectives Reduce time to market by shortening innovation cycles 1.5 Strategy Private or public Cloud? 1.6 Demand Predictable, expected demand 1.7 Application