2: Cloud Computing Paradigms

Zubair Nabi

zubair.nabi@itu.edu.pk

April 17, 2013

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 1 / 22

Outline

1 Introduction

2 Cloud service providers

3 Utility Computing

4 Economics

5 Challenges

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 2 / 22

Outline

1 Introduction

2 Cloud service providers

3 Utility Computing

4 Economics

5 Challenges

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 3 / 22

Cloud computing

A realization of utility computing in which computation, storage, andservices are offered as a metered service

Encompasses applications delivered as services over the Internet andhardware and software in the datacenters that enable those services

I Software as a Service (SaaS)

Public Cloud: If available to the public as a pay-as-you-go model, e.g.Amazon Web Services, Google AppEngine, and Microsoft Azure

Private Cloud: Internal datacenters of an organization that are notpublicly accessible

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 4 / 22

Cloud computing

A realization of utility computing in which computation, storage, andservices are offered as a metered serviceEncompasses applications delivered as services over the Internet andhardware and software in the datacenters that enable those services

I Software as a Service (SaaS)

Public Cloud: If available to the public as a pay-as-you-go model, e.g.Amazon Web Services, Google AppEngine, and Microsoft Azure

Private Cloud: Internal datacenters of an organization that are notpublicly accessible

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 4 / 22

Cloud computing

A realization of utility computing in which computation, storage, andservices are offered as a metered serviceEncompasses applications delivered as services over the Internet andhardware and software in the datacenters that enable those services

I Software as a Service (SaaS)

Public Cloud: If available to the public as a pay-as-you-go model, e.g.Amazon Web Services, Google AppEngine, and Microsoft Azure

Private Cloud: Internal datacenters of an organization that are notpublicly accessible

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 4 / 22

Cloud computing

A realization of utility computing in which computation, storage, andservices are offered as a metered serviceEncompasses applications delivered as services over the Internet andhardware and software in the datacenters that enable those services

I Software as a Service (SaaS)

Public Cloud: If available to the public as a pay-as-you-go model, e.g.Amazon Web Services, Google AppEngine, and Microsoft Azure

Private Cloud: Internal datacenters of an organization that are notpublicly accessible

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 4 / 22

Cloud computing

A realization of utility computing in which computation, storage, andservices are offered as a metered serviceEncompasses applications delivered as services over the Internet andhardware and software in the datacenters that enable those services

I Software as a Service (SaaS)

Public Cloud: If available to the public as a pay-as-you-go model, e.g.Amazon Web Services, Google AppEngine, and Microsoft Azure

Private Cloud: Internal datacenters of an organization that are notpublicly accessible

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 4 / 22

Advantages

Advantages to both service providers and end users

1 Service providers:I Simplified software installation and maintenanceI Centralized control over versioningI No need to build, provision, and maintain a datacenterI On the fly scaling

2 End users:I “Anytime, anywhere” accessI Share data and collaborate easilyI Safeguard data stored in the infrastructure (debatable)

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 5 / 22

Advantages

Advantages to both service providers and end users1 Service providers:

I Simplified software installation and maintenance

I Centralized control over versioningI No need to build, provision, and maintain a datacenterI On the fly scaling

2 End users:I “Anytime, anywhere” accessI Share data and collaborate easilyI Safeguard data stored in the infrastructure (debatable)

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 5 / 22

Advantages

Advantages to both service providers and end users1 Service providers:

I Simplified software installation and maintenanceI Centralized control over versioning

I No need to build, provision, and maintain a datacenterI On the fly scaling

2 End users:I “Anytime, anywhere” accessI Share data and collaborate easilyI Safeguard data stored in the infrastructure (debatable)

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 5 / 22

Advantages

Advantages to both service providers and end users1 Service providers:

I Simplified software installation and maintenanceI Centralized control over versioningI No need to build, provision, and maintain a datacenter

I On the fly scaling

2 End users:I “Anytime, anywhere” accessI Share data and collaborate easilyI Safeguard data stored in the infrastructure (debatable)

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 5 / 22

Advantages

Advantages to both service providers and end users1 Service providers:

I Simplified software installation and maintenanceI Centralized control over versioningI No need to build, provision, and maintain a datacenterI On the fly scaling

2 End users:I “Anytime, anywhere” accessI Share data and collaborate easilyI Safeguard data stored in the infrastructure (debatable)

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 5 / 22

Advantages

Advantages to both service providers and end users1 Service providers:

I Simplified software installation and maintenanceI Centralized control over versioningI No need to build, provision, and maintain a datacenterI On the fly scaling

2 End users:I “Anytime, anywhere” access

I Share data and collaborate easilyI Safeguard data stored in the infrastructure (debatable)

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 5 / 22

Advantages

Advantages to both service providers and end users1 Service providers:

I Simplified software installation and maintenanceI Centralized control over versioningI No need to build, provision, and maintain a datacenterI On the fly scaling

2 End users:I “Anytime, anywhere” accessI Share data and collaborate easily

I Safeguard data stored in the infrastructure (debatable)

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 5 / 22

Advantages

Advantages to both service providers and end users1 Service providers:

I Simplified software installation and maintenanceI Centralized control over versioningI No need to build, provision, and maintain a datacenterI On the fly scaling

2 End users:I “Anytime, anywhere” accessI Share data and collaborate easilyI Safeguard data stored in the infrastructure (debatable)

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 5 / 22

Outline

1 Introduction

2 Cloud service providers

3 Utility Computing

4 Economics

5 Challenges

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 6 / 22

History

Phenomenal growth of Web services in late 90s and early 2000s

Large Internet companies, including Amazon, eBay, Google, Microsoft,Yahoo, etc., already had massive infrastructure

To keep up with demand, these companies also developed scalablesoftware infrastructure (think MapReduce, GFS, BigTable, Dynamo, etc.)

They also acquired the operational expertise to deter potential physicaland electronic attacks

Therefore, they had already created extremely large datacenters toleverage statistical multiplexing and bulk purchasing of infrastructure

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 7 / 22

History

Phenomenal growth of Web services in late 90s and early 2000s

Large Internet companies, including Amazon, eBay, Google, Microsoft,Yahoo, etc., already had massive infrastructure

To keep up with demand, these companies also developed scalablesoftware infrastructure (think MapReduce, GFS, BigTable, Dynamo, etc.)

They also acquired the operational expertise to deter potential physicaland electronic attacks

Therefore, they had already created extremely large datacenters toleverage statistical multiplexing and bulk purchasing of infrastructure

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 7 / 22

History

Phenomenal growth of Web services in late 90s and early 2000s

Large Internet companies, including Amazon, eBay, Google, Microsoft,Yahoo, etc., already had massive infrastructure

To keep up with demand, these companies also developed scalablesoftware infrastructure (think MapReduce, GFS, BigTable, Dynamo, etc.)

They also acquired the operational expertise to deter potential physicaland electronic attacks

Therefore, they had already created extremely large datacenters toleverage statistical multiplexing and bulk purchasing of infrastructure

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 7 / 22

History

Phenomenal growth of Web services in late 90s and early 2000s

Large Internet companies, including Amazon, eBay, Google, Microsoft,Yahoo, etc., already had massive infrastructure

To keep up with demand, these companies also developed scalablesoftware infrastructure (think MapReduce, GFS, BigTable, Dynamo, etc.)

They also acquired the operational expertise to deter potential physicaland electronic attacks

Therefore, they had already created extremely large datacenters toleverage statistical multiplexing and bulk purchasing of infrastructure

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 7 / 22

History

Phenomenal growth of Web services in late 90s and early 2000s

Large Internet companies, including Amazon, eBay, Google, Microsoft,Yahoo, etc., already had massive infrastructure

To keep up with demand, these companies also developed scalablesoftware infrastructure (think MapReduce, GFS, BigTable, Dynamo, etc.)

They also acquired the operational expertise to deter potential physicaland electronic attacks

Therefore, they had already created extremely large datacenters toleverage statistical multiplexing and bulk purchasing of infrastructure

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 7 / 22

Incentive for providers

Incentives include revenue, leveraging existing investment, defending afranchise, attacking an incumbent, leveraging customer relationships, andbecoming a platform

Data centers are being established in seemingly arbitrary locations

Reasons for choosing a location include costs of electricity, cooling,labour, property, and taxes

Cooling and electricity account for 1/3rd of all costs!

Cheaper to ship data over fiber optic cables than to ship electricity overhigh-voltage transmission lines

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 8 / 22

Incentive for providers

Incentives include revenue, leveraging existing investment, defending afranchise, attacking an incumbent, leveraging customer relationships, andbecoming a platform

Data centers are being established in seemingly arbitrary locations

Reasons for choosing a location include costs of electricity, cooling,labour, property, and taxes

Cooling and electricity account for 1/3rd of all costs!

Cheaper to ship data over fiber optic cables than to ship electricity overhigh-voltage transmission lines

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 8 / 22

Incentive for providers

Incentives include revenue, leveraging existing investment, defending afranchise, attacking an incumbent, leveraging customer relationships, andbecoming a platform

Data centers are being established in seemingly arbitrary locations

Reasons for choosing a location include costs of electricity, cooling,labour, property, and taxes

Cooling and electricity account for 1/3rd of all costs!

Cheaper to ship data over fiber optic cables than to ship electricity overhigh-voltage transmission lines

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 8 / 22

Incentive for providers

Incentives include revenue, leveraging existing investment, defending afranchise, attacking an incumbent, leveraging customer relationships, andbecoming a platform

Data centers are being established in seemingly arbitrary locations

Reasons for choosing a location include costs of electricity, cooling,labour, property, and taxes

Cooling and electricity account for 1/3rd of all costs!

Cheaper to ship data over fiber optic cables than to ship electricity overhigh-voltage transmission lines

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 8 / 22

Incentive for providers

Incentives include revenue, leveraging existing investment, defending afranchise, attacking an incumbent, leveraging customer relationships, andbecoming a platform

Data centers are being established in seemingly arbitrary locations

Reasons for choosing a location include costs of electricity, cooling,labour, property, and taxes

Cooling and electricity account for 1/3rd of all costs!

Cheaper to ship data over fiber optic cables than to ship electricity overhigh-voltage transmission lines

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 8 / 22

New technology trends and business models

“High-touch, high-margin, high-commitment” provisioning of service to“low-touch, low-margin, low-commitment”

For instance:I Payment model in Web 1.0: Contractual arrangement with a payment

processing service such as VeriSign or Authorize.net; making it hard forsmall businesses to accept credit card payment online

I Web 2.0: With PayPal-like services anyone can sign up and accept creditpayments without a contract and a long-term commitment

Another example:I Ad revenue model in Web 1.0: Set up a relationship with an ad placement

company, such as DoubleClickI Web 2.0: Use Google AdSense

This same model was used by Amazon Web Services in 2006:pay-as-you-go computing with no contract, with the only requirementbeing a credit card

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 9 / 22

New technology trends and business models

“High-touch, high-margin, high-commitment” provisioning of service to“low-touch, low-margin, low-commitment”For instance:

I Payment model in Web 1.0: Contractual arrangement with a paymentprocessing service such as VeriSign or Authorize.net; making it hard forsmall businesses to accept credit card payment online

I Web 2.0: With PayPal-like services anyone can sign up and accept creditpayments without a contract and a long-term commitment

Another example:I Ad revenue model in Web 1.0: Set up a relationship with an ad placement

company, such as DoubleClickI Web 2.0: Use Google AdSense

This same model was used by Amazon Web Services in 2006:pay-as-you-go computing with no contract, with the only requirementbeing a credit card

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 9 / 22

New technology trends and business models

“High-touch, high-margin, high-commitment” provisioning of service to“low-touch, low-margin, low-commitment”For instance:

I Payment model in Web 1.0: Contractual arrangement with a paymentprocessing service such as VeriSign or Authorize.net; making it hard forsmall businesses to accept credit card payment online

I Web 2.0: With PayPal-like services anyone can sign up and accept creditpayments without a contract and a long-term commitment

Another example:I Ad revenue model in Web 1.0: Set up a relationship with an ad placement

company, such as DoubleClickI Web 2.0: Use Google AdSense

This same model was used by Amazon Web Services in 2006:pay-as-you-go computing with no contract, with the only requirementbeing a credit card

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 9 / 22

New technology trends and business models

“High-touch, high-margin, high-commitment” provisioning of service to“low-touch, low-margin, low-commitment”For instance:

I Payment model in Web 1.0: Contractual arrangement with a paymentprocessing service such as VeriSign or Authorize.net; making it hard forsmall businesses to accept credit card payment online

I Web 2.0: With PayPal-like services anyone can sign up and accept creditpayments without a contract and a long-term commitment

Another example:I Ad revenue model in Web 1.0: Set up a relationship with an ad placement

company, such as DoubleClick

I Web 2.0: Use Google AdSense

This same model was used by Amazon Web Services in 2006:pay-as-you-go computing with no contract, with the only requirementbeing a credit card

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 9 / 22

New technology trends and business models

“High-touch, high-margin, high-commitment” provisioning of service to“low-touch, low-margin, low-commitment”For instance:

I Payment model in Web 1.0: Contractual arrangement with a paymentprocessing service such as VeriSign or Authorize.net; making it hard forsmall businesses to accept credit card payment online

I Web 2.0: With PayPal-like services anyone can sign up and accept creditpayments without a contract and a long-term commitment

Another example:I Ad revenue model in Web 1.0: Set up a relationship with an ad placement

company, such as DoubleClickI Web 2.0: Use Google AdSense

This same model was used by Amazon Web Services in 2006:pay-as-you-go computing with no contract, with the only requirementbeing a credit card

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 9 / 22

New technology trends and business models

“High-touch, high-margin, high-commitment” provisioning of service to“low-touch, low-margin, low-commitment”For instance:

I Payment model in Web 1.0: Contractual arrangement with a paymentprocessing service such as VeriSign or Authorize.net; making it hard forsmall businesses to accept credit card payment online

I Web 2.0: With PayPal-like services anyone can sign up and accept creditpayments without a contract and a long-term commitment

Another example:I Ad revenue model in Web 1.0: Set up a relationship with an ad placement

company, such as DoubleClickI Web 2.0: Use Google AdSense

This same model was used by Amazon Web Services in 2006:pay-as-you-go computing with no contract, with the only requirementbeing a credit card

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 9 / 22

New applications

Mobile applications: Require high availability and rely on large data setsthat are most conveniently hosted in large datacenters

Parallel batch processing: Analytics jobs that analyze terabytes of dataand can take hours to finish can leverage the “cost associativity” of thecloud

Business analytics: Understanding customers, supply chains, buyinghabits, ranking, and so on

Computation offloading: Compute-intensive tasks are offloaded to thecloud. For instance, Matlab, Mathematica, image rendering, 3Danimations, etc.

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 10 / 22

New applications

Mobile applications: Require high availability and rely on large data setsthat are most conveniently hosted in large datacenters

Parallel batch processing: Analytics jobs that analyze terabytes of dataand can take hours to finish can leverage the “cost associativity” of thecloud

Business analytics: Understanding customers, supply chains, buyinghabits, ranking, and so on

Computation offloading: Compute-intensive tasks are offloaded to thecloud. For instance, Matlab, Mathematica, image rendering, 3Danimations, etc.

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 10 / 22

New applications

Mobile applications: Require high availability and rely on large data setsthat are most conveniently hosted in large datacenters

Parallel batch processing: Analytics jobs that analyze terabytes of dataand can take hours to finish can leverage the “cost associativity” of thecloud

Business analytics: Understanding customers, supply chains, buyinghabits, ranking, and so on

Computation offloading: Compute-intensive tasks are offloaded to thecloud. For instance, Matlab, Mathematica, image rendering, 3Danimations, etc.

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 10 / 22

New applications

Mobile applications: Require high availability and rely on large data setsthat are most conveniently hosted in large datacenters

Parallel batch processing: Analytics jobs that analyze terabytes of dataand can take hours to finish can leverage the “cost associativity” of thecloud

Business analytics: Understanding customers, supply chains, buyinghabits, ranking, and so on

Computation offloading: Compute-intensive tasks are offloaded to thecloud. For instance, Matlab, Mathematica, image rendering, 3Danimations, etc.

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 10 / 22

Outline

1 Introduction

2 Cloud service providers

3 Utility Computing

4 Economics

5 Challenges

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 11 / 22

Classes of utility computing

Every application needs computation, storage, and quite possiblycommunication

These resources need to be virtualized to achieve elasticity and theillusion of infinite capacity

The details of statistical multiplexing and sharing is abstracted away fromthe programmer

Different utility computing offerings can be distinguished on the basis ofthe abstraction presented to the programmer

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 12 / 22

Classes of utility computing

Every application needs computation, storage, and quite possiblycommunication

These resources need to be virtualized to achieve elasticity and theillusion of infinite capacity

The details of statistical multiplexing and sharing is abstracted away fromthe programmer

Different utility computing offerings can be distinguished on the basis ofthe abstraction presented to the programmer

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 12 / 22

Classes of utility computing

Every application needs computation, storage, and quite possiblycommunication

These resources need to be virtualized to achieve elasticity and theillusion of infinite capacity

The details of statistical multiplexing and sharing is abstracted away fromthe programmer

Different utility computing offerings can be distinguished on the basis ofthe abstraction presented to the programmer

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 12 / 22

Classes of utility computing

Every application needs computation, storage, and quite possiblycommunication

These resources need to be virtualized to achieve elasticity and theillusion of infinite capacity

The details of statistical multiplexing and sharing is abstracted away fromthe programmer

Different utility computing offerings can be distinguished on the basis ofthe abstraction presented to the programmer

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 12 / 22

Bare metal hardware abstraction

An instance looks like physical hardware

Programmers control the entire software stack from the kernel upwards

Employed by Amazon EC2

A very thin API is exposed to request and configure virtualized hardwareNo bar on the kinds of applications that can be hosted

I Low level virtualization, block-device storage, and IP-level connectivityallow developers to design any application

On the downside, scalability and failover are application-dependent

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 13 / 22

Bare metal hardware abstraction

An instance looks like physical hardware

Programmers control the entire software stack from the kernel upwards

Employed by Amazon EC2

A very thin API is exposed to request and configure virtualized hardwareNo bar on the kinds of applications that can be hosted

I Low level virtualization, block-device storage, and IP-level connectivityallow developers to design any application

On the downside, scalability and failover are application-dependent

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 13 / 22

Bare metal hardware abstraction

An instance looks like physical hardware

Programmers control the entire software stack from the kernel upwards

Employed by Amazon EC2

A very thin API is exposed to request and configure virtualized hardwareNo bar on the kinds of applications that can be hosted

I Low level virtualization, block-device storage, and IP-level connectivityallow developers to design any application

On the downside, scalability and failover are application-dependent

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 13 / 22

Bare metal hardware abstraction

An instance looks like physical hardware

Programmers control the entire software stack from the kernel upwards

Employed by Amazon EC2

A very thin API is exposed to request and configure virtualized hardware

No bar on the kinds of applications that can be hostedI Low level virtualization, block-device storage, and IP-level connectivity

allow developers to design any application

On the downside, scalability and failover are application-dependent

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 13 / 22

Bare metal hardware abstraction

An instance looks like physical hardware

Programmers control the entire software stack from the kernel upwards

Employed by Amazon EC2

A very thin API is exposed to request and configure virtualized hardwareNo bar on the kinds of applications that can be hosted

I Low level virtualization, block-device storage, and IP-level connectivityallow developers to design any application

On the downside, scalability and failover are application-dependent

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 13 / 22

Bare metal hardware abstraction

An instance looks like physical hardware

Programmers control the entire software stack from the kernel upwards

Employed by Amazon EC2

A very thin API is exposed to request and configure virtualized hardwareNo bar on the kinds of applications that can be hosted

I Low level virtualization, block-device storage, and IP-level connectivityallow developers to design any application

On the downside, scalability and failover are application-dependent

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 13 / 22

Bare metal hardware abstraction

An instance looks like physical hardware

Programmers control the entire software stack from the kernel upwards

Employed by Amazon EC2

A very thin API is exposed to request and configure virtualized hardwareNo bar on the kinds of applications that can be hosted

I Low level virtualization, block-device storage, and IP-level connectivityallow developers to design any application

On the downside, scalability and failover are application-dependent

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 13 / 22

Domain-specific platform

Target traditional web applications

Enforce an application structure of clean separation between a statelesscomputation tier and a stateful storage tier

Employed by Google AppEngine

Applications are expected to be request-reply based

In contrast to the bare metal hardware abstraction, enable automaticscaling and high-availability mechanisms

Not suitable for general-purpose computing

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 14 / 22

Domain-specific platform

Target traditional web applications

Enforce an application structure of clean separation between a statelesscomputation tier and a stateful storage tier

Employed by Google AppEngine

Applications are expected to be request-reply based

In contrast to the bare metal hardware abstraction, enable automaticscaling and high-availability mechanisms

Not suitable for general-purpose computing

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 14 / 22

Domain-specific platform

Target traditional web applications

Enforce an application structure of clean separation between a statelesscomputation tier and a stateful storage tier

Employed by Google AppEngine

Applications are expected to be request-reply based

In contrast to the bare metal hardware abstraction, enable automaticscaling and high-availability mechanisms

Not suitable for general-purpose computing

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 14 / 22

Domain-specific platform

Target traditional web applications

Enforce an application structure of clean separation between a statelesscomputation tier and a stateful storage tier

Employed by Google AppEngine

Applications are expected to be request-reply based

In contrast to the bare metal hardware abstraction, enable automaticscaling and high-availability mechanisms

Not suitable for general-purpose computing

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 14 / 22

Domain-specific platform

Target traditional web applications

Enforce an application structure of clean separation between a statelesscomputation tier and a stateful storage tier

Employed by Google AppEngine

Applications are expected to be request-reply based

In contrast to the bare metal hardware abstraction, enable automaticscaling and high-availability mechanisms

Not suitable for general-purpose computing

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 14 / 22

Domain-specific platform

Target traditional web applications

Enforce an application structure of clean separation between a statelesscomputation tier and a stateful storage tier

Employed by Google AppEngine

Applications are expected to be request-reply based

In contrast to the bare metal hardware abstraction, enable automaticscaling and high-availability mechanisms

Not suitable for general-purpose computing

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 14 / 22

Hybrid

Offer a sweet spot between flexibility and programmer convenience

Offered by Microsoft’s Azure

Applications are written using .NET libraries and compiled to the CommonLanguage Runtime (A language-independent management environment)

Supports general purpose computing

Users have control over the choice of language but not the underlying OSor runtime

Provide some degree of automatic failover and scalability but requiresome help from the developer in the form of declaration of someapplication properties

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 15 / 22

Hybrid

Offer a sweet spot between flexibility and programmer convenience

Offered by Microsoft’s Azure

Applications are written using .NET libraries and compiled to the CommonLanguage Runtime (A language-independent management environment)

Supports general purpose computing

Users have control over the choice of language but not the underlying OSor runtime

Provide some degree of automatic failover and scalability but requiresome help from the developer in the form of declaration of someapplication properties

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 15 / 22

Hybrid

Offer a sweet spot between flexibility and programmer convenience

Offered by Microsoft’s Azure

Applications are written using .NET libraries and compiled to the CommonLanguage Runtime (A language-independent management environment)

Supports general purpose computing

Users have control over the choice of language but not the underlying OSor runtime

Provide some degree of automatic failover and scalability but requiresome help from the developer in the form of declaration of someapplication properties

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 15 / 22

Hybrid

Offer a sweet spot between flexibility and programmer convenience

Offered by Microsoft’s Azure

Applications are written using .NET libraries and compiled to the CommonLanguage Runtime (A language-independent management environment)

Supports general purpose computing

Users have control over the choice of language but not the underlying OSor runtime

Provide some degree of automatic failover and scalability but requiresome help from the developer in the form of declaration of someapplication properties

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 15 / 22

Hybrid

Offer a sweet spot between flexibility and programmer convenience

Offered by Microsoft’s Azure

Applications are written using .NET libraries and compiled to the CommonLanguage Runtime (A language-independent management environment)

Supports general purpose computing

Users have control over the choice of language but not the underlying OSor runtime

Provide some degree of automatic failover and scalability but requiresome help from the developer in the form of declaration of someapplication properties

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 15 / 22

Hybrid

Offer a sweet spot between flexibility and programmer convenience

Offered by Microsoft’s Azure

Applications are written using .NET libraries and compiled to the CommonLanguage Runtime (A language-independent management environment)

Supports general purpose computing

Users have control over the choice of language but not the underlying OSor runtime

Provide some degree of automatic failover and scalability but requiresome help from the developer in the form of declaration of someapplication properties

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 15 / 22

Outline

1 Introduction

2 Cloud service providers

3 Utility Computing

4 Economics

5 Challenges

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 16 / 22

Elasticity

Pay-as-you-go model: Only pay for what you use

Add or remove resources at a fine grain (such as one server at a time)with minimal lead time

Useful for traffic spikes such as “Black Friday”

Over time, hardware costs come down and vendors acquire updatedhardware. Thus, benefiting the tenant

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 17 / 22

Elasticity

Pay-as-you-go model: Only pay for what you use

Add or remove resources at a fine grain (such as one server at a time)with minimal lead time

Useful for traffic spikes such as “Black Friday”

Over time, hardware costs come down and vendors acquire updatedhardware. Thus, benefiting the tenant

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 17 / 22

Elasticity

Pay-as-you-go model: Only pay for what you use

Add or remove resources at a fine grain (such as one server at a time)with minimal lead time

Useful for traffic spikes such as “Black Friday”

Over time, hardware costs come down and vendors acquire updatedhardware. Thus, benefiting the tenant

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 17 / 22

Elasticity

Pay-as-you-go model: Only pay for what you use

Add or remove resources at a fine grain (such as one server at a time)with minimal lead time

Useful for traffic spikes such as “Black Friday”

Over time, hardware costs come down and vendors acquire updatedhardware. Thus, benefiting the tenant

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 17 / 22

Reasons for companies to migrate to the cloud

Pay separately per resource: Pay proportional to resource requirements

Power, cooling, and physical plant costs: Cost of electricity andcooling already factored in

Man-power costs: No need to employ sysadmins

Operational costs: Low-level upgrades and software patchesresponsibility of the provider

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 18 / 22

Reasons for companies to migrate to the cloud

Pay separately per resource: Pay proportional to resource requirements

Power, cooling, and physical plant costs: Cost of electricity andcooling already factored in

Man-power costs: No need to employ sysadmins

Operational costs: Low-level upgrades and software patchesresponsibility of the provider

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 18 / 22

Reasons for companies to migrate to the cloud

Pay separately per resource: Pay proportional to resource requirements

Power, cooling, and physical plant costs: Cost of electricity andcooling already factored in

Man-power costs: No need to employ sysadmins

Operational costs: Low-level upgrades and software patchesresponsibility of the provider

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 18 / 22

Reasons for companies to migrate to the cloud

Pay separately per resource: Pay proportional to resource requirements

Power, cooling, and physical plant costs: Cost of electricity andcooling already factored in

Man-power costs: No need to employ sysadmins

Operational costs: Low-level upgrades and software patchesresponsibility of the provider

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 18 / 22

Outline

1 Introduction

2 Cloud service providers

3 Utility Computing

4 Economics

5 Challenges

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 19 / 22

Obstacles

1 Service availability: Possibility of cloud outage

2 Data lock-in: Reliance on cloud specific APIs

3 Security: Requires strong encrypted storage, VLANs, and networkmiddleboxes (firewalls, etc.)

4 Data transfer bottlenecks: Moving large amounts of data in and out isexpensive

5 Performance unpredictability: Resource sharing between applications

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 20 / 22

Obstacles

1 Service availability: Possibility of cloud outage

2 Data lock-in: Reliance on cloud specific APIs

3 Security: Requires strong encrypted storage, VLANs, and networkmiddleboxes (firewalls, etc.)

4 Data transfer bottlenecks: Moving large amounts of data in and out isexpensive

5 Performance unpredictability: Resource sharing between applications

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 20 / 22

Obstacles

1 Service availability: Possibility of cloud outage

2 Data lock-in: Reliance on cloud specific APIs

3 Security: Requires strong encrypted storage, VLANs, and networkmiddleboxes (firewalls, etc.)

4 Data transfer bottlenecks: Moving large amounts of data in and out isexpensive

5 Performance unpredictability: Resource sharing between applications

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 20 / 22

Obstacles

1 Service availability: Possibility of cloud outage

2 Data lock-in: Reliance on cloud specific APIs

3 Security: Requires strong encrypted storage, VLANs, and networkmiddleboxes (firewalls, etc.)

4 Data transfer bottlenecks: Moving large amounts of data in and out isexpensive

5 Performance unpredictability: Resource sharing between applications

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 20 / 22

Obstacles

1 Service availability: Possibility of cloud outage

2 Data lock-in: Reliance on cloud specific APIs

3 Security: Requires strong encrypted storage, VLANs, and networkmiddleboxes (firewalls, etc.)

4 Data transfer bottlenecks: Moving large amounts of data in and out isexpensive

5 Performance unpredictability: Resource sharing between applications

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 20 / 22

Obstacles (2)

6 Scalable storage: No standard model to arbitrarily scale storage up anddown on-demand while ensuring data durability and high availability

7 Bugs in large-scale distributed systems: Hard to debug large-scaleapplications in full deployment

8 Scaling quickly: Automatically scaling while conserving resources andmoney is an open ended problem

9 Reputation fate sharing: Bad behaviour by one tenant can reflect badlyon the rest

10 Software licensing: Gap between pay-as-you-go model and softwarelicensing

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 21 / 22

Obstacles (2)

6 Scalable storage: No standard model to arbitrarily scale storage up anddown on-demand while ensuring data durability and high availability

7 Bugs in large-scale distributed systems: Hard to debug large-scaleapplications in full deployment

8 Scaling quickly: Automatically scaling while conserving resources andmoney is an open ended problem

9 Reputation fate sharing: Bad behaviour by one tenant can reflect badlyon the rest

10 Software licensing: Gap between pay-as-you-go model and softwarelicensing

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 21 / 22

Obstacles (2)

6 Scalable storage: No standard model to arbitrarily scale storage up anddown on-demand while ensuring data durability and high availability

7 Bugs in large-scale distributed systems: Hard to debug large-scaleapplications in full deployment

8 Scaling quickly: Automatically scaling while conserving resources andmoney is an open ended problem

9 Reputation fate sharing: Bad behaviour by one tenant can reflect badlyon the rest

10 Software licensing: Gap between pay-as-you-go model and softwarelicensing

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 21 / 22

Obstacles (2)

6 Scalable storage: No standard model to arbitrarily scale storage up anddown on-demand while ensuring data durability and high availability

7 Bugs in large-scale distributed systems: Hard to debug large-scaleapplications in full deployment

8 Scaling quickly: Automatically scaling while conserving resources andmoney is an open ended problem

9 Reputation fate sharing: Bad behaviour by one tenant can reflect badlyon the rest

10 Software licensing: Gap between pay-as-you-go model and softwarelicensing

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 21 / 22

Obstacles (2)

6 Scalable storage: No standard model to arbitrarily scale storage up anddown on-demand while ensuring data durability and high availability

7 Bugs in large-scale distributed systems: Hard to debug large-scaleapplications in full deployment

8 Scaling quickly: Automatically scaling while conserving resources andmoney is an open ended problem

9 Reputation fate sharing: Bad behaviour by one tenant can reflect badlyon the rest

10 Software licensing: Gap between pay-as-you-go model and softwarelicensing

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 21 / 22

References

1 Above the Clouds: A Berkeley View of Cloud Computing" by MichaelArmbrust, Armando Fox, Rean Griffith, Anthony D. Joseph, Randy Katz,Andy Konwinski, Gunho Lee, David Patterson, Ariel Rabkin, Ion Stoica,and Matei Zaharia. Technical Report EECS-2009-28, EECS Department,University of California, Berkeley.

Zubair Nabi 2: Cloud Computing Paradigms April 17, 2013 22 / 22