cloud modelling language (cloudml) · •scalability •performance •availability •cost . s...

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Cloud Modelling Language (CloudML)

Alessandro Rossini

INF5120

6 May 2013


Alessandro Rossini


Alessandro Rossini

Education


Alessandro Rossini

Education • 2004-2006 M.Sc., Università dell'Aquila (Italia) Universitetet i Bergen


Alessandro Rossini

Education • 2004-2006 M.Sc., Università dell'Aquila (Italia) Universitetet i Bergen • 2008-2011 Ph.D., Universitetet i Bergen


Alessandro Rossini

Education • 2004-2006 M.Sc., Università dell'Aquila (Italia) Universitetet i Bergen • 2008-2011 Ph.D., Universitetet i Bergen Employment


Alessandro Rossini

Education • 2004-2006 M.Sc., Università dell'Aquila (Italia) Universitetet i Bergen • 2008-2011 Ph.D., Universitetet i Bergen Employment • 2007 Software engineer, Integrator, Bergen


Alessandro Rossini

Education • 2004-2006 M.Sc., Università dell'Aquila (Italia) Universitetet i Bergen • 2008-2011 Ph.D., Universitetet i Bergen Employment • 2007 Software engineer, Integrator, Bergen • 2008-2012 Research fellow, Universitetet i Bergen


Alessandro Rossini

Education • 2004-2006 M.Sc., Università dell'Aquila (Italia) Universitetet i Bergen • 2008-2011 Ph.D., Universitetet i Bergen Employment • 2007 Software engineer, Integrator, Bergen • 2008-2012 Research fellow, Universitetet i Bergen • 2012 Lecturer, Høgskolen i Bergen


Alessandro Rossini

Education • 2004-2006 M.Sc., Università dell'Aquila (Italia) Universitetet i Bergen • 2008-2011 Ph.D., Universitetet i Bergen Employment • 2007 Software engineer, Integrator, Bergen • 2008-2012 Research fellow, Universitetet i Bergen • 2012 Lecturer, Høgskolen i Bergen • 2012- Research scientist, SINTEF, Oslo


Cloud computing


Cloud computing

A computing model enabling ubiquitous network access to a shared and virtualised pool of

computing capabilities (e.g., network, storage, processing, and memory) that can be rapidly provisioned with minimal management effort

source: NIST


source: Graviant


IaaS PaaS SaaS


Applications

Data

Run-time

OS

Virtualisation

Servers

Storage

Network

IaaS PaaS SaaS


Applications

Data

Run-time

OS

Virtualisation

Servers

Storage

Network

Cons

umer

Pr

ovid

er

IaaS PaaS SaaS


Applications

Data

Run-time

OS

Virtualisation

Servers

Storage

Network

Applications

Data

Run-time

OS

Virtualisation

Servers

Storage

Network

Cons

umer

Pr

ovid

er

Cons

umer

Pr

ovid

er

IaaS PaaS SaaS


Applications

Data

Run-time

OS

Virtualisation

Servers

Storage

Network

Applications

Data

Run-time

OS

Virtualisation

Servers

Storage

Network

Applications

Data

Run-time

OS

Virtualisation

Servers

Storage

Network

Cons

umer

Pr

ovid

er

Cons

umer

Pr

ovid

er

Prov

ider

IaaS PaaS SaaS


Benefits

• Scalability

• Performance

• Availability

• Cost


Challenges

• Heterogeneity

• Incompatibility

• Lack of standards

• Lack of methodologies


CloudML


Amazon AWS Rackspace

IBM SmartCloud Terramark

…


Amazon AWS OpenStack vCloud



…

…

Stacks


jclouds Simple Cloud Deltacloud




…

…

…

Libraries

Stacks


Cloudify Cloud Foundry Scalr





…

…

…

…

Frameworks

Libraries

Stacks


Cloudify Cloud Foundry Scalr





…

…

…

…

Frameworks

Libraries

Stacks

PaaS

IaaS


CloudML

• Domain-specific language (DSL) for modelling the provisioning and deployment of multi-cloud systems at design-time

• Models@run-time environment for enacting the provisioning and deployment of these systems at run-time


EU Projects

• MODAClouds

• PaaSage

• REMICS

http://www.modaclouds.eu/

http://www.paasage.eu/

http://remics.eu/


Resources

• http://cloudml.org (overhaul coming soon)

• https://github.com/SINTEF-9012/cloudml/

http://cloudml.org/

http://cloudml.org/

https://github.com/SINTEF-9012/cloudml/


Design-time


Cloud Provider-Independent Model (CPIM)


CPIM

• Generic provisioning and deployment model that is independent of the cloud provider


CPIM

• Generic provisioning and deployment model that is independent of the cloud provider

• Consists of node types and artefacts types


Node type

• Generic virtual machine – a virtual machine running GNU/Linux


Node type

• Provisioning requirements – 2 cores ≤ compute ≤ 4 cores

– 2 GiB ≤ memory ≤ 4 GiB

– storage ≥ 10 GiB

– location = Europe


Node type example (JSON) "nodeTypes": [

{

"id": "SmallGNULinux",

"os": "GNULinux",

"compute": [ 2, 4 ],

"memory": [ 2048, 4096 ],

"storage": [ 10240 ],

"location": "eu",

"provides": [

{ "id": "SSHCapability" }

]

}

]


Artefact types

• Generic component of the application – a Java servlet of an application for document

collaboration

– a Jetty container

– a MongoDB database


Artefact types

• Deployment commands – retrieve the Java servlet from cloudml.org

– configure it

– run it

http://cloudml.org/


Artefact types

• Deployment dependencies – the Jetty container and the MongoDB database have

to be deployed before the Java servlet


Artefact types

• Communication channels – a Java servlet communicates with another Java

servlet through Hypertext Transfer Protocol Secure (HTTPS) on port 443


Artefact A Artefact B

Artefact C

Provided applicative capability

Communication channel

Required applicative capability

Provided deployment capability

Required deployment capability

Dependency

Resources (binaries, scripts, etc.)


Artefact type example (JSON) "artefactTypes": [

{

"id": "MongoDB",

"retrieval": "wget http://cloudml.org/services/mongodb.sh",

"deployment": "sudo mongodb.sh",

"provides": [

{ "id": "MongoDBCapability" }

]

},

…


Artefact type example (JSON) …

{

"id": "Jetty",

"retrieval": "wget http://cloudml.org/services/jetty.sh",

"deployment": "sudo jetty.sh",

"provides": [

{ "id": "JettyCapability" }

]

},

…


Artefact type example (JSON) …

{

"id": "Docs",

"retrieval": "wget http://cloudml.org/apps/docs.war; wget http://cloudml.org/apps/docs_configure.sh; wget http://cloudml.org/apps/docs_deploy.sh",

"configuration": "sudo docs_configure.sh",

"deployment": "sudo docs_deploy.sh",

"requires": [

{ "id": "JettyCapability" },

{ "id": "MongoDBCapability" }

]

}

]


Cloud Provider-Specific Model (CPSM)


CPSM

• Specific provisioning and deployment model that is dependent on the cloud provider


CPSM

• Specific provisioning and deployment model that is dependent on the cloud provider

• Consists of node instances and artefact instances


Node instance

• Instance of a virtual machine on a specific cloud provider – a virtual machine running GNU/Linux on Amazon EC2


Node instance example (JSON) "nodeInstances": [

{

"id": "aws1",

"type": "SmallGNULinux",

"provider": "aws-ec2",

"provides": [

{

"id": "ssh1",

"type": "SSHCapability"

}

]

}

]


Artefact instance

• Instance of a component of the application on a specific virtual machine – an instance of the Java servlet on the virtual

machine above

– an instance of the Jetty container on …

– an instance of the MongoDB database on …


Artefact instance example (JSON) "artefactInstances": [

{

"id": "mongodb1",

"type": "MongoDB",

"provides": [

{

"id": "mongodb1",

"type": "MongoDBCapability"

}

]

},

…


Artefact instance example (JSON) …

{

"id": "jetty1",

"type": "Jetty",

"provides": [

{

"id": "jetty1",

"type": "JettyCapability"

}

]

},

…


Artefact instance example (JSON) …

{

"id": "docs1",

"type": "Docs",

"destination": "aws1",

"requires": [

{ "id": "jetty1" },

{ "id": "mongodb1" }

]

}

]


Cloud Provider-Independent Model

JSON XMI …



Cloud Provider-Specific Model

Models@run-time

JSON XMI …




Models@run-time

Provisioning and Deployment

JSON XMI

jclouds

…

Cloudify …




Models@run-time


JSON XMI

jclouds

…

Cloudify

Amazon AWS

…

Rackspace …


Run-time


Models@run-time

• CPSM causally connected to the running system

• A change in the CPSM is reflected on-demand in the running system

• A change in the running system is automatically reflected in the CPSM


Models@run-time

Current CPSM


Models@run-time

Current CPSM

Reasoning


Models@run-time

Current CPSM

Reasoning Target CPSM


Models@run-time

Current CPSM

Reasoning Model Checking

Target CPSM


Models@run-time

Current CPSM

Target CPSM


Target CPSM


Models@run-time

Current CPSM

Target CPSM


Target CPSM

Diff


Models@run-time

Current CPSM Adaptation

Target CPSM


Target CPSM

Diff


Models@run-time


Current CPSM Adaptation

Target CPSM


Target CPSM

Diff


Provisioning and deployment

• Provisioning requirements

• Deployment commands

• Deployment dependencies

• Communication channels


Provisioning and deployment

• Provisioning requirements

• Deployment commands

• Deployment dependencies

• Communication channels

• Expressed with CloudML


Service-Level Agreement (SLA)

• Internal QoS requirements – compute load ≤ 90%

– memory load ≤ 90%

• External QoS requirements – response time ≤ 1s



• Internal QoS requirements – compute load ≤ 90%

– memory load ≤ 90%

• External QoS requirements – response time ≤ 1s

• Not expressed with CloudML



• Adaptation rules – if response time > 1s then scale out by provisioning a

new virtual machine

– if compute load ≤ 10% then scale down by deprovisioning an existing virtual machine



• Adaptation rules – if response time > 1s then scale out by provisioning a

new virtual machine

– if compute load ≤ 10% then scale down by deprovisioning an existing virtual machine

• Not expressed with CloudML, but enacted through CloudML


Reference

Nicolas Ferry, Alessandro Rossini, Franck Chauvel, Brice Morin, Arnor Solberg

Towards model-driven provisioning, deployment, monitoring, and adaptation of multi-cloud systems

In IEEE CLOUD 2013

To appear


Demo


Thank you!

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cloud modelling language (cloudml) · •scalability •performance •availability •cost . s...

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