The Cloud-computing paradigm advocates the use of re- sources available “in the clouds”. In front of the multiplicity of cloud providers, it becomes cumbersome to manually tackle this heterogene- ity. In this paper, we propose to define an abstraction layer used to model resources available in the clouds. This cloud modelling language (CloudML) allows cloud users to focus on their needs, i.e., the modelling the resources they expect to retrieve in the clouds. An automated provi- sioning engine is then used to automatically analyse these requirements and actually provision resources in clouds. The approach is implemented, and was experimented on prototypical examples to provision resources in major public clouds (e.g., Amazon EC2 and Rackspace).

1. Toward CloudML, a Model-Based Approach
to Provision Resources in the Clouds
Eirik Brandtzæg1,2, Sébastien Mosser1, Parastoo Mohagheghi1
(1) SINTEF IKT, NSS Department, MOD group, Oslo, Norway
(2) University of Oslo, Oslo, Norway
First International Workshop on Model-Driven Engineering on and for the Cloud
Co-located with ECMFA’12
02.07.2012, Copenhagen, Denmark

2. Cloud-Computing: From Ads ...
«Much like plugging in a microwave in order
to power it doesn’t require any knowledge of
electricity, one should be able to plug in an
application to the cloud in order to receive
the power it needs to run, just like a utility.»
2
http://jineshvaria.s3.amazonaws.com/public/cloudbestpractices-jvaria.pdf

3. ... To Reality!
«However, we are not there yet.»
3
http://jineshvaria.s3.amazonaws.com/public/cloudbestpractices-jvaria.pdf

4. Outline
The REMICS project
Motivations
CloudML Artefacts
Conclusions & Perspectives
(c) bschwehn

5. (c) saidoe
The REMICS project Migrating to the Cloud

6. 
From «Legacy» to «the Cloud»

Legacy
  Cloud

System
6

7. Focus: Infrastucture as a Service
Resource Cloud
7

8. Migration: Code to UML Extraction
soaML
Legacy
System
8

9. Migration: Code to UML Extraction
soaML
Legacy Cloud ??
System
8

10. Motivations:
even on a simple example ...
Resource Booking

11. A Single Application ...
business logic
...
database server
E.g., the «usual» BankManager system 10

12. ... But Several Topologies to Support It!
APP DB APP DB
Test / Dev Independent VMs
APP
APP DB default > Disk
> RAM >> RAM
APP
Load-balanced 11

13. Challenges
Complexity
Run-time
Shareable
???
Multi-Cloud
Robustness
Reproducibility
12

14. CloudML:
Eirik Brandtzæg’s MSc Thesis
Meta-model & Engine

15. Envisioned Approach
design
Application
business expert
Topology1 ... Topologyn
Template1 ... Templaten
cloud expert
CloudML Engine
exec
cloud user models@run.time 14

16. 15

17. CloudML Template language
{
"name": "MyTemplate",
"nodes": [{
"name": "AppNode", "minCores": 2,
"locationId": "us-east-1a"
}, {
"name": "DatabaseNode",
"minDisk": 4000
"locationId": "ap-southeast-1a",
}]
}
16

18. Asynchronous
booking
models@run.time
17

19. Involved Modules
18

20. Implementation & Tool Support
Textual syntax JSON
Modularity
Multi-cloud
Asynchronous booking
models@run.time
https://github.com/eirikb/cloudml-engine 19

21. Conclusions & Perspectives

22. Conclusions
• CloudML:
• Meta-model to reify resources available in the clouds
• Models@run.time approach to interact with the provisioned ressources
• Tool support:
• Engine available as a turn-key Maven artefact
• Open source (LGPL): code available on GitHub
21

23. Perspectives
• Strengthen validation of the CloudML artefacts:
• Engine: Empirical results (Amazon Research Grant, $25.000)
• Meta-model: REMICS case studies (e.g., e-Science, Tourism, Banking)
• Complete Modelling of Cloud Applications + Tool Support:
• EU funded projects (Call 8): MODAClouds, PaaSage, Broker@Cloud
• Automated deployment already sketched with Eirik’s MSc thesis
Eirik Brandtzæg, Mohagheghi Parastoo, Sébastien Mosser. “Towards a Domain-
Specific Language to Deploy Applications in the Clouds” in Proceedings of the Third
International Conference on Cloud Computing, GRIDs, and Virtualisation (CLOUD
COMPUTING'12), Nice, 22-27 july 2012. 22

24. Thanks for your attention!
Toward CloudML, a Model-Based Approach
to Provision Resources in the Clouds
Eirik Brandtzæg, Sébastien Mosser, Parastoo Mohagheghi