Model-Driven Management of Docker Containers. Docker Containers Management with Model.

1. University of Lille & Inria Lille - Nord Europe (France)
Fawaz Paraïso | Stéphanie Challita | Yahya Al-Dhuraibi | Philippe Merle
9th International Conference on Cloud Computing(CLOUD 2016)
Model-Driven Management of
Docker Containers

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Model-Driven Management of Docker Containers
1 | Context

3. Jun 27- July 2, 2016 . San Francisco
Containers Technology
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Containers add
new efficiency to
Cloud Computing
Docker is the well know containers technology
Docker Adoption Is Not Without Concern …
Portability
low resource consumption
Lightweight

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Model-Driven Management of Docker Containers
2 | Challenges for Managing Docker
Containers

5. Jun 27- July 2, 2016 . San Francisco
A distributed Event Processing Application
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Word
Word
Count
Count
Count
Count
Rolling
Rolling
Ranking
Rolling
Ranking
Rolling

6. Jun 27- July 2, 2016 . San Francisco
Deployability of Application
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Deployment
Corrections
This operation can be repeated severals time
Resource consumed
Time consumed
Application
Runtime
Appli
Currently, with Docker there is no way to guarantee the deployability of application

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Challenges for Managing Docker Containers
1. Challenge 1: Lack of the verification
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Resources Management at Runtime
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Runtime
App
cpu
memory
…

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Challenges for Managing Docker Containers
1. Lack of the verification
2. Challenge 2: Resource management at runtime
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Synchronization between Design Time and Runtime
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Runtime
App
Design Time

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Challenges for Managing Docker Containers
1. Lack of the verification
2. Resources management at runtime
3. Challenge 3: Synchronization between design time and
runtime
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Inconsistency Use of Containers Across
Organizations
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The problem of:
Maintainability remains
Inconsistency
Swarm Compose

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Challenges for Managing Docker Containers
1. Lack of the verification
2. Resources management at runtime
3. Synchronization between design time and runtime
4. Challenge 4: Inconsistency use of containers across
organizations
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14. Jun 27- July 2, 2016 . San Francisco
Outline
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1.Context
2.Problem Statement
3.Our approach
4.Evaluation
5.Conclusion
6. Future Work

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Model-Driven Management of Docker Containers
3 | Our Approach

16. Jun 27- July 2, 2016 . San Francisco
Model-Driven Engineering (MDE)
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MDE = Abstraction + Automation
Model is an abstraction that enables to deal with complex reality in
simplified way
Automation is a model transformation that mutates on model to
another
Viewpoint V2
M2
Viewpoint V1
M1
Object Constraint Language (OCL)

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Our Approach
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Model-Driven Management of Docker Containers
Our solution is four phase model-driven tool
1. Analysis of consistency
2. Resource management at runtime
2. Synchronization of designed and deployed Containers
3. Design Tool

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Architecture Overview
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Docker
Model
Runtime
Legend:
Docker artifact
Model element
Connector
Generate artifacts
Update model elements
Connector

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Docker Model (1/2)
‣ In MDE everything is a model
➡Container, Link, Host,Volume, etc…
• All modeling artefacts in MDE are interrelated
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Transformations
DockerFile, compose, swarm
Validation
Design

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Docker Model (2/2)
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}[Merle et al. Cloud 2015]
{

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Docker Container Architectural Constraints
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Container-a
Container-b
This architecture will fail during its deployment due to
the cycle between containers
context Container inv NoCycleBetweenContainerLinks:
links->select(oclIsTypeOf(Link)).target->closure
(links->select(oclIsTypeOf(Link)).target)->excludes(self)
OCL constraint

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Synchronization
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Docker
Model
Runtime
Connector
Two way synchronization

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Connecting Docker Model Online
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Docker
Model
Runtime
Detect changes Connector
DESIGN TIMERUNTIME
Model
Model
update
Change
Detection
Monitoring

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Design Tool
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Available here: http://tinyurl.com/occiware

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Model-Driven Management of Docker Containers
4 | Evaluation

26. Jun 27- July 2, 2016 . San Francisco
Use Case
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Storm
topology
ranking bolt
rolling count rolling count
count count count
word spout 1 word spout 2
20 VMs with 8 Docker containers
deployed on a private Cloud

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Overhead
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Create action Avg. start time Docker Model Overhead
Docker 168.509 sec -
Docker with Model 170.382 sec 1,11 %
Start action Avg. start time Docker Model Overhead
Docker 5.033 sec -
Docker with Model 5.04 sec 2,1 %
Stop action Avg. start time Docker Model Overhead
Docker 84.12 sec -
Docker with Model 86.01 sec 2,25 %
Container creation time
Container starting time
Container stopping time
The experiment shows that the
overhead introduced by Docker Model
is negligible regarding all advantages
provided by our approach
8 containers were used to perform
this evaluation

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Scalability of Docker Model at Runtime
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Total of 50,000 containers
where generated. For each
generation, the model
performs creation and
update actions.
The average time taken to
generate 50 containers is 14.30
seconds

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Model-Driven Management of Docker Containers
5 | Conclusion

30. Jun 27- July 2, 2016 . San Francisco
Conclusion
Presented an ongoing Model-Driven Management of
Docker Containers
MDE tooling enables to design, reason, and deploy
containers
Our approach provides to the users the possibility to
verify the deployability of Docker containers at design time
Tested our approach on a representative application
scenario and deployed it to cloud
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Model-Driven Management of Docker Containers
6 | Future Work

32. Jun 27- July 2, 2016 . San Francisco
Future Work
Investigate the adaptation of managed containers as a
set of atomic changes
Extended our approach to other container solutions
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33. Questions & comments
University of Lille & Inria Lille - Nord Europe (France)
Thank you!
http://occiware.org
Fawaz Paraïso : fawaz.paraiso@inria.fr