Model-Driven Management of Docker Containers

Fawaz Paraiso (1) , Stéphanie Challita (1) , Yahya Al-Dhuraibi (1) , Philippe Merle (1)

1 SPIRALS - Self-adaptation for distributed services and large software systems

With the emergence of Docker, it becomes easier to encapsulate applications and their dependencies into lightweight Linux containers and make them available to the world by deploying them in the cloud. Compared to hypervisor-based virtualization approaches, the use of containers provides faster start-ups times and reduces the consumption of computer resources. However, Docker lacks of deployability verification tool for containers at design time. Currently, the only way to be sure that the designed containers will execute well is to test them in a running system. If errors occur, a correction is made but this operation can be repeated several times before the deployment becomes operational. Docker does not provide a solution to increase or decrease the size of container resources in demand. Besides the deployment of containers, Docker lacks of synchronization between the designed containers and those deployed. Moreover, container management with Docker is done at low level, and therefore requires users to focus on low level system issues. In this paper we focus on these issues related to the management of Docker containers. In particular, we propose an approach for modeling Docker containers. We provide tooling to ensure the deployability and the management of Docker containers. We illustrate our proposal using an event processing application and show how our solution provides a significantly better compromise between performance and development costs than the basic Docker container solution.

Mots clés: Model Driven Engineering; Docker; Cloud Computing; Container; Models@runtime

Domaines: Génie logiciel [cs.SE]

Fawaz Paraiso, Stéphanie Challita, Yahya Al-Dhuraibi, Philippe Merle. Model-Driven Management of Docker Containers. 9th IEEE International Conference on Cloud Computing (CLOUD), Jun 2016, San Francisco, United States. pp.718 - 725, ⟨10.1109/CLOUD.2016.0100⟩. ⟨hal-01314827⟩