International audienceWith 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

Abstract. Open Cloud Computing Interface (OCCI) is the only open standard for managing any kinds of cloud resources, e.g., Infrastructure as a Service, Platform as a Service, and Software as a Service. However, no model-driven tooling exists to assist OCCI users in designing, editing, validating, generating, and managing OCCI artifacts (i.e., extensions that represent specific application domains and configurations that define running systems). In this paper, we propose the first model-driven tool chain for OCCI called OCCIware Studio. This tool chain is based on a metamodel defining the static semantics for the OCCI standard in Ecore and OCL. OCCIware Studio provides OCCI users facilities for designing, editing, validating, generating, and managing OCCI artifacts. We detail the tooled process to define an OCCI extension. In addition, we show how the cloud user can leverage the generated tooling for this extension to create his own OCCI configurations and manage them in the cloud. We illustrate our paper with the OCCI Infrastructure extension defining OCCI-compliant compute, network, and storage resources.

Abstract:To tackle the cloud-provider lock-in, the Open Grid Forum (OGF) is developing the Open Cloud Computing Interface (OCCI), a standardized interface for managing any kind of cloud resources. Besides the OCCI Core model, which defines the basic modeling elements for cloud resources, the OGF also defines extensions that reflect the requirements of different cloud service levels, such as IaaS and PaaS. However, so far the OCCI PaaS extension is very coarse grained and lacks of supporting use cases and implementations. Especially, it does not define how the components of the application itself can be managed. In this paper, we present a model-driven framework that extends the OCCI PaaS extension and is able to use different configuration management tools to manage the whole lifecycle of cloud applications. We demonstrate the feasibility of the approach by presenting four different use cases and prototypical implementations for three different configuration management tools.