The diversity in the way different cloud providers offer their services, give their SLAs, present their QoS, support different technologies, etc., complicates the portability and interoperability of cloud applications, and favors vendor lockin. Standards like TOSCA, and tools supporting them, have come to help in the provider-independent description of cloud applications. After the variety of proposed cross-cloud application management tools, we propose going one step further in the unification of cloud services with a deployment tool in which IaaS and PaaS services are integrated into a unified interface. We provide support for applications whose components are to be deployed on different providers, indistinctly using IaaS and PaaS services. The TOSCA standard is used to define a portable model describing the topology of the cloud applications and the required resources in an agnostic, and providers- and resources-independent way. We include in this paper some highlights on our implementation on Apache Brooklyn and present a non-trivial example that illustrates our approach.

Cloud Computing providers offer diverse services and capabilities, which can be used by end-users to compose heterogeneous contexts of multiple cloud platforms to deploy their applications, in accordance with the best offered capabilities. However, this is an ideal scenario, since cloud platforms are being conducted in an isolated way by presenting interoperability and portability restrictions. Each provider defines its own API, non-functional requirements, QoS, add-ons, etc., and developers are often locked-in a concrete cloud environment, hampering the integration of heterogeneous provider services to achieve cross-deployment. This work presents an approach to deploy cross-cloud applications by using standardisation efforts of design, management and deployment of cloud applications. Specifically, using mechanisms specified by the TOSCA and CAMP standards, we propose a methodology to describe the topology and distribution of modules of a cloud application and to deploy the inter-connected modules over heterogeneous clouds. We present our prototype TOMAT, which supports the automatic distribution of cloud applications over multiple providers.

The adaptive management of complex applications deployed across multiple heterogeneous PaaS platforms is one of the problems that have emerged with the cloud revolution. The ongoing EU research project SeaClouds aims at providing seamless adaptive multi-cloud management of complex applications by supporting the distribution, monitoring and migration of application modules over multiple heterogeneous PaaS platforms. In this paper we present context, motivations and objectives of SeaClouds, its relation with other cloud initiatives, and its initial architecture.

Cloud computing promises easy access, low entry cost and elasticity. However, elastic service provisioning \nis usually delivered via service replication, which must be supervised manually, hand-picking the services \nto replicate and ensuring their proper load balance. Automated service provisioning, i.e., the function of \nautomatically scaling the services to cope up with their runtime demand, is a research challenge in cloud \ncomputing. In this work, we include such scalability analysis early in its development cycle, right at the design \nstage. We propose a model-driven approach where various QoS parameters can be simulated and analyzed \nusing the e-Motions tool. Additionally, the model is automatically transformed to fit the given throughput \nrequirements by replicating the services which cause the bottleneck. In order to evaluate the proposal, we \npresent some initial experimental results run over the e-Motions tool.

Adaptation is of utmost importance in systems developed by assembling reusable software services accessed through their public interfaces. This process aims at solving, as automatically as possible, mismatch cases which may be given at the different interoperability levels among interfaces by synthesizing a mediating adaptor. In this paper, we present a toolbox that fully supports the adaptation process, including: (i) different methods to construct adaptation contracts involving several services; (ii) simulation and verification techniques which help to identify and correct erroneous behaviours or deadlocking executions; and (iii) techniques for the generation of centralized or distributed adaptor protocols based on the aforementioned contracts. Our toolbox relates our models with implementation platforms, starting with the automatic extraction of behavioural models from existing interface descriptions, until the final adaptor implementation is generated for the target platform.