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Various scientific and commercial applications require automated scalability and orchestration on cloud computing resources. However, extending applications with such automated scalability on an individual basis is not feasible. This paper investigates how such automated orchestration can be added to cloud applications without major reengineering of the application code. We suggest a generic architecture for an application level cloud orchestration framework, called MiCADO that supports various application scenarios on multiple heterogeneous federated clouds. Besides the generic architecture description, the paper also presents the first MiCADO reference implementation, and explains how the scalability of the Data Avenue service that is applied for data transfer in WS-PGRADE/gUSE based science gateways, can be improved. Performance evaluation of the implemented scalability based on up and downscaling experiments is presented.

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So far BOINC based desktop Grid systems have been applied at the global computing level. This paper describes an extended version of BOINC called SZTAKI Desktop Grid (SZDG) that aims at using Desktop Grids (DGs) at local (enterprise/institution) level. The novelty of SZDG is that it enables the hierarchical organisation of local DGs, i.e., clients of a DG can be DGs at a lower level that can take work units from their higher level DG server. More than that, even clusters can be connected at the client level and hence work units can contain complete MPI programs to be run on the client clusters. In order to easily create Master/Worker type DG applications a new API, called as the DC-API has been developed. SZDG and DC-API has been successfully applied both at the global and local level, both in academic institutions and in companies to solve problems requiring large computing power.

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Automated deployment and run-time management of microservices-based applications in cloud computing environments is relatively well studied with several mature solutions. However, managing such applications and tasks in the cloud-to-edge continuum is far from trivial, with no robust, production-level solutions currently available. This paper presents our first attempt to extend an application-level cloud orchestration framework called MiCADO to utilise edge and fog worker nodes. The paper illustrates how MiCADO-Edge can automatically deploy complex sets of interconnected microservices in such multi-layered cloud-to-edge environments. Additionally, it shows how monitoring information can be collected from such services and how complex, user- defined run-time management policies can be enforced on application components running at any layer of the architecture. The implemented solution is demonstrated and evaluated using two realistic case studies from the areas of video processing and secure healthcare data analysis.