Model based control for multi-cloud applications

The advent of cloud computing has offered to developers a new appealing paradigm to deploy their applications without capital investments. Resources can now be acquired on-demand in a flexible, scalable and rapid way. However, cloud providers lack of native mechanisms to guarantee the Quality of Service required by specific application domains. High availability can be achieved by replication of critical components. Since outages could affect the entire cloud provider, replication can be effective only by using multiple providers. In this paper we tackle the above problem and present an approach to guarantee availability requirements of cloud-based applications by exploiting replication on multiple clouds to reduce unavailability, still limiting costs. More precisely, we propose: i) an approach to model, at design time, the application, its availability requirements and the characteristics of the used clouds, and ii) a self-adaptive technique responsible, at runtime, of both in-cloud scaling policies and traffic routing among different cloud providers, by means of a control-theoretical approach. We integrated the modeling approach in the Palladio Bench IDE and developed a runtime self-adaptation controller in Matlab. The controller has been evaluated against different workload conditions, costs variations and service failures in simulated scenarios. The controller has been able to provide the desired availability minimizing costs.