Currently, cloud computing is a topic that is widely discussed in literature and in practice. The establishment of cloud computing brings along several chances, but at the same time confronts the operators of computing centers with difficult tasks: whereas for the user, the operation of software and the infrastructure required for this operation are highly simplified, computing centers, which offer the cloud-services, have to master the challenges of cloud computing. This concerns for example the availability of cloud-services of almost 100%, combined with high performance. 

For the operation of Very Large Business Applications (VLBA) based on cloud computing, further challenges arise since VLBA are highly complex and heterogeneous systems. A certain partial aspect of the operation of cloud-based VLBA is load balancing within a computing center/within computing centers which are responsible for the operation. Load balancing is exacerbated by the complex structure of the VLBA-cloud one the one hand, and by the provision of functionalities as services on the other hand. Especially the decoupling of services and systems leads to a state in which important classification numbers for the workload of the servers cannot be determined by the service. 

In the context of this project, an approach is meant to be developed with the help of which the workload within a (cloud-) system landscape can be determined and, based on this, an efficient load balancing on the basis of suitable alogrithms and other components can be conducted.