Earth Observation applications are benefiting from a constantly growing amount of data from satellites. The company Vista is facing the challenge to exploit the available remote sensing data, making use of sophisticated algorithms that demand high computing power for a growing number of customers and thus increasing areas. In the presented use case a Docker image containing all the needed software for pre-processing of Sentinel-2 data has been build. This image is performing an atmospheric correction, computation of cloud and cloud shadow geometry, specific methods of radiative transfer modelling for classification and vegetation parameter retrieval of one satellite image. A Kubernetes cluster consisting of 10 worker nodes, each equipped with 32 CPUs and 64 GB of RAM, has been set up on the Telekom Cloud. A master node is performing the job management of the whole cluster, allowing easy distribution and orchestration of jobs. In the described set-up, the whole processing power of 320 Cores and 640 GB of RAM can be accessed, which could also easily be further extended. Accessing the whole processing power of the cluster, 700 Sentinel-2 scenes with a total of 3 TB storage needed are processed simultaneously within 24 hours delivering the basis for downstream products.