High Availability of Big-Geo-Data as a Platform as a Service

There are ever-increasing challenges in the development of spatial data. The data increase rises continuously. The sharp rise in these information collections more and more data storage is required. Furthermore, should the systems have high availability and provide acceptable response time under load. The fulfillment of such requirement can be limited realized with a simple client / server system, since these do not scale well and act slowly in poor conditions. Therefore, more and more applications are deployed in the cloud as a service. This brings many benefits; inter alia, improving the availability and scalability of services. In this work the design decisions is demonstrated using an existing server system that are necessary for the realization of the product in the cloud. This product is then provided as a "Platform as a Service". Here points are as discussed persistence in distributed systems and cloud API design. This is then tested in a distributed system and compared against a simple client / server system. Also, a model is presented, thus the availability of the system is calculated