Software-defined radio (SDR) is used for R&D such as cognitive radio. Because sampling devices and personal computers configuring the SDR environment have fixed configurations, some reconfiguration is needed when the SDR application requires different data sources and computational resources. To enable reconfiguration, we present a cloud platform that has scalable computing resources and data sources deployed over a wide area. We use the existing SDR development environment (SDRDE) and implement it on the cloud platform. It is necessary to transfer the SDR environment to the cloud by separating the UI and data management from the existing SDRDE. In this study, we selected the GNU Radio Companion (GRC) as the base platform and implemented an SDRDE for an unspecified number of users by separating the UI. In addition, we used task parallel and distributed computing for the SDR application. In this study, we focus on compatibility with the base implementation and lifting the limits of computational resources. We confirmed the compatibility with GRC in terms of user skill sets and software assets and evaluated the system response time. Further, the relationship between CPU utilization and instructions per cycle during SDR application execution shows that in general, this approach is effective.