We propose a novel technology to leverage rapidly evolving cloud based infrastructure to improve time constrained situational awareness for real-time decision making. Our "CloudTurbine" innovation eliminates the distinction between files and streams to distribute live streaming sensor and video data over cloud file sharing services. Streaming and static data have long been considered separately, with unique mechanisms for data transmittal and viewing of each. Files are the greatest common denominator linking static data across all computers. However, real-time streaming data distribution is widely presumed to be sensor-centric; i.e. up-front requirements to "keep up" with live data trump all other considerations. A great unification of cloud based services for static data has recently occurred. There are now many providers of "file sharing" cloud based services. The paradigm for all is simple: (1) put data in a local file folder, (2) it automatically shows up at other linked systems via a cloud service. Wouldn't it be nice if one could unify an approach to streaming data that leveraged this file-sharing cloud infrastructure? That is precisely what we propose. Building upon a functional prototype, we propose to characterize, evaluate, refine and adapt CloudTurbine technology to NASA and commercial applications. CloudTurbine is a streaming data interface to and from standard file sharing cloud services. It delegates much of the data transmittal, security, and server resources to the cloud service provider. It provides robust continuous streaming for high data and frame rates while trading off manageable amounts of delivery latency (on the order of seconds). In so doing, it eliminates the distinction between files and streams, and enables a simple, cost effective new paradigm for streaming data middleware.