As data volumes continue to grow there is a need to move processing not only closer to the source of the data but also closer in time to when the data are created. This style of processing data as it streams off the telescope leads to data pipelines that need to focus on throughput. Bifrost is an open-source, modular C++/CUDA/Python framework that is intended to make building reliable, high-performance data capture and analysis pipelines such as this easier. In this talk I will discuss Bifrost and its core concepts of ring memory spaces and blocks how they are used for CPU and GPU computing. I will also discuss use cases for Bifrost by providing examples of instruments that are currently using or investigating using the framework. Finally, future development plans and directions for the framework will be presented.