Abstract: Methods, systems, and computer readable media for emulating and testing data flows in distributed computing systems. An example system includes a workload abstractor configured for receiving monitored traffic in a distributed computing system performing a machine learning task and generating, using the monitored traffic, a test environment-agnostic workload model for the machine learning task and storing the test environment-agnostic workload model in a workload model repository with one or more other workload models. The system includes a test controller configured for selecting a test case for the machine learning task and a testbed mode for the test case; executing the test case by translating the test environment-agnostic workload model into a testbed-specific workload model for the testbed mode; and reporting, based on executing the test case, one or more performance metrics for the machine learning task.