Systems and methods for scaling computational-workflows to disparate execution engines via engine-agnostic computational-workflow engine recommendations

Abstract

In some embodiments, reducing usage of computational resources associated with scaling computational-workflows to disparate execution engines via engine-agnostic computational-workflow engine recommendations may be facilitated. In some embodiments, the system receives a computational-workflow configured to execute within a first computational-workflow environment. The system then determines a set of operational dependencies for the computational workflow. The system then generates a feature vector comprising the set of operational dependencies to be inputted into a machine learning model configured to generate a first recommendation indicating a second computational-workflow environment to execute the first computational-workflow. The system may receive the first recommendation from the machine learning model, and deploy the first computational-workflow within the second computational-workflow environment.