1. A method comprising: implementing a real-time event processing engine on a distributed data processing platform, wherein the real-time event processing engine is configured to process an unbounded stream of event data to detect a plurality of network security-related issues and/or to train a machine learning model; implementing a batch event processing engine on the distributed data processing platform, wherein the batch event processing engine is configured to process a batch of historic event data to detect a plurality of network security-related issues and/or to train a machine learning model; and enabling the real-time event processing engine and the batch event processing engine to share a model state of a particular machine learning model, the particular machine learning model being configured to process a time slice of data to produce a score for detecting a network security-related issue, wherein the real-time event processing engine and the batch event processing engine each utilize the shared model state to share, with the other engine, network security-related knowledge gained from processing one's respective data.