Nixer CyberML is made up from User Event Storage, ML Analytics services and open source Java Spring plug-ins, all based on the flexible and developer-extendable Nixer CyberML architecture

The Nixer CyberML architecture merges visibility and control with machine-learning algorithms. It’s design allows HTTP traffic to be labelled efficiently and triggers application behaviours based on traffic characteristics.
Rule engine and machine-learning algorithms that learn from application events such as an application user action or a login provide rich context for decision processes.


Machine-learning and event storage is generally kept in the cloud due to the elastic storage requirements
for large numbers of user events, and the processing workload of the algorithms. However in Release 1 there is localised in-application storage and processing for some limited capabilities, to allow Spring developers to see the architecture in action end-to-end.

The easiest way to understand how Nixer CyberML works is to clone it from Github and read the code.