Time series anomaly detection with rare event failure prediction

A method, comprising:

• determining, by a device comprising a processor and using a first machine learning model, a location of a data anomaly within sequential data;
• and
• determining, by the device and using a second machine learning model that is not the first machine learning model, whether a probability of a future failure event is at least a threshold probability based on the data anomaly and the sequential data.

A non-transitory machine-readable medium comprising computer executable instructions that, when executed by a processor, facilitate performance of operations, the operations comprising:

• determining, using a first machine learning model, a location of an anomalous sample within a data sequence;
• and
• determining, using a second machine learning model that is not the first machine learning model, that a probability of a future disruptive event is at least a threshold probability based on the location of the anomalous sample and the data sequence.