1. An application failure prediction system comprising: a processor; and a non-transitory data storage comprising machine-readable instructions that cause the processor to: receive for a time interval, real-time data associated with a first application executing on a computing apparatus; analyze the real-time data using a first predictive data model to identify a plurality of anomalies within the real-time data, each of the plurality of anomalies represents a corresponding potential application failure; determine respective anomaly scores for the plurality of anomalies based on the analysis; compare each of the respective anomaly scores with a threshold predetermined within the first predictive data model; indicate high probabilities for occurrence of the corresponding potential application failures for high-scoring anomalies of the plurality of anomalies, the high-scoring anomalies having the respective anomaly scores greater than the threshold; and implement a first set of corrective actions for the high-scoring anomalies.