Methods and systems for system maintenance include identifying patterns in heterogeneous logs. Predictive features are extracted from a set of input logs based on the identified patterns. It is determined that the predictive features indicate a future system failure using a first model. A second model is trained, based on a target sample from the predictive features and based on weights associated with a distance between the target sample and a set of samples from the predictive features, to identify one or more parameters of the second model associated with the future system failure. A system maintenance action is performed in accordance with the identified one or more parameters.