1. A method implemented by one or more processing devices, the method comprising: obtaining a data set for one or more data centers; receiving a diagnostic level selection from a user, the diagnostic level selection being used to tune a magnitude of performance anomalies in the data set to an amount of computational resources allotted to identifying the performance anomalies; using the allotted amount of the computational resources, identifying the performance anomalies in the data set that have anomaly scores within the diagnostic level selection; determining predicates for the identified performance anomalies; generating a ranked list of the predicates based at least in part on the anomaly scores; and causing at least one of the predicates of the ranked list to be presented.