Methods and systems of automatic confidence-controlled sampling to analyze, detect anomalies and problems in monitoring data and event messages generated by sources of a distributed computing system are described. A source can be virtual or physical object of the distributed computing system, a resource of the distributed computing system, or an event source running in the distributed computing. Monitoring data includes metric data generated by resources and data that represents meta-data properties of event sources. Confidence-controlled sampling is used to determine characteristics of the monitoring data, identify periodic patterns in the behavior of a source, detect changes in behavior of a source, and compare the behavior of two sources. Confidence-controlled sampling speeds up characterization the data sets, determination of behavior patterns, and detection and reporting of anomalies and problems of the resources and event sources of the distributed computing system.