Abstract: Mechanisms are provided for determining threshold conditions for performing operations within a performance monitoring tool. Metric data is collected from a computing system environment and clustering analysis is performed on the metric data to generate a plurality of clusters. One or more candidate clusters are selected that are candidate clusters for generating a threshold condition for performance monitoring. At least one threshold condition for performance monitoring is generated based on a composition of the selected one or more candidate clusters. The at least one threshold condition is then applied to future performance metric data to determine whether to perform an operation in response to the future performance metric data meeting or not meeting the at least one threshold condition.

Abstract: Mechanisms are provided for determining threshold conditions for performing operations within a performance monitoring tool. Metric data is collected from a computing system environment and clustering analysis is performed on the metric data to generate a plurality of clusters. One or more candidate clusters are selected that are candidate clusters for generating a threshold condition for performance monitoring. At least one threshold condition for performance monitoring is generated based on a composition of the selected one or more candidate clusters. The at least one threshold condition is then applied to future performance metric data to determine whether to perform an operation in response to the future performance metric data meeting or not meeting the at least one threshold condition.