1. A method, comprising: performing, by one or more computing devices: classifying, based at least in part on a first statistical analysis, one or more performance metric collections corresponding to an observation period of an executing process into a first set of metrics representing one or more sub-periods during which a workload of the executing process exhibited a change trend, and a second set of metrics representing one or more sub-periods during which the workload did not exhibit a change trend; grouping, based at least in part on a second statistical analysis, the second set of metrics into one or more metric clusters, wherein each metric cluster of the one or more metric clusters represents a respective statistically stable workload level; detecting, based at least in part on a third statistical analysis of a particular performance metric corresponding to the one or more metric clusters, whether an upward trend in memory usage at the executing process during the observation time period is indicated; and in response to detecting that an upward trend in memory usage at the executing process during the observation time period is indicated, providing a notification of a potential memory leak at the executing process.