Dynamic threshold adjustment based on performance trend data

Abstract

The present disclosure includes analyzing client instance performance trends to predict future client instance performance and adjusting thresholds used to send resource utilization alerts based on analyzing the client instance performance trends. In particular, a data center providing a platform as a service includes a database that stores performance data associated with client instances. The data center also includes alignment logic that temporally aligns the performance data, and a frequency based filter that compresses the aligned performance data based on frequency of values. The data center further includes dynamic threshold adjustment logic that adjusts thresholds associated with sending performance trend alerts based on analyzing the compressed set of performance data. In this manner, the thresholds may be dynamically adjusted for changing circumstances and/or relevant details associated with resource usage, and thus may more accurately send performance trend alerts indicative of situations when resource utilization becomes high and resources become low.