Patent ID: 8661299

Claim:
A computer-implemented method for detecting abnormalities in time-series data from an online professional network, the method comprising: receiving the time-series data, including at least one of throughput measurements and latency measurements associated with requests made to a back-end system associated with the online professional network; during a transitory startup period for the online professional network, detecting a start of a plain associated with steady-state behavior for requests made to the back-end system by, using a multi-degree polynomial to compute a best-fit line for throughput measurements for requests made to the backend system, and if an increase in throughput as indicated by the best-fit line falls below a threshold value, determining that the plain associated with steady state behavior has started; after the plain associated with steady state behavior has started, attempting to detect an abnormality by examining data points in the plain and looking for a deviation from the best-fit line; and upon detecting an abnormality in the time-series data in the plain, looking up associated system metrics which are temporally proximate to the abnormality, and generating a notification about the abnormality along with the associated system metrics to facilitate determining a root cause of the abnormality.