MEASURING AFFINITY BANDS FOR PRO-ACTIVE PERFORMANCE MANAGEMENT

摘要

A computer implemented system and method for pro-active application monitoring and alerting using affinity band. To enable pro-active monitoring, the present invention may derive affinity band. The invention accesses performance data generated from monitoring an application associated with one or more transaction and configuring iteration period to derive affinity band. The method provides configuring an interval within iteration period whereby all performance metric values may be aggregated and deriving affinity band for each of the performance metrics. The affinity band may then be used as benchmark or threshold to monitor current values for each of the performance metrics. Alerts may be raised through pro-active monitoring mechanism when the current values of the performance metric go beyond the threshold set, displaying a tendency to rise or go beyond normal values with extent of deviation.

主权项

1. A computer implemented method for pro-active application monitoring and alerting using affinity band, comprising:
accessing performance data generated from monitoring an application; configuring an interval within the iteration period wherein performance metric values are aggregated; deriving affinity band for each of the aggregated performance metric values using a response time of one or more transactions, wherein the affinity band is derived by a method consisting of steps:
determining individual data values of application response times;determining a lowest data value and a highest data value of application response times for a unit period;sorting the lowest data value and the highest data value by dropping a predefined percentage from the lowest data value and highest data value;determining average of the lowest data value and the highest data value;dividing the average interval of the lowest data value and the highest data value into predefined equal parts;using each of the equal parts for response time bucketing;classifying the response time data into buckets;identifying a frequency of response time for each of the intervals;providing response time distribution along with the affinity band;calculating affinity mean by removing predefined percentage of the lowest data value and the highest data value of the response time for the unit period;determining an average and a standard deviation of the remaining mid data values for the unit period;determining a lower and an upper range of the affinity band using the average and the standard deviation; monitoring current values for each of the performance metric values using the affinity band as a threshold; raising an alert when the current values of the performance metric values go beyond the threshold.