Hi All,
I am trying to predict cpu utilization of servers using Machine learning toolkit app of splunk, during the use of this app i found "predict numeric field" showcase using Linear regression algorithm was doing perfect prediction for the given field but it cannot be used for forecasting the same
I tried merging splunk queries of Linear regression and Kalman filter to forecast the Predicted field, is this approach correct ?
Find below Query i used for the same and let me know your thoughts and suggesstions.
I am trying this because i am not sure about the prediction results of only kalman filter.
index=main sourcetype=cpumetric metric_name=CPUUtilization Environment="WEB" Average>2.00
| apply "Predict_CPUUtilization"
| table _time, "Average", "predicted(Average)" | rename predicted(Average) as Avrg | timechart span=15m avg(Avrg)
| predict "avg(Avrg)" as prediction algorithm="LLP5" future_timespan="3" holdback="0" lower"50"=lower"50" upper"50"=upper"50"
| `forecastviz(3, 0, "avg(Avrg)", 50)
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