How to select time series data with "average value" <= threshold

[chuanjia xing]

Hi there,

     I think my question is pretty common but looks like I can't find the answer to it. 

     The problem I am trying to solve is: Let's say I have 100 metrics data for cpuutilization for my instance. Each one is a time series for 1 day with granularity of 1 min. So each one has 1,440 data point. 

       Now I want to select the instances which has an "average cpu utilization" <= 10% for one day. How should I do this, basically how should I calculate the "average cpu utilization" for one time series? 

        One way I am thinking to do is, for each time series, I find the p90 data point and check if it is <= 10%. If it is, then I'll say that this instance data is with "average cpu utilization" <= 10% and select it. But looks like there's no function in Prometheus for me to find the p90 for a time series, or I just didn't find the right function for it.

         So, is above the right way to select? If yes, how can I find the p90 for a time series? If not, then how should I solve this problem?

Thanks,

[Ben Kochie]

You want to use one of the "over time" functions.

avg_over_time(cpu_utilization[1d]) < 0.10

quantile_over_time(0.9 cpu_utilization[1d]) < 0.10

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[chuanjia xing]

Thanks for your reply! I tried to use avg_over_time and quantile_over_time, these 2 functions will still return a time series data based on the cpu_utilization data. So if I apply "< 0.10" on it, it will still return the data points which are < 0.1. 

This 2 functions are helpful, but still I didn't get the result I need. For example, I apply these 2 functions for the cpu utilization data on 4/1/2021, I still get a time series for it. How can I determine if the "cpu utilization on 4/1/2021 is above or below 20%"?