I'm trying to create an SLO definition based on the number of fast and slow key requests, WITHOUT the need to create a custom metric for slow requests.
My idea was to define the SLO as:
100* (number of slow key requests / number of total requests)
nothing special, really.
I could create a custom service metric for the keyrequest that counts the number of requests that exceed a certain response time. But could this be done without that step, just with metric queries?
I thought of this metric query:
builtin:service.keyRequest.response.time
:filter(
<filter for my key request goes here>
)
:avg
:partition(
"time",
value(fast,lt(300000)),
value(slow,otherwise)
)
:splitBy("time")
:filter(eq("time","fast"))
:count
:fold(sum)
The idea was to use partition as a way to get the metric data points above and below a certain slow/fast level and then use count to calculate the number of datapoints and use those in the SLO definition: 100*(slow/fast).
(it wouldn't be perfectly accurate due to aggregation, but it should work for the SLO)
The metric partitioning works:
but I'm struggling in "counting" the number of metric points required for the SLO calculation.
Any ideas how this could be achieved?
