:-) this is a very common problem. Your data is dynamic, and I’ll be surprised if Prometheus has anything built in to deal with it (would be wonderful if it has though )
You need something more sophisticated than a fixed threshold. Normally these type of algorithms are classified under anomaly detection. These algorithms will analyze your past data to deduce alert threshold for the moment dynamically based on historical values. your data has trend (slowly increasing ) and seasonality (those two repeated peaks ), and a suitable algorithm will decompose (time series decomposition ) to extract those patterns and then compute the threshold at any given time based on those. There are limits to these type f algorithms , so you have to tune /choose based on your specific use case.
I’m curious if there’s any easy way to do this with Prometheus, let’s see what others say