Hi! Thank your for the project :)
I found myself missing an implementation of the Summary metric, so decided to file an issue in case anyone (maybe myself) decides to contribute an implementation.
Open Metrics spec defines a metric type that computes quantiles locally on the client: Summary.
It's quite useful if you want to learn/discover how a system behaves, especially if you don't have much data a-priori. In that sense, Summary is dual to Histogram - both can be used to understand data distribution (e.g. latency data), but with different use-cases and tradeoffs.
Good overview on the differences between Summary and Histogram metrics is given in Prometheus doc https://prometheus.io/docs/practices/histograms/
Hi! Thank your for the project :)
I found myself missing an implementation of the Summary metric, so decided to file an issue in case anyone (maybe myself) decides to contribute an implementation.
Open Metrics spec defines a metric type that computes quantiles locally on the client: Summary.
It's quite useful if you want to learn/discover how a system behaves, especially if you don't have much data a-priori. In that sense, Summary is dual to Histogram - both can be used to understand data distribution (e.g. latency data), but with different use-cases and tradeoffs.
Good overview on the differences between Summary and Histogram metrics is given in Prometheus doc https://prometheus.io/docs/practices/histograms/