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First of all a big thanks to the Perses team for creating this utility. Understanding metrics_usage is a critical first step to identifying unused/underused metrics. However one critical piece that is currently missing is ad-hoc queries from Grafana ( or your tool of choice).
Any interest in adding this feature to this project? A "simple" approach would be to parse the query logs generated by Grafana within a period of time and extract out the queries and by extension the underlying time series.
This is an are that we'll be investing time in this quarter so I'm trying to gauge whether this feature would be of interest to this project. If so, we'd love to collaborate on a solution.
The text was updated successfully, but these errors were encountered:
On a unrelated note - a static analyzer is a nice starting point, but have you also considered an online approach that keeps track of metrics usage over time? My thought is if this is turned into a service that is constantly polling the right sources and capturing a real time state of metrics_usage, then it could be used to auto downsample or even filter unused/underused metrics. A "Poor mans adaptive metrics" if you will.
Hey folks,
First of all a big thanks to the Perses team for creating this utility. Understanding metrics_usage is a critical first step to identifying unused/underused metrics. However one critical piece that is currently missing is ad-hoc queries from Grafana ( or your tool of choice).
Any interest in adding this feature to this project? A "simple" approach would be to parse the query logs generated by Grafana within a period of time and extract out the queries and by extension the underlying time series.
This is an are that we'll be investing time in this quarter so I'm trying to gauge whether this feature would be of interest to this project. If so, we'd love to collaborate on a solution.
The text was updated successfully, but these errors were encountered: