Open Dieterbe opened 10 years ago
I think graphs with more than 10 targets are very often useless and un-exploitable. (Because you can't differenciate colors visually, then the legend takes the most of your screen space).
Table export would be more usefull with that kind of graph I think.
I would recommand the user to aggregate in that kind of cases.
Table export would be more usefull with that kind of graph I think.
you mean, show a html table with all the data in it?
the graph can be made a little clearer, an upcoming timeserieswidget/flot feature is that you hoover over legend elements and it highlights the corresponding trendline.
another interesting concept could be, if the legend would grow larger than 1 window height, show some kind of systemic overview of the variable tags that would otherwise show up for all targets in the legend. i.e. like a facet display saying which tag keys occur in all targets, and across how many targets, and maybe for each how many different values, and maybe show a few of the most common ones, or something.
we could also show the most deviant ones and hide the rest.
+1
if you didn't filter down a lot, it can happen that graphs contain hundreds of metrics.
limit
, if all targets go on one graph)the same set of targets being rendered on one graph, vs on multiple graphs, is a big difference. I think the problem is, when graphite gets a big request (with multiple targets), it handles them all in sequence instead of in parrallel (need to confirm this). timeserieswidget used to have code that splits up a request in multiple subrequest, i could reintroduce that, or fix graphite to use parrallellisation (unlikely), than in GE/timeserieswidget we just need to do something to make the graph's height match the legend.
or in GE limit the amount of targets per graph. (i.e. max targets per graph 50 or so) you can see the difference usually with something like
catchall statsd
vscatchall statsd group by n1,n2,n3,n4
PRO of splitting up to multiple graphs:
CON of splitting up to multiple graphs: