Not sure how this is supposed to work. To be able to support
Angular's development server and Spring as a standalone application
I had to hardcode the port Spring uses.
The problem is, that Angular runs on port 4200. Angular is compiled
to static files. So I cannot dynamically add the port that is
configured for Spring. But Angular has to be able to talk to the
Spring application.
I chose port 17333, because it does not collide with the standard
Tomcat port (8080).
People are having trouble to understand durations like
100000 or 2.7E+6 milliseconds. Therefore we are
hanging the labels on the y-axis to include the unit
in the tic's label. We also use multiples of seconds,
minutes, hours and days instead of multiples of 10.
The new datetimepicker can be used to specify date ranges. We no longer
need to define a start date and a range. This simplifies the code
for zooming and shifting considerably.
ParallelRequestsAggregator generates a line plot that shows the number
of parallel requests among the plotted events.
This plot has two issues:
1. It only considers events that are plotted. Events that occur later,
but were started within the plotted time frame are not considered.
2. For performance reasons we are only plotting points when a value
changed. This leads to diagonal lines.
Unfortunately the datetime picker does not support seconds. But it is
one of the few that support date and time and are flexible enough to
be used with VueJS.
1. yRange is set to 0-120 minutes. This makes the gallery plots easier
to compare.
2. Set groupBy to pod/method/build. That is what I use the most and I
think this will help in most cases.
- split the 'sortby' select field into two fields
- sort by average
- legend shows plotted and total values in the date range
- removed InlineDataSeries, because it was not used anymore
Sometimes it is useful to specify the certain y-axis range. For example
when you are only interested in the values that take longer than a
threshold. Or when you want to exclude some outliers. When you want to
compare plots in a gallery, it is very handy when all plots have the
same data-area.
Eventually we want to only support what is now called aggregate, but
not have to implement different plot types. So instead of supporting
percentile plots for dashboards I removed them. You can still get
percentile plots together with the scatter plot.
Scaling big plots to small thumbnails results in bad images that barely
show any details.
We solve this by calling gnuplot a second time to generate the
thumbnails. They don't have any labels and are rendered in the required
size, so that not scaling is necessary.
Thumbnails have to be requested explicitly, because it can be expensive
to compute them.
