The idea of the explore page is to give a slightly “higher” level view of your data than why Pyroscope currently gives you.
I created a mockup of what I was thinking about for another page on the sidebar called “tag explorer”
Current problem
For example, right now for our rideshare example, there is one particular region and one particular vehicle that have performance issues, but if we didn’t know that before looking at the example how could we figure out which vehicle and which region are the “problem” areas?
In current Pyroscope you have to click one by one through each region and then one by one through each vehicle and then possible combine region + vehicle in order to figure this out. The comparison page makes this slightly faster 2x but only because you can compare two things at once…
Proposed solution
In this proposed “explore” page i’m proposing that we allow users to select a tag_key and see all the series associated with the corresponding tag values on one graph.
Note: Lets NOT add the “where” dropdown for v1
In this situation, if one region is consuming significantly more cpu, even if there are 30 regions, we would be able to see at first glance that 29 are normal and one series is high.
We could then dig further and look at the “descriptive statistics” for that series compared to the other series.
Finally, we could see the flamegraph associated with that series and if we want we can use the buttons to go to Single view, comparison view, or diff view.
We can do group by, but not “where”. So for the first implementation we should not include the “where” dropdown.
Descriptive statistics:
For V1 we can just stub these.
For example we will eventually calculate all these column headers on the frontend. But for now we should just use something simple like avg_samples and just use that for all 9 columns.
The more important functionality is to be able to click on one of the tags and have it show up in the flamegraph below.
Long term benefits or proposed solution
This allows for the potential to do “alerts” based off of these statistics
Opens the door / lays the foundation for more advanced analytics
Once we have an endpoint for merging flamegraphs we could potentially do something like comparing a single flamegraph for <25% percentile to >75% percentile. Note: I’m considering each 10s “bar” it’s own data point…
Rperry2174
commented
2 years ago
Goal:
The idea of the explore page is to give a slightly “higher” level view of your data than why Pyroscope currently gives you. I created a mockup of what I was thinking about for another page on the sidebar called “tag explorer”
Current problem
For example, right now for our rideshare example, there is one particular region and one particular vehicle that have performance issues, but if we didn’t know that before looking at the example how could we figure out which vehicle and which region are the “problem” areas?
In current Pyroscope you have to click one by one through each region and then one by one through each vehicle and then possible combine region + vehicle in order to figure this out. The comparison page makes this slightly faster 2x but only because you can compare two things at once…
Proposed solution
In this proposed “explore” page i’m proposing that we allow users to select a tag_key and see all the series associated with the corresponding tag values on one graph.
Note: Lets NOT add the “where” dropdown for v1
In this situation, if one region is consuming significantly more cpu, even if there are 30 regions, we would be able to see at first glance that 29 are normal and one series is high.
We could then dig further and look at the “descriptive statistics” for that series compared to the other series.
Finally, we could see the flamegraph associated with that series and if we want we can use the buttons to go to Single view, comparison view, or diff view.
Implementation details
Dmitry added support for “group by” queries here: https://github.com/pyroscope-io/pyroscope/pull/1244
We can do group by, but not “where”. So for the first implementation we should not include the “where” dropdown.
Descriptive statistics:
For V1 we can just stub these.
For example we will eventually calculate all these column headers on the frontend. But for now we should just use something simple like
avg_samplesand just use that for all 9 columns.The more important functionality is to be able to click on one of the tags and have it show up in the flamegraph below.
Long term benefits or proposed solution
Reference
Here's how jaeger does descriptive statistics