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Status Future consideration
Workspace Instana
Created by Guest
Created on Oct 14, 2022

24 hour (daily) granularity on long term views

When looking at a few weeks worth of data in Instana granularity is set to 12 hours.
When having a daily seasonality in traffic - which I assume most Instana users have to some extend - this means that data like the number of calls cannot be easily compared. There is always a higher bar and a lower bar. If granularity would be reduced to 24 hours in these cases data would be much easier to compare on a daily basis.

Please evaluate if there a ways to provide this kind of view - either by changing the default behaviour or by adding the possibility to choose.

This does not only apply for application perspectives but basically all dashboards.

Idea priority Medium
  • Guest
    Reply
    |
    Feb 23, 2023

    Hi Edwin.

    Unfortunately I can't see the image you posted. It's somehow broken.

    I am not quite sure, but I think what your suggesting is not what I'm actually looking for.

    When I want to look at the data of a month, I get two values (each 12h) per day. If there was only one value per day, I'd be able to visualize the development of our traffic and also the weekly seasonality. This does not work well with half days.

    Not quite sure if timeshift would help with this.


    Kind regards

    Henning

  • Guest
    Reply
    |
    Feb 9, 2023

    Here's an example of a 1 hr time window for Garbage Collection Time in Custom Dashboards that compares with the same time window from 1 week prior:




  • Guest
    Reply
    |
    Feb 9, 2023

    Here's an example of a 1 hr time window for Garbage Collection Time in Custom Dashboards that compares with the same time window from 1 week prior:




  • Guest
    Reply
    |
    Feb 9, 2023

    Hi Henning, have you considered utilizing the TimeShift capability across Instana to solve this use case?

    With Timeshift, whether it is in Application Dashboards or in Custom Dashboards you can take a higher granularity time window such as 12 hours as in your example and compare it directly with the last time window, or one from 24 hours ago or a week ago etc.