Hello,
We are creating a Dashboard to monitor issues from an external system.
We are collecting data of "issues" using Logstash from a different application and storing them in ElasticSearch.
As a crucial requirement, we want to plot No. of Open Issues against a timeline.
Consider a sample document:
{
"_id": "978",
"issue-id": "issue01",
"status": "OPEN",
"creation-date": "25-Oct-2020",
"last-modified-date": "26-Oct-2020"
}
We have creation-date, last-modified-date, and @timestamp as date fields. Time is also stored with date, of course.
Now we want to create a timeseries to visualize number of open issues with time.
So, for example, if an issue closes, the graph should be updated (decrease). If a new issues opens, the line graph should go up, and so on..
I am trying to do this with Time Series Visual Builder (TSVB), but I am not sure on how to have it mathematically correct. I am trying to do a "Cumulative Sum" on Count Aggregation. I have also applied panel filter to only consider "OPEN" issues.
But this is not correct.
Is there a mathematically correct way I can find cumulative sum of open issues and plot it against a timeline?
Regarding index:
A new document is created in the index whenever an issue changes.
So, in essence, all changes of a particular issue are stored within the index.
For example, if status of the above issue (issue01) changes, a new document would be created with a new _id (the old document is still persisting in the index).
{
"_id": "979",
"issue-id": "issue01",
"status": "CLOSED",
"creation-date": "25-Oct-2020",
"last-modified-date": "27-Oct-2020"
}
Should we think of a different way to index the issues also?
Looking for some guidance here.
Thanks.