Getting Data In

How can I exclude a specific recurring time range from my search?

qbolbk59
Path Finder

Hi all,

I need to create a dashboard which can provide me the total review time taken by the analyst. I have created the following query:

| datamodel Incident_Management Notable_Events search | stats earliest(_time) as _time by rule_id  | `drop_dm_object_name("Notable_Events")`| `get_correlations` | join rule_id [| datamodel Incident_Management Incident_Review search  | stats earliest(_time) as reviewtime by Incident_Review.rule_id,Incident_Review.reviewer_realname| `drop_dm_object_name("Incident_Review")`] | eval tot=reviewtime-_time | stats count,avg(tot) as avg_tot,max(tot) as max_tot ,min(tot) as min_tot by reviewer_realname | sort - avg_tot | `uptime2string(avg_tot, avg_tot)` | `uptime2string(max_tot, max_tot)` | `uptime2string(min_tot, min_tot)` |rename *_tot* as *_time_to_review* | fields - *_dec

This is working fine and giving me results close to my expectations. However i don't need to include the off-business hours in the review time. For e.g., if i acknowledged and alert today and i closed it tomorrow, the total review time should not have the Off-business hour time (possibly 8-10 hours) and it should get subtracted.

Can anybody help me here on this issue ?

0 Karma

DalJeanis
Legend

If you absolutely never have a situation where an analyst works on a ticket for more than one work day... i.e., never count more than the work hours during the first and second day :

 | eval daydiff= floor(reviewtime/86400) - floor(_time/86400)
 | eval tot = case(daydiff<=0, reviewtime - _time,
                   daydiff=1, reviewtime - _time - 16*3600,
                   daydiff>1, reviewtime - _time + 8* 3600 - daydiff*86400)

On the other hand, if you want to count all 9-5 hours regardless of weekday or weekend, use this:

 | eval daydiff= floor(reviewtime/86400) - floor(_time/86400)
 | eval tot = case(daydiff<=0, reviewtime - _time,
                   daydiff>=1, reviewtime - _time - daydiff*16*3600)

And, if you want to count off for weekends, but not for weekdays, then there will be some complicated logic that I can't rattle off without checking the time functions.

0 Karma

qbolbk59
Path Finder

Hi @DalJeanis

Thanks for helping. The normal working hours is 12 hours a day and 7 days a week. so if an alert was triggered today and it got closed tomorrow, i need to remove the 12 off business hours from the total time taken. similarly if it got closed after two days, i need to remove 24 hours (2*12) and so on. I used the logic provided by you and modified it a bit and now have used the below query and it seems that now it's rendering me exact results.

| datamodel Incident_Management Notable_Events search | stats earliest(_time) as _time by rule_id | `get_correlations` | join rule_id [| datamodel Incident_Management Incident_Review search  | stats earliest(_time) as reviewtime by Incident_Review.rule_id,reviewer_realname | `drop_dm_object_name("Incident_Review")`] | eval tot=reviewtime-_time |eval tot1=round(tot/86400) | eval tot2=(tot-(tot1*43200)) |stats count,avg(tot2) as avg_tot,max(tot2) as max_tot ,min(tot2) as min_tot by reviewer_realname | sort - avg_tot | `uptime2string(avg_tot, avg_tot)` | `uptime2string(max_tot, max_tot)` | `uptime2string(min_tot, min_tot)` |rename *_tot* as *_time_to_review* | fields - *_dec
0 Karma

qbolbk59
Path Finder

It's not exact result, but close to the expectations. Needs more tweaking.

0 Karma

Sukisen1981
Champion

this is an interesting problem...just to be clear-
eval tot=reviewtime-_time
review time is like a start time and the _time is like an end time for each ticket?
basically, you already have for each event the reviewtime like say
event reviewtime(start time) is 10:00 am on a monday
and the
_time (end time) is like say 10:00 AM on Wednesday?
so assuming an 8 hr work day 8:00 - 16:00
your eval tot should be 6 hrs (mon) + 8 hrs(tue) + 2 hrs(wed)= 16?

0 Karma
Get Updates on the Splunk Community!

Introducing the 2024 Splunk MVPs!

We are excited to announce the 2024 cohort of the Splunk MVP program. Splunk MVPs are passionate members of ...

Splunk Custom Visualizations App End of Life

The Splunk Custom Visualizations apps End of Life for SimpleXML will reach end of support on Dec 21, 2024, ...

Introducing Splunk Enterprise 9.2

WATCH HERE! Watch this Tech Talk to learn about the latest features and enhancements shipped in the new Splunk ...