Messages count
Messages count by type
Average processing time
Average messages size
Messages size
Attachment size
Data filter
Comparing Left dashboard with Right you can say:
(1) SUM MSG Count by Type
- R does not create issues in remote JIRA → Is a project started?
- Considering R is for support team:
- R has abut 1.000 issues created per month → Do you have a team capacity to handle this amount of tickets?
- R receives many incoming comments comparing to L → Is your team able to respond to all tickets on time?
- R does not have too much workflow transitions → Again, that can point to extend team capacity.
- L looks more stable flow.
- There is less tickets.
- There is not so much updates (that could mean tickets are well resolved faster).
- More workflow transitions can point to issues resolved on time.
Of course, first you need to identify your synchronization characteristic / baseline.
(2) AVG Processing Time/AVG MSG Size & (3) SUM MSG Count/SUM MSG Size (Synchronization performance statistic)
- R has decreased processing time and message size. Values are low. Performance is ok.
- L has better performance but it has twice as smaller message size as R.
- Look for high peaks. If AVG Processing Time peaks do not correlate with MSG Size and MSG Count it means JIRA was under heavy load.
- Under heavy stress environment monitor deviations to tune your JIRA server performance on daily basis.
(4) SUM MSG Size/SUM ATT Size
- R and L does not transfer too much attachments. Monitor this statistic over time to predict attachments volume.
- You can eliminate Attachments to see Messages more accurate. Look for high peaks to examine stress situation.
