Maybe it’s sharing updates, creating reports, managing documentation, or something entirely different.
Curious to know what’s still taking up your team’s time.
Hi @Akankshya_M _Amoeboids_
With my experience in Data Centre, the most persistent manual headache was handling cross-application users, permissions, and group syncs across isolated spaces and projects.
Unlike Cloud, where Atlassian Guard handle much of the cross-product identity automation out of the box, DC environments often rely on manual administrative intervention when teams scale, change projects, or re-organise.
Common Data Center Friction Points (my opinion)
Manual Project & Space Onboarding: Manually provisioning a new Jira project alongside its corresponding Confluence space, setting up permission schemes, and mapping group access line by line.
Archiving Inactive Users: Deactivating a user in Active Directory/LDAP frees up a seat, but manually scrubbing or reassigning their open Jira tickets, space permissions, and page ownership across DC instances requires tedious admin intervention.
The Data Center Workaround for the above is to have paid automation plugins, or require custom in-house development work.
Thus said, even on Cloud where native automation, Atlassian Rovo, and cross-product triggers do run into manual workarounds caused by platform guardrails, execution limits, and contextual boundaries.
Example:
Thanks for sharing this perspective. 🙌
The difference between Data Center and Cloud is very interesting, especially in the areas of user management, permissions and cross-product administration.
Although automation can reduce repetitive administrative work, human review is still necessary for permissions, inactive users, and outdated knowledge.
The point about stale knowledge base content especially stands out. Automating the cleanup without first understanding whether a page is genuinely obsolete can create more problems than it solves.
There’s definitely a balance between automating repetitive tasks and keeping the right level of human oversight.
Appreciate you adding the Data Center perspective to the discussion!
If I can chime in here, I'd say the reporting aspect is still something that most customers and users think is a side thing and don't give much importance to it. You can actually see how Atlassian looks at it as well (if we're not looking at Atlassian Analytics) 👀
But, from what I've seen and heard, there will be some developments in that area so it's much more robust and combines with AI/Rovo, so we'll see what comes out of it. 🤔
In any case, that's one area which could be automated > for example, creating reports/dashboards out of a user's requirements. ➕
Hi Akankshya,
I would like to have version history/version control for workflows. If workflow change causes an unexpected issue, we should be able to see the previous versions and directly roll back to correct version instead of manually recreating the previous configurations.
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