How to Protect Sensitive Data in Large Jira/Confluence Instances

[Utkarsh Chandel]

With so many Jira issues and Confluence pages created daily, strong data loss prevention (DLP) is essential to stop confidential data from slipping in unnoticed.

Do you run daily scans on new content, or rely on weekly/monthly compliance checks? Do you adjust schedules by project, space, or data sensitivity?

How do you decide what requires frequent monitoring to reduce data leakage risk? I’m also interested in how teams balance scan frequency with performance impact on large instances. Some use continuous monitoring for high‑risk areas, while others rely on scheduled DLP scans for lower‑sensitivity spaces.

Would love to hear what data protection strategies have worked best for others managing information security in Jira and Confluence. 

[Adam Fox]

I think a mix of both works well. High-risk projects and spaces should be monitored more frequently, while lower-risk areas can be checked on a regular schedule. That helps catch sensitive data early without putting too much load on larger Jira and Confluence instances.

It also makes sense to adjust the scan frequency based on the type of data and how often that area changes.