?? Optimizing Jira Performance: Managing Large Change Histories ??

Adding worklog entries in Jira can sometimes become a slow process, especially when an issue has a large change history ??. This can impact team productivity, particularly in scenarios where worklogs are frequently added and tickets remain active over long periods ??. This issue has been identified in the Jira Data Center project under JRASERVER-45903, which explains how large change histories can slow down the process of adding new worklog entries ???.

?? Problem Identified: The analysis revealed a significant performance difference between logging work on an issue with little history and one with over 800 changes. For example:

• Issue with 858 history entries: ? 6104 ms to log work.
• Issue with only 4 history entries: ? 189 ms for the same action.

Teams working on long-term tickets, such as support or maintenance projects, can experience performance degradation due to this issue ??.

?? Suggested Solutions and Workarounds: While this issue is in the long-term backlog for resolution, Atlassian suggests a useful workaround ??: cloning problematic tickets with long histories and using the clones to log new work entries. This reduces the size of the history and improves overall performance ???.

?? Proactive Monitoring: Companies can also adopt proactive strategies by monitoring tickets with large numbers of worklog entries through specific SQL queries. For example:

select issueid, count(id) from worklog group by issueid having count(id) > 100 order by count(id) desc;        

This helps identify issues that could become problematic before they start affecting Jira's performance ??.

?? Conclusion: If you're using Jira for long-term project tracking, it’s essential to implement strategies that prevent large change histories from becoming a bottleneck ?. By combining Atlassian's recommendations with active ticket monitoring, you can maintain optimal performance and keep your teams productive ??.