Hello community,
We’re currently developing a Forge application that needs to retrieve all issues from a Jira instance. The problem we’re facing is that the Jira REST API limits the response to 100 issues per request, which makes it challenging to handle large instances efficiently.
We tried fetching issues in chunks (batches of 100) and then combining them once all pages are loaded. While this approach works for smaller datasets, it becomes problematic for large instances containing thousands of issues — the app eventually crashes or runs out of resources when too many results are processed in memory.
We’re looking for a better approach or workaround to overcome this limitation. Ideally, we want to fetch all issues from the instance without hitting Forge’s resource or memory constraints, perhaps by processing data incrementally, streaming results, or storing partial data between requests.
Has anyone faced a similar situation or found an efficient pattern for handling large-scale Jira issue retrieval in Forge? Any best practices, examples, or guidance would be greatly appreciated.
Thanks in advance for your help!