I built a PowerBI dashboard fetching dynamic Jira data via custom API and JQL. Refresh works in desktop mode but fails when published using direct Jira queries. Any alternatives?
I have encountered a similar issue when deploying PowerBI dashboards that fetch data directly from Jira. In my case, the problem was addressed by restructuring how the data connection was managed. I moved away from direct Jira queries and instead implemented an intermediary service that handled the API calls. This service managed the authentication and caching of data, ensuring that the refresh worked reliably even in the published version. The approach involved some initial setup but ultimately paid off by providing a more consistent integration with Jira.
In my experience, the challenge with dynamic auto-refresh often stems from authentication inconsistencies when the report is published compared to desktop mode. A solution that worked for me was moving to a custom authentication gateway that securely manages API calls. This allowed the published report to maintain a stable connection to Jira without directly exposing credentials. I also noticed that setting refresh schedules with periodic authentication checks helped avoid stale connections. Although it demands a bit of additional setup, this method has proven to be reliable and scalable in managing Jira integrations.
hey, same here. i solved the issue by adding a middle layer that pinged the refresh via scheduled tasks. not the neatest, but it handles the auth hiccups and updates the dashboard reliably. might be worth giving this a try!
In my experience, switching to a more managed connection setup helped address the refresh issues with Jira data in PowerBI. Rather than relying solely on direct queries, I switched to a setup where data refreshes were handled through a dedicated on-premises data gateway and a controlled API endpoint. This change minimized authentication issues while ensuring that refresh intervals were properly managed, even when the dashboard was published. It took some initial configuration, but ultimately, this approach delivered more reliable refresh cycles and allowed for better error monitoring and troubleshooting when integrating Jira data.
In my experience, an alternative solution that worked well was to offload the Jira data into an intermediary storage, such as an Azure SQL database or similar staging area. This approach allows you to schedule smaller, focused data pulls from Jira into the staging environment, decoupling the refresh process from direct Jira queries in PowerBI. Once the data is staged and pre-processed, the PowerBI report refreshes from a more reliable data source. Although it does increase the complexity of your architecture, it provides a stable and consistent refresh cycle, alleviating many of the authentication issues encountered.