I’m really interested in this because I’ve been doing a lot with Paginated Reports lately, and I can easily see myself running into the same issue.
If you need all the data in a single report (which is usually the most desirable), then his suggestion to "Use the Power BI REST API asynchronously instead of the built-in export action" is the best course of action.
Here’s a way to handle this that avoids the timeout issue in the built‑in Power Automate action.
The “Export to File for Paginated Reports” connector runs synchronously inside Power Automate, so it has to finish within the platform’s execution window. Large paginated report exports often exceed that limit, which is why you see the timeout even though the same export works fine in the Power BI Service.
The workaround is to call the Power BI REST API directly, because the export API is asynchronous. Instead of waiting for the export to finish, you start an export job, get back a job ID, and then poll the job until it completes. Once the job status is “Succeeded,” you download the file from the URL the API returns.
Chris Webb has a great walkthrough showing how to do this with Power Automate using a custom connector. He covers authentication, how to call the ExportToFile endpoint, and how to handle the asynchronous polling pattern. It’s one of the clearest examples of using the REST API for exports.
There’s also a Power BI Dev Camp session that goes deeper into the same pattern. It shows how to build flows around the REST API, how the asynchronous export job works behind the scenes, and how to structure the HTTP calls in Power Automate.
Between those two resources, the pattern looks like this:
- Use an HTTP action to call the ExportToFile endpoint and start the export job.
- Capture the job ID returned by the API.
- Use a Do Until loop to poll the job status endpoint every few seconds.
- When the status becomes “Succeeded,” read the file download URL from the response.
- Use another HTTP action to download the file and store it wherever you need it.
This avoids the synchronous timeout entirely because Power Automate is no longer waiting for the export itself — it’s just checking the job status.
Please post a reply on how you make out with this approach.
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Thanks
-Mark
