Getting semantic model refresh issue from fabric pipeline

Question

Getting semantic model refresh issue from fabric pipeline

Ravi M 0

we were trying to run semantic model pipeline in fabric pipeline but getting the below error.

how to fix this?

sematic activity error:
{"message":"You have exceeded the amount of requests allowed in the current time frame and further requests will fail. Retry in 120 seconds."}

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2 answers

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Answer 1

The error message indicates that the semantic model refresh request has been throttled because the allowed request limit for that operation has been exceeded within a short time window. The service is explicitly returning a retry interval of 120 seconds, which means additional requests during that period are likely to be rejected.

A few things to check:

Verify whether your Fabric pipeline is triggering multiple semantic model refreshes concurrently, especially through ForEach activities with parallel execution enabled.
Check whether the same semantic model is being refreshed from multiple sources at the same time, such as a Fabric pipeline, scheduled refresh, Dataflow, or API-based refresh process.
If using a ForEach activity, reduce the batch count or switch to sequential execution to prevent bursts of refresh requests.
Introduce a delay or retry policy that respects the returned retry interval instead of immediately resubmitting the refresh request.

The key point is that this is a throttling/rate limiting response, not a data refresh, model design, or connectivity failure. Focus on reducing request frequency and controlling concurrency rather than repeatedly retrying the activity immediately after it fails.

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Answer 2

The error indicates request throttling. The workload exceeded the allowed number of Fabric service requests in a time window, so additional requests are temporarily blocked.

To fix it:

Wait and retry after the cooldown period shown in the error.
- In this case, retry after 120 seconds.
Add retry logic with exponential backoff in the pipeline or calling process.
- Start with increasing delays such as 1s, 2s, 4s, 8s.
- Respect any Retry-After value when it is returned.
- Set a maximum retry count to avoid endless retries.
- Add jitter to avoid many retries happening at the same time.
Reduce request frequency.
- Avoid tight loops that repeatedly call Fabric APIs or semantic model operations.
- Reduce how often the pipeline triggers semantic model requests.
Reduce concurrency.
- Avoid running multiple concurrent processes against the same Fabric items if not required.
- Stagger pipeline runs if several are starting at the same time.
If this happens frequently, review capacity pressure.
- Frequent throttling can indicate the workload is too high for the current capacity.
- Optimize the workload, and if needed scale up to a higher Fabric capacity SKU.

If the issue continues even after reducing request rate and retrying, contact support.