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ADF - Az function activity 499 error

Santhi Dhanuskodi 365 Reputation points
2026-03-09T06:54:47.4266667+00:00

WE get an error while executing azure function activity inside adf pipeline. Azure function is calling an API and extracts and stores the data returned by api to a storage account.

Call to provided Azure function 'api_blob' failed with status-'499' while invoking 'POST' on 'https://<fucntionapp>.azurewebsites.net' and message - 'Invoking Azure function failed with HttpStatusCode - 499.'.

Pls note that the data is generated and stored in storge account, even though adf throws error. have set azure funciton timeout as 30 minutes, and also adf az function activity timeout is also set as more than 1 hour...And we use premium only for function app...and the data generation happens from 6 minutes to 8 minutes.

Azure Data Factory
Azure Data Factory

An Azure service for ingesting, preparing, and transforming data at scale.


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  1. Smaran Thoomu 34,880 Reputation points Microsoft External Staff Moderator
    2026-03-23T13:38:56.2033333+00:00

    Hi @Santhi Dhanuskodi
    Since the Azure Function is completing the processing and writing data successfully, the HTTP 499 error is related to how the connection between ADF and the Function is handled, not a failure in your business logic.

    In Azure Data Factory, the Azure Function activity makes a synchronous HTTP call and expects a response within the gateway handling limits. If the function takes several minutes to respond (even if timeouts are configured higher), the connection can still be closed by the underlying service infrastructure, which results in a 499 error.

    This explains why:

    • Data is generated and stored correctly
    • But ADF marks the activity as failed

    What you can try first

    1. Ensure the function returns the HTTP response as soon as processing completes (avoid any delayed response after blob write).
    2. Check if the function logs show long response serialization or network delays after execution.
    3. Test invoking the function directly (Postman / curl) to confirm response timing consistency.

    Recommended long term approach

    If this process may continue to take several minutes, consider using an asynchronous pattern such as:

    Durable Functions

    Queue-trigger based processing

    This avoids keeping the HTTP request open and makes pipeline execution more reliable.

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