Forum Discussion
Fabric UDFs Deployment ISSUEs
When using python packages the UFDs work in testing mode, but when published and running in run mode I get the following error:
Error:
{ "functionName": "hello_fabric", "invocationId": "00000000-0000-0000-0000-000000000000", "status": "Failed", "errors": [ { "errorCode": "WorkloadException", "subErrorCode": "NotFound", "message": "User data function: 'hello_fabric' invocation failed." } ] }I have pinpointed that this only happens when adding the bigquery auth package and also only in prod/run mode. I have no idea how to fix it as it was working for the past month but after small change to my functions the publishing always show this error.
Example function:
import datetime import fabric.functions as fn import logging import json from google.cloud import bigquery from google.oauth2.credentials import Credentials udf = fn.UserDataFunctions() def get_bigquery_client(var_lib: fn.FabricVariablesClient, auth_type: str = "SERVICE") -> bigquery.Client: variables = var_lib.getVariables() auth_type_upper = auth_type.upper() if auth_type_upper == "PERSONAL": json_string = variables.get("GCP_PERSONAL_API_CREDS_JSON") or "" if not json_string: raise ValueError("auth_type is 'PERSONAL' but GCP_PERSONAL_API_CREDS_JSON is missing or empty.") credentials_info = json.loads(json_string) project_id = credentials_info.get("quota_project_id") user_creds = Credentials.from_authorized_user_info(credentials_info) return bigquery.Client(credentials=user_creds, project=project_id) if auth_type_upper == "SERVICE": json_string = variables.get("GCP_API_CREDS_JSON") or "" if not json_string: raise ValueError("auth_type is 'SERVICE' but GCP_API_CREDS_JSON is missing or empty.") credentials_info = json.loads(json_string) return bigquery.Client.from_service_account_info(credentials_info) raise ValueError(f"Invalid auth_type '{auth_type}'. Must be 'SERVICE' or 'PERSONAL'.") @udf.connection(argName="varLib", alias="apivariables") @udf.function() def hello_fabric(varLib: fn.FabricVariablesClient,name: str) -> str: client = get_bigquery_client(varLib, "PERSONAL") logging.info('Python UDF trigger function processed a request.') return f"{varLib} {client} Welcome to Fabric Functions, {name}, at {datetime.datetime.now()}!"Any help would be appreciated!
Hi Hansie151,
Yes — the pattern you describe strongly points to a Fabric UDF dependency/runtime mismatch, rather than a problem with your BigQuery credentials or the get_bigquery_client() logic.
The key clue is: Works in Test/Develop mode, fails only after Publish → Run only mode, and adding google-cloud-bigquery triggers it.
Please check this.
4 Replies
- odtJitendra
Advocate I
Hi Hansie151,
Yes — the pattern you describe strongly points to a Fabric UDF dependency/runtime mismatch, rather than a problem with your BigQuery credentials or the get_bigquery_client() logic.
The key clue is: Works in Test/Develop mode, fails only after Publish → Run only mode, and adding google-cloud-bigquery triggers it.
Please check this.
This looks like a Fabric User Data Functions (UDF) deployment/runtime issue rather than an issue with your Python code itself.
Since the function works in Test mode but fails in Run/Published mode, and you have isolated the problem to the "google-cloud-bigquery" / "google.oauth2" packages, I would check the production dependency resolution first.
A few things I would try:
1. Pin the package versions instead of relying on the latest versions. For example, explicitly define compatible versions of:
- "google-cloud-bigquery"
- "google-auth"
- "google-api-core"
2. Check the published environment's dependency list and confirm that the Google packages are actually being included after publishing. Test mode can sometimes have a different dependency/runtime context than the deployed function.
3. Try importing the packages separately:
import google.auth
import google.oauth2.credentials
import google.cloud.bigquery
This can help identify whether the failure occurs during module initialization.
4. Since the error is only:
"WorkloadException / NotFound"
and does not expose the underlying Python exception, check the Fabric monitoring/logging output for the published invocation. The actual import/dependency error may be hidden behind the generic workload error.
5. As a diagnostic, temporarily remove the BigQuery imports and the "get_bigquery_client()" call. If the published function runs successfully, that further confirms the dependency/runtime issue.
One other thing I'd test is changing:
from google.oauth2.credentials import Credentials
to a lazy import inside the "PERSONAL" branch. That prevents the Google OAuth package from being loaded when the function is initialized:
if auth_type_upper == "PERSONAL":
from google.oauth2.credentials import Credentials
...
Given that this worked previously and started failing after a relatively small change, I'd also compare the package versions and Fabric runtime/deployment configuration between the last working publication and the current one.
If all of this checks out, I'd raise it with Microsoft as a Fabric Functions deployment regression, providing the function definition, dependency versions, and the fact that Test mode succeeds while Published/Run mode returns "WorkloadException: NotFound".
Please let me know if any of the above solution works for you .
v-sathmakuriCommunity Support
Hi Hansie151 ,
Could you check the suggestion provided above and let us know if you have any additional queries?
Thanks!!
- v-sathmakuri
Hi Hansie151 ,
Could you review the suggestion provided above and let us know if you have any additional questions, we are happy to address.
Thanks!!
