Problem creating pipeline job using ml_client.jobs.create_or_update, gives http response error

Thank you for the suggestion. The authentication works, now if I print ml_client.compute.list, it returns all the compute resources from aml but it still fails at ml_client.jobs.create_or_update step.

I have defined multiple step pipeline:

pipeline = func(
    startdate,
    enddate
)

	pipeline_job = ml_client.jobs.create_or_update(pipeline,
							experiment_name=experiment_name
)

---------------------------------------------------------------------------
HttpResponseError                         Traceback (most recent call last)
Cell In[43], line 16
     11 pipeline.outputs.forecast_folder = Output(
     12     type="uri_folder", mode="rw_mount", path=forecast_output_path
     13 )
     15 if run_pipeline:
---> 16     pipeline_job = ml_client.jobs.create_or_update(
     17         pipeline,
     18         experiment_name=experiment_name
     19     )
     21 # Create pipeline with schedule. Different schedules can be used for more information see: https://learn.microsoft.com/en-us/azure/machine-learning/how-to-schedule-pipeline-job?tabs=python
     22 if create_with_schedule:

File /usr/local/Caskroom/miniforge/base/envs/nl-rapidminer/lib/python3.8/site-packages/azure/core/tracing/decorator.py:78, in distributed_trace.<locals>.decorator.<locals>.wrapper_use_tracer(*args, **kwargs)
     76 span_impl_type = settings.tracing_implementation()
     77 if span_impl_type is None:
---> 78     return func(*args, **kwargs)
     80 # Merge span is parameter is set, but only if no explicit parent are passed
     81 if merge_span and not passed_in_parent:

File /usr/local/Caskroom/miniforge/base/envs/nl-rapidminer/lib/python3.8/site-packages/azure/ai/ml/_telemetry/activity.py:350, in monitor_with_telemetry_mixin.<locals>.monitor.<locals>.wrapper(*args, **kwargs)
    348 dimensions = {**parameter_dimensions, **(custom_dimensions or {})}
    349 with log_activity(logger, activity_name or f.__name__, activity_type, dimensions) as activityLogger:
--> 350     return_value = f(*args, **kwargs)
    351     if not parameter_dimensions:
    352         # collect from return if no dimensions from parameter
    353         activityLogger.activity_info.update(_collect_from_return_value(return_value))

File /usr/local/Caskroom/miniforge/base/envs/nl-rapidminer/lib/python3.8/site-packages/azure/ai/ml/operations/_job_operations.py:667, in JobOperations.create_or_update(self, job, description, compute, tags, experiment_name, skip_validation, **kwargs)
    661 if (rest_job_resource.properties.job_type == RestJobType.PIPELINE) or (
    662     hasattr(rest_job_resource.properties, "identity")
    663     and (isinstance(rest_job_resource.properties.identity, UserIdentity))
    664 ):
    665     self._set_headers_with_user_aml_token(kwargs)
--> 667 result = self._operation_2023_02_preview.create_or_update(
    668     id=rest_job_resource.name,  # type: ignore
    669     resource_group_name=self._operation_scope.resource_group_name,
    670     workspace_name=self._workspace_name,
    671     body=rest_job_resource,
    672     **kwargs,
    673 )
    675 if is_local_run(result):
    676     ws_base_url = self._all_operations.all_operations[
    677         AzureMLResourceType.WORKSPACE
    678     ]._operation._client._base_url

File /usr/local/Caskroom/miniforge/base/envs/nl-rapidminer/lib/python3.8/site-packages/azure/core/tracing/decorator.py:78, in distributed_trace.<locals>.decorator.<locals>.wrapper_use_tracer(*args, **kwargs)
     76 span_impl_type = settings.tracing_implementation()
     77 if span_impl_type is None:
---> 78     return func(*args, **kwargs)
     80 # Merge span is parameter is set, but only if no explicit parent are passed
     81 if merge_span and not passed_in_parent:

File /usr/local/Caskroom/miniforge/base/envs/nl-rapidminer/lib/python3.8/site-packages/azure/ai/ml/_restclient/v2023_04_01_preview/operations/_jobs_operations.py:760, in JobsOperations.create_or_update(self, resource_group_name, workspace_name, id, body, **kwargs)
    758     map_error(status_code=response.status_code, response=response, error_map=error_map)
    759     error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
--> 760     raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
    762 if response.status_code == 200:
    763     deserialized = self._deserialize('JobBase', pipeline_response)

HttpResponseError: (UserError) Subscription, ResourceGroup, or WorkspaceName of the input uri does not match the current workspace
Code: UserError
Message: Subscription, ResourceGroup, or WorkspaceName of the input uri does not match the current workspace
Additional Information:Type: ComponentName
Info: {
    "value": "managementfrontend"
}Type: Correlation
Info: {
    "value": {
        "operation": "",
        "request": "eeeeeeeeeeeeee"
    }
}Type: Environment
Info: {
    "value": "westeurope"
}Type: Location
Info: {
    "value": "westeurope"
}Type: Time
Info: {
    "value": "2024-01-08T08:50:53.6377099+00:00"
}

Thank you for the response. The authentication works but it still fails on ml_client.jobs.create_or_update step with the same error.

Hi @Muhammad Hamza Shafiq ,

Thank you for the information that the authentication works. To have a better understanding of the issue you were facing, can you please provide the document you were following, along with the complete code you were using.

Thank you!

@Muhammad Hamza Shafiq Thanks for reaching out to us again, do you have a chance to check on above comment? I hope your issue has been resolved. Regards, Yutong