@Virginia Lopez-Gil Does this error occur consistently with your workspace? Do you have any other workspace facing similar issues when you try to publish?
You may have to request a support case to get this looked in detail with the service team. If you do not have a support subscription we could help you get one for this issue. Thanks!!
Azure Error: HTTPSConnectionPool(host='westus2.api.azureml.ms', port=443):
Virginia Lopez-Gil
11
Reputation points
Hi,
we have a process that we have been running for over a year and suddenly have started failing and the error is not very descriptive. In this process, we run a train evaluation and a registration process from Azure DevOps.
The script that we are running is:
def main():
# Get Azure machine learning workspace
login_azure = ServicePrincipalAuthentication(tenant_id, app_id, app_secret)
aml_workspace = Workspace.get(
name=workspace_name,
subscription_id=subscription_id,
resource_group=resource_group,
auth=login_azure,
)
myenv = Environment(name="myenv")
CONDA_YAML = "src/train/conda_dependencies.yml"
load_requirements_into_conda_yml(conda_yml=CONDA_YAML)
conda_dep = CondaDependencies(conda_dependencies_file_path=CONDA_YAML)
# We need this pip version
conda_dep.add_conda_package("pip==20.2.4")
files_whl = []
os.chdir("./ml_service/pipelines")
for file_whl in glob.glob("*.whl"):
files_whl.append(file_whl)
for file_whl in files_whl:
try:
whl_url = Environment.add_private_pip_wheel(
workspace=aml_workspace, file_path=file_whl, exist_ok=True
)
conda_dep.add_pip_package(whl_url)
except Exception:
print(f"Not able to add the wheel {file_whl}")
os.chdir("../../")
myenv.docker.base_image_registry.address = REGISTRY_CONTAINER_IMAGE
myenv.docker.base_image_registry.username = REGISTRY_CONTAINER_USERNAME
myenv.docker.base_image_registry.password = REGISTRY_CONTAINER_PASSWORD
# Environment Configuration
myenv.docker.enabled = True
myenv.python.user_managed_dependencies = False
myenv.docker.base_image = REGISTRY_BASE_IMAGE
myenv.python.conda_dependencies = conda_dep
run_config = RunConfiguration()
run_config.target = "template-trainc"
# Image configuration
model_name = PipelineParameter(name="model_name", default_value=model_name)
release_id = PipelineParameter(name="release_id", default_value="0")
run_config.environment = myenv
train_step = PythonScriptStep(
name="Train Model",
script_name=train_script_path,
compute_target=run_config.target,
source_directory=sources_directory_train,
arguments=["--release_id", release_id, "--model_name", model_name],
runconfig=run_config,
allow_reuse=False,
)
print("Step Train created")
evaluate_step = PythonScriptStep(
name="Evaluate Model ",
script_name=evaluate_script_path,
compute_target=run_config.target,
source_directory=sources_directory_train,
arguments=["--release_id", release_id, "--model_name", model_name],
runconfig=run_config,
allow_reuse=False,
)
print("Step Evaluate created")
evaluate_step.run_after(train_step)
steps = [evaluate_step]
train_pipeline = Pipeline(workspace=aml_workspace, steps=steps)
train_pipeline.validate()
published_pipeline = train_pipeline.publish(
name=pipeline_name, description="Model training/retraining pipeline", version=build_id
)
print(f"Published pipeline: {published_pipeline.name}")
print(f"for build {published_pipeline.version}")
the error is produced by this line:
published_pipeline = train_pipeline.publish(
name=pipeline_name, description="Model training/retraining pipeline", version=build_id
)
We are running the process in a container, that we have saved in azure acr, the container image that we are using is https://github.com/microsoft/MLOpsPython, with the requirements:
adal==1.2.2
antlr4-python3-runtime==4.7.2
applicationinsights==0.11.9
argcomplete==1.10.0
asn1crypto==0.24.0
atomicwrites==1.3.0
attrs==19.1.0
azure-batch==7.0.0
azure-cli==2.0.71
azure-cli-command-modules-nspkg==2.0.3
azure-cli-core==2.0.71
azure-cli-nspkg==3.0.4
azure-cli-telemetry==1.0.3
azure-common==1.1.23
azure-cosmos==3.1.1
azure-datalake-store==0.0.47
azure-functions-devops-build==0.0.22
azure-graphrbac==0.60.0
azure-keyvault==1.1.0
azure-mgmt-advisor==2.0.1
azure-mgmt-appconfiguration==0.1.0
azure-mgmt-applicationinsights==0.1.1
azure-mgmt-authorization==0.52.0
azure-mgmt-batch==6.0.0
azure-mgmt-batchai==2.0.0
azure-mgmt-billing==0.2.0
azure-mgmt-botservice==0.2.0
azure-mgmt-cdn==3.1.0
azure-mgmt-cognitiveservices==5.0.0
azure-mgmt-compute==6.0.0
azure-mgmt-consumption==2.0.0
azure-mgmt-containerinstance==1.5.0
azure-mgmt-containerregistry==3.0.0rc5
azure-mgmt-containerservice==5.3.0
azure-mgmt-cosmosdb==0.7.0
azure-mgmt-datalake-analytics==0.2.1
azure-mgmt-datalake-nspkg==3.0.1
azure-mgmt-datalake-store==0.5.0
azure-mgmt-datamigration==0.1.0
azure-mgmt-deploymentmanager==0.1.0
azure-mgmt-devtestlabs==2.2.0
azure-mgmt-dns==2.1.0
azure-mgmt-eventgrid==2.2.0
azure-mgmt-eventhub==2.6.0
azure-mgmt-hdinsight==1.1.0
azure-mgmt-imagebuilder==0.2.1
azure-mgmt-iotcentral==1.0.0
azure-mgmt-iothub==0.8.2
azure-mgmt-iothubprovisioningservices==0.2.0
azure-mgmt-keyvault==1.1.0
azure-mgmt-kusto==0.3.0
azure-mgmt-loganalytics==0.2.0
azure-mgmt-managedservices==1.0.0
azure-mgmt-managementgroups==0.2.0
azure-mgmt-maps==0.1.0
azure-mgmt-marketplaceordering==0.2.1
azure-mgmt-media==1.1.1
azure-mgmt-monitor==0.5.2
azure-mgmt-msi==0.2.0
azure-mgmt-netapp==0.5.0
azure-mgmt-network==3.0.0
azure-mgmt-nspkg==3.0.2
azure-mgmt-policyinsights==0.3.1
azure-mgmt-privatedns==0.1.0
azure-mgmt-rdbms==1.9.0
azure-mgmt-recoveryservices==0.4.0
azure-mgmt-recoveryservicesbackup==0.4.0
azure-mgmt-redis==6.0.0
azure-mgmt-relay==0.1.0
azure-mgmt-reservations==0.3.1
azure-mgmt-resource==2.2.0
azure-mgmt-search==2.1.0
azure-mgmt-security==0.1.0
azure-mgmt-servicebus==0.6.0
azure-mgmt-servicefabric==0.2.0
azure-mgmt-signalr==0.1.1
azure-mgmt-sql==0.13.0
azure-mgmt-sqlvirtualmachine==0.4.0
azure-mgmt-storage==4.0.0
azure-mgmt-trafficmanager==0.51.0
azure-mgmt-web==0.42.0
azure-multiapi-storage==0.2.4
azure-nspkg==3.0.2
azure-storage-blob==1.5.0
azure-storage-common==1.4.2
azureml==0.2.7
azureml-core==1.0.62
azureml-dataprep==1.1.17
azureml-dataprep-native==13.0.3
azureml-pipeline==1.0.62
azureml-pipeline-core==1.0.62
azureml-pipeline-steps==1.0.62
azureml-sdk==1.0.62
azureml-telemetry==1.0.62
azureml-train==1.0.62
azureml-train-core==1.0.62
azureml-train-restclients-hyperdrive==1.0.62
backports.tempfile==1.0
backports.weakref==1.0.post1
bcrypt==3.1.7
certifi==2019.3.9
cffi==1.11.5
chardet==3.0.4
cloudpickle==1.2.2
colorama==0.4.1
conda==4.3.16
contextlib2==0.5.5
cryptography==2.4.2
distro==1.4.0
docker==4.0.2
dotnetcore2==2.1.8.1
entrypoints==0.3
fabric==2.5.0
flake8==3.7.8
flake8-formatter-junit-xml==0.0.6
fusepy==3.0.1
humanfriendly==4.18
idna==2.8
importlib-metadata==0.23
invoke==1.3.0
isodate==0.6.0
javaproperties==0.5.1
jeepney==0.4.1
Jinja2==2.10.1
jmespath==0.9.4
jsondiff==1.2.0
jsonpickle==1.2
junit-xml==1.8
knack==0.6.3
MarkupSafe==1.1.1
mccabe==0.6.1
mock==2.0.0
more-itertools==7.2.0
msrest==0.6.10
msrestazure==0.6.2
ndg-httpsclient==0.5.1
numpy==1.19.4
oauthlib==3.1.0
pandas==1.1.4
paramiko==2.6.0
pathspec==0.5.9
pbr==5.4.3
pip==18.1
pluggy==0.13.0
portalocker==1.5.1
psutil==5.6.3
py==1.8.0
pyasn1==0.4.7
pycodestyle==2.5.0
pycosat==0.6.3
pycparser==2.19
pydocumentdb==2.3.3
pyflakes==2.1.1
Pygments==2.4.2
PyJWT==1.7.1
PyNaCl==1.3.0
pyOpenSSL==18.0.0
PySocks==1.6.8
pytest==4.3.0
python-dateutil==2.8.0
python-dotenv==0.10.3
pytz==2019.1
PyYAML==5.1.2
requests==2.22.0
requests-oauthlib==1.2.0
ruamel.yaml==0.16.12
ruamel.yaml.clib==0.2.2
scp==0.13.2
SecretStorage==3.1.1
setuptools==40.6.3
six==1.12.0
sshtunnel==0.1.5
tabulate==0.8.3
urllib3==1.24.1
vsts==0.1.25
vsts-cd-manager==1.0.2
websocket-client==0.56.0
wheel==0.30.0
xmltodict==0.12.0
zipp==0.6.0
Error:
File "/usr/local/lib/python3.7/site-packages/azureml/pipeline/core/_aeva_provider.py", line 100, in __init__
self.datatype_provider.ensure_default_datatypes()
File "/usr/local/lib/python3.7/site-packages/azureml/pipeline/core/_aeva_provider.py", line 1512, in ensure_default_datatypes
ids = [datatype.id for datatype in self.get_all_datatypes()]
File "/usr/local/lib/python3.7/site-packages/azureml/pipeline/core/_aeva_provider.py", line 1448, in get_all_datatypes
entities = self._service_caller.get_all_datatypes_async()
File "/usr/local/lib/python3.7/site-packages/azureml/pipeline/core/_restclients/aeva/service_caller.py", line 499, in get_all_datatypes_async
workspace_name=self._workspace_name, custom_headers=self._get_custom_headers())
File "/usr/local/lib/python3.7/site-packages/azureml/pipeline/core/_restclients/aeva/aml_pipelines_api10.py", line 813, in api_v10_subscriptions_by_subscription_id_resource_groups_by_resource_group_name_providers_microsoft_machine_learning_services_workspaces_by_workspace_name_data_types_get
response = self._client.send(request, header_parameters, stream=False, **operation_config)
File "/usr/local/lib/python3.7/site-packages/msrest/service_client.py", line 336, in send
pipeline_response = self.config.pipeline.run(request, **kwargs)
File "/usr/local/lib/python3.7/site-packages/msrest/pipeline/__init__.py", line 197, in run
return first_node.send(pipeline_request, **kwargs) # type: ignore
File "/usr/local/lib/python3.7/site-packages/msrest/pipeline/__init__.py", line 150, in send
response = self.next.send(request, **kwargs)
File "/usr/local/lib/python3.7/site-packages/msrest/pipeline/requests.py", line 137, in send
return self.next.send(request, **kwargs)
File "/usr/local/lib/python3.7/site-packages/msrest/pipeline/__init__.py", line 150, in send
response = self.next.send(request, **kwargs)
File "/usr/local/lib/python3.7/site-packages/msrest/pipeline/requests.py", line 193, in send
self.driver.send(request.http_request, **kwargs)
File "/usr/local/lib/python3.7/site-packages/msrest/universal_http/requests.py", line 333, in send
return super(RequestsHTTPSender, self).send(request, **requests_kwargs)
File "/usr/local/lib/python3.7/site-packages/msrest/universal_http/requests.py", line 145, in send
raise_with_traceback(ClientRequestError, msg, err)
File "/usr/local/lib/python3.7/site-packages/msrest/exceptions.py", line 51, in raise_with_traceback
raise error.with_traceback(exc_traceback)
File "/usr/local/lib/python3.7/site-packages/msrest/universal_http/requests.py", line 142, in send
**kwargs)
File "/usr/local/lib/python3.7/site-packages/requests/sessions.py", line 530, in request
resp = self.send(prep, **send_kwargs)
File "/usr/local/lib/python3.7/site-packages/requests/sessions.py", line 643, in send
r = adapter.send(request, **kwargs)
File "/usr/local/lib/python3.7/site-packages/requests/adapters.py", line 507, in send
raise RetryError(e, request=request)
msrest.exceptions.ClientRequestError: Error occurred in request., RetryError: HTTPSConnectionPool(host='westus2.api.azureml.ms', port=443): Max retries exceeded with url: /api/v1.0/subscriptions/01c989d5-4dec-4881-a9df-193efdcc5582/resourceGroups/trpacml01-AML-RG/providers/Microsoft.MachineLearningServices/workspaces/trpacml01-AML-WS/DataTypes (Caused by ResponseError('too many 530 error responses'))
##[error]Bash exited with code '1'.
Is there is any new kind of requirement? proxy? or the service is unavailable?
Thank you so much!
Azure Machine Learning
Azure Machine Learning
An Azure machine learning service for building and deploying models.
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romungi-MSFT 49,096 Reputation points Microsoft Employee Moderator2021-02-03T10:16:40.747+00:00