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APPLIES TO: Python SDK azureml v1
During machine learning deployments using an AKS cluster, you may receive an invalid certificate error, such as {"code":"BadRequest","statusCode":400,"message":"The request is invalid.","details":[{"code":"KubernetesUnaccessible","message":"Kubernetes error: AuthenticationException. Reason: InvalidCertificate"}]
.
Status: Open
Problem area: Inferencing
Azure Machine Learning deployments with an AKS cluster fail with the error:
{"code":"BadRequest","statusCode":400,"message":"The request is invalid.","details":[{"code":"KubernetesUnaccessible","message":"Kubernetes error: AuthenticationException. Reason: InvalidCertificate"}],
and the following error is shown in the MMS logs:
K8sReadNamespacedServiceAsync failed with AuthenticationException: System.Security.Authentication.AuthenticationException: The remote certificate was rejected by the provided RemoteCertificateValidationCallback. at System.Net.Security.SslStream.SendAuthResetSignal(ProtocolToken message, ExceptionDispatchInfo exception) at System.Net.Security.SslStream.CompleteHandshake(SslAuthenticationOptions sslAuthenticationOptions) at System.Net.Security.SslStream.ForceAuthenticationAsync[TIOAdapter](tioadapteradapterbooleanreceivefirstbytereauthenticationdatabooleanisapm) at System.Net.Http.ConnectHelper.EstablishSslConnectionAsync(SslClientAuthenticationOptions sslOptions, HttpRequestMessage request, Boolean async, Stream stream, CancellationToken cancellationToken)
This error occurs because the certificate for AKS clusters created before January 2021 does not include the Subject Key Identifier
value, which prevents the required Authority Key Identifier
value from being generated.
There are two options to resolve this issue:
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Deploy a containerized application on Azure Kubernetes Service - Training
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Manage data ingestion and preparation, model training and deployment, and machine learning solution monitoring with Python, Azure Machine Learning and MLflow.