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typo fix
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articles/machine-learning/how-to-attach-kubernetes-to-workspace.md

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@@ -51,7 +51,7 @@ Otherwise, if a [user-assigned managed identity is specified in Azure Machine Le
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|--|--|--|
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|Azure Relay|Azure Relay Owner|Only applicable for Arc-enabled Kubernetes cluster. Azure Relay isn't created for AKS cluster without Arc connected.|
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|Kubernetes - Azure Arc or Azure Kubernetes Service|Reader <br> Kubernetes Extension Contributor <br> Azure Kubernetes Service Cluster Admin |Applicable for both Arc-enabled Kubernetes cluster and AKS cluster.|
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|Azure Kubernetes Service|Contributor|For private cluster in the region enabled Trusted Access cluster and cannot attach the cluster to workspace.You can check [this doc](https://github.com/Azure/AML-Kubernetes/blob/master/docs/azureml-aks-ta-support.md) for details.|
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|Azure Kubernetes Service|Contributor|For private cluster in the region enabled Trusted Access cluster and cannot attach the cluster to workspace. You can check [this doc](https://github.com/Azure/AML-Kubernetes/blob/master/docs/azureml-aks-ta-support.md) for details.|
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> [!TIP]

articles/machine-learning/how-to-troubleshoot-kubernetes-compute.md

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@@ -178,7 +178,7 @@ This error should occur when the extension owned ingress service does not have e
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You can:
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* Access the cluster and check the status of service `azureml-ingress-nginx-controller` and its backend pod under `azureml` namespace.
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* If cluster does not have any running backend pod, check the reason by describe the pod. For example, if the pod does not have enough resources to run, you can delete some deployments to free enough resources for the ingress pod.
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* If cluster does not have any running backend pod, check the reason by describe the pod. For example, if the pod does not have enough resources to run, you can delete some pods to free enough resources for the ingress pod.
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#### ERROR: ClusterUnauthorized
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AMLArc failed to connect to the cluster, reason: Unauthorized.
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````
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This error should only occur in TA-enabled cluster which means the token has expired during the deployment.
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This error should only occur in TA-enabled cluster, means the access token has expired during the deployment.
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You can try again after several minutes.
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