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    To grant access for Cluster nodes API in HDI ESP enabled cluster for Azure AD users with Ambari admin role other than Cluster Admin user

    The node details of HDInsight clusters can be retrieved via API call using the below endpoint https:///ws/v1/cluster/nodes/ Apache wiki Reference: https://hadoop.apache.org/docs/current/hadoop-yarn/hadoop-yarn-site/ResourceManagerRest.html#Cluster_Nodes_API Currently the support is there for Non-ESP HDI cluster where any local user in cluster group can access it. In ESP HDI cluster, only the cluster admin user(super user) has the access to it. Even if we give Ambari admin role for AAD domain users, its not able to access the endpoints and retrieve the cluster node details. We need this feature where AAD user with Ambari Administrator role should be able to access the API and retrieve cluster node details.

    Support changing timezone settings on cluster nodes

    The customer is planning to monitor the logs on each nodes in case of failure and would like to change the time zone settings on host operating system of each nodes. This is not supported on HDI cluster now. Appreciate if you could consider supporting this.

    Hdinsight deployment percentage bar

    Customer believe that if we add a percentage bar. That would be very help to their development end. They are not aware of the depoyment stages and wanted to tracked it by a percentage bar.

    Need more detailed cluster failure messages in the Portal UI and via Powershell

    It currently took 2 weeks to resolve issues with Cluster creation. Part of this was due to the generic error messages posted to the UI . "Error: Internal server error occurred while processing the request. Please retry the request or contact support." should never be an error in it's entirety there needs to be more details to provide the client the ability to troubleshoot and make informed decisions. Errors found by Microsoft during their review of internal logs that are unavailable to the users would have enabled us to to provide more information and to confirm things prior to contacting support. You can review case 119070524002276 for all the back and forth between us and MS to determine the underlying issue. Either you need to enhance the error logs within your application or give clients access to the logs that MS is reviewing. The issues ending up being an MS internal quota issue and a known bug that intermittently affects Spark clusters which took 2 weeks to discover mainly because we had to have the cluster fail then wait for MS to review the logs.

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