This topic describes a recommended series of steps to help you start diagnosing issues with a Cloudera Machine Learning workspace.
Issues with Provisioning ML Workspaces: If provisioning an ML workspace fails, first go to your cloud provider account and make sure that you have all the resources required to provision an ML workspace. If failures persist, start debugging by reviewing the error messages on the screen. Check the workspace logs to see what went wrong. For more details on the troubleshooting resources available to you, see Troubleshooting ML Workspaces on AWS.
Issues with Accessing ML Workspaces: If your ML Admin has already provisioned a workspace for you but attempting to access the workspace fails, confirm with your ML Admin that they have completed all the steps required to grant you access: Configuring User Access to CML
Issues with Running Workloads: If you have access to a workspace but are having trouble running sessions/jobs/experiments, and so on, see if your error is already listed here: Troubleshooting Issues with Workloads.
If you need assistance, contact Cloudera Support. Cloudera customers can register for an account to create a support ticket at the support portal. For CDP issues in particular, make sure you include the Request ID associated with your error message in the support case you create.