There is a command group 'az_ml_online deployment'. This group of commands could 'manage azure ml online deployments'. The group of commands has global parameter '--debug' which means 'Increase logging verbosity to show all debug logs.'. The group of commands has global parameter '--help -h' which means 'Show this help message and exit.'. The group of commands has global parameter '--only-show-errors' which means 'Only show errors, suppressing warnings.'. The group of commands has global parameter '--output -o' which means 'Output format.'. The group of commands has global parameter '--query' which means 'JMESPath query string. See <a href="http://jmespath.org/">http://jmespath.org/</a> for more information and examples.'. The group of commands has global parameter '--subscription' which means 'Name or ID of subscription. You can configure the default subscription using `az account set -s NAME_OR_ID`.'. The group of commands has global parameter '--verbose' which means 'Increase logging verbosity. Use --debug for full debug logs.'. This group contains a child command 'az_ml_online deployment_get logs'.The syntax is: az ml online-deployment get-logs --endpoint-name
                                 --name
                                 --resource-group
                                 --workspace-name
                                 [--container]
                                 [--lines]
                                 [--local {false, true}]. The 1th example of the child command would be to use it to 'get the container logs for an online deployment', the syntax is: az ml online-deployment get-logs --name my-deployment --endpoint-name my-endpoint --lines 100 --resource-group my-resource-group --workspace-name my-workspace. The parameter '--endpoint-name -e' is required. It is used to name of the online endpoint.. The parameter '--name -n' is required. It is used to name of the deployment.. The parameter '--resource-group -g' is required. It is used to name of resource group. you can configure the default group using `az configure --defaults group=<name>`.. The parameter '--workspace-name -w' is required. It is used to name of the azure ml workspace. you can configure the default workspace using `az configure --defaults workspace=<name>`.. The parameter '--container -c' is optional. the type of container from which to retrieve logs. allowed values: inference-server, storage-initializer.. The parameter '--lines -l' is optional. the maximum number of lines to tail.. The parameter '--local' is optional. get logs from local deployment in docker environment.. 