def METHOD_NAME(endpoint_name: Optional[str] = None,
                       resource_group_name: Optional[str] = None,
                       workspace_name: Optional[str] = None,
                       opts: Optional[pulumi.InvokeOptions] = None) -> AwaitableGetBatchEndpointResult:
    """
    Use this data source to access information about an existing resource.
    :param str endpoint_name: Name for the Batch Endpoint.
    :param str resource_group_name: The name of the resource group. The name is case insensitive.
    :param str workspace_name: Name of Azure Machine Learning workspace.
    """
    __args__ = dict()
    __args__['endpointName'] = endpoint_name
    __args__['resourceGroupName'] = resource_group_name
    __args__['workspaceName'] = workspace_name
    opts = pulumi.InvokeOptions.merge(_utilities.get_invoke_opts_defaults(), opts)
    __ret__ = pulumi.runtime.invoke('azure-native:machinelearningservices/v20230401preview:getBatchEndpoint', __args__, opts=opts, typ=GetBatchEndpointResult).value
    return AwaitableGetBatchEndpointResult(
        batch_endpoint_properties=pulumi.get(__ret__, 'batch_endpoint_properties'),
        id=pulumi.get(__ret__, 'id'),
        identity=pulumi.get(__ret__, 'identity'),
        kind=pulumi.get(__ret__, 'kind'),
        location=pulumi.get(__ret__, 'location'),
        name=pulumi.get(__ret__, 'name'),
        sku=pulumi.get(__ret__, 'sku'),
        system_data=pulumi.get(__ret__, 'system_data'),
        tags=pulumi.get(__ret__, 'tags'),
        type=pulumi.get(__ret__, 'type'))