Azure Data Lake Analytics now supports new policies to manage compute resources (AUs)

[Azure Data Lake Analytics](https://azure.microsoft.com/en-us/services/data-lake-analytics/) now supports new policies that help you control the compute resources allocated to your most business-critical and experimental/ad-hoc jobs that are running side-by-side in the same account. The policies can be customized to meet your unique business and cost control requirements. This feature introduces two levels of policies that help you manage your compute resources: * **Account-level policies** control how many jobs can run simultaneously, how many Analytics Units (AU) are available to these jobs, etc. * **Job-level policies** control the maximum AUs and priority of each submitted job based on different users or security groups. For more details, see: * [Managing your Azure Data Lake Analytics Compute Resources (Overview)](https://blogs.msdn.microsoft.com/azuredatalake/2017/06/08/managing-your-azure-data-lake-analytics-compute-resources-overview/) * [Managing your Azure Data Lake Analytics Compute Resources (Account-level Policy)](https://blogs.msdn.microsoft.com/azuredatalake/2017/06/08/managing-your-azure-data-lake-analytics-compute-resources-account-level-policy/) * [Managing your Azure Data Lake Analytics Compute Resources (Job-level Policy)](https://blogs.msdn.microsoft.com/azuredatalake/2017/06/08/managing-your-azure-data-lake-analytics-compute-resources-job-level-policy/) * Data Lake Analytics * Features * [ Data Lake Analytics](https://azure.microsoft.com/en-gb/products/data-lake-analytics/)