December 19, 2019

Release notes and fixed issues

  • Monitoring Workspaces with Grafana - CML now leverages Prometheus and Grafana to provide a dashboard that allows you to monitor how CPU, memory, storage, and other resources are being consumed by ML workspaces.
  • Custom Quotas - CML workspace site administrators can now enable custom quotas to set resource usage per user.
  • Tags - There are three new AWS resource tracking tags:
    • Cloudera-Resource-Name: <The CRN of the associated CML Workspace for which the resource was provisioned.>
    • Cloudera-Environment-Resource-Name: <The CRN of the Environment in which the resource was created.>
    • Cloudera-Creator-Resource-Name: <The CRN of the CDP user who requested creation of the resource.>

    AWS resource tags are set by default. They can be searched and viewed through the AWS console or CLI. These tags are helpful for tracking resource usage and cost.

  • Granting remote access - The procedure to grant and revoke remote access to ML workspaces is improved. You can easily add new users. You can also see which users currently have access, and then quickly revoke access to specific users.
  • CML instance type cost reduced - The node used to run the CML application was downsized to a more economical AWS instance type. The instance type was changed from m5.12xlarge to m5.4xlarge, which should result in a noticeable reduction in cloud costs.
  • Base Engine v10-cml1.3 - The default engine is now v10. See the package listing for the updated versions of included libraries.
    • Python 3 is version 3.6.9 (was 3.6.8 in Engine v8).
    • Python 2 is version 2.7.17 (was 2.7.11 in Engine v8).