DLab is Self-service, Fail-safe Exploratory Environment for Collaborative Data Science Workflow

New features in v2.4.0

All Cloud platforms:

  • Implemented bucket browser. Now user is able to manage Cloud data source by means of accessing Cloud Blob Storage from DLab Web UI;
  • Added support of audit. Now DLab administrators can view history of all actions;
  • Updated versions of installed software:
    • Ubuntu v.18.04;
    • TensorFlow notebook v.2.1.0;
    • MongoDB v.4.2.

AWS:

  • Added support of new version of Data Engine Service (EMR) v.5.30.0 and v.6.0.0.

Improvements in v2.4.0

All Cloud platforms:

  • Added support of connection via Livy and SparkMagic for Jupyter and RStudio notebooks;
  • Added ability to select multiple resources on 'Environment management' to make user experience easier and more intuitive;
  • Added support to install libraries of particular version from DLab Web UI. Also, now user is able to update/downgrade library via Web UI;
  • Extended billing functionality introducing new entity - monthly project quota(s);
  • Added notifications for cases when project quota is exceeded;
  • Conveyed analytical environment URL's to DLab administration page.

GCP:

  • Added possibility to create custom image for notebook.

Bug fixes in v2.4.0

All Cloud platforms:

  • Fixed a bug when administrative permissions disappeared after endpoint connectivity issues;
  • Fixed a bug when all resources disappeared in 'List of resources' page after endpoint connectivity issues;
  • Fixed a bug when administrative role could not be edited for already existing group;
  • Fixed a bug when billing report was not populated in Safari;
  • Fixed a bug with discrepancies in detailed billing and in-grid billing report.

GCP:

  • Fixed a bug when billing was not correctly updated for period overlapping two calendar years;

Microsoft Azure:

  • Fixed a rare bug when notebooks or SSN were not always created successfully from the first attempt.

Known issues in v2.4.0

GCP:

  • SSO is not available for Superset.

Microsoft Azure:

  • Notebook creation fails on RedHat;
  • Web terminal is not working for Notebooks only for remote endpoint.

Refer to the following link in order to view the other major/minor issues in v2.4.0:

Apache DLab: Known issues

Known issues caused by cloud provider limitations in v2.4.0

Microsoft Azure:

  • Resource name length should not exceed 80 chars;
  • TensorFlow templates are not supported for RedHat Enterprise Linux;
  • Low priority Virtual Machines are not supported yet.

GCP:

  • Resource name length should not exceed 64 chars;
  • NOTE: DLab has not been tested on GCP for RedHat Enterprise Linux.