Cloudera is delighted to announce the release of Cloudera Data Science Workbench 1.4.0. With this release, Cloudera Data Science Workbench extends the machine learning platform experience from research to production. Data scientists can now build, train, and deploy models in a unified workflow with two new key capabilities: experiments and models.
Experiments: Experiments let data scientists train, compare, and reproduce versioned models. With this feature,, data scientists can run a batch job that will:
- create a snapshot of model code, dependencies, and configuration parameters necessary to train the model
- build and execute the training run in an isolated container
- track model metrics, performance, and any model artifacts the user specifies
Models: Models let data scientists build, deploy, and manage models as REST APIs to serve predictions. With this feature, data scientists can simply select a Python or R function within a project file, and Cloudera Data Science Workbench will:
- create a snapshot of model code, saved model parameters, and dependencies
- build an immutable executable container with the trained model and serving code
- add a REST endpoint that automatically accepts input parameters matching the function signature, and that returns a data structure matching the function’s return type
- save the built model container, along with metadata like who built or deployed it
- deploy and start a specified number of model API replicas, automatically load balanced
- let the user document, test, and share the model
In addition, Cloudera Data Science Workbench 1.4 also includes security enhancements that help automate user administration.
Simplified user administration: Previous CDSW releases offered LDAP and SAML authentication but allowed every user to log in. The consequence was user sprawl and unintended license consumption. Site administrators had to be manually entitled in the Cloudera Data Science Workbench UI.
With version 1.4 you can now designate LDAP and SAML groups for both users and administrators. With automatic synchronisation, the ability to log in or administer CDSW now depends on a user’s group membership. These groups can be assigned in your existing centralised LDAP/SAML authentication system.
We’ve added two new properties to CDSW:
- LDAP/SAML User Groups - Groups whose users can log in to CDSW
- LDAP/SAML Admin Groups - Groups whose users are automatically made site administrators in CDSW
For a complete list of new features and bug fixes in this release, please see the Release Notes.
For more information on downloading, installing and using Cloudera Data Science Workbench, please see the links below:
As always, we welcome your feedback. Please send your comments and suggestions on our community forums.
