Cloudera Machine Learning’s new APIv2 provides all CML users with the ability to programmatically create, read, update and delete projects and workloads, including jobs, models and applications. This means that users can automate creation and setup of projects, or trigger actions such as retraining or deploying a new version of a model as part of the project lifecycle, all from within the product or from an external scheduling or CI/CD tool, using the Python client library or HTTPS REST API.
In addition to creating production-ready ML models and applications, machine learning engineers must also take those models and applications to production, which often involves deploying to a different environment. Further, these applications are rarely deployed once and left alone. Rather, many models will be updated with further versions as modellers continue to iterate, or as the profile of incoming data changes. These activities are challenging and susceptible to error if they can only be done manually through a UI. CML’s API now allows ML engineers to script these deployment and maintenance events, schedule or automate them, or integrate with external process and approval workflows by calling APIs based on a suitable trigger.
The new API is available to all CML Public Cloud customers running a workspace upgraded on 01-Sep-2021 or later. APIv2 will be available to CML Private Cloud and Cloudera Data Science Workbench customers in a future release. For more information on getting started with the API, see the associated documentation.
