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Model Registration:
Jupyter: added a new GUI-based Jupyter plugin that provides an intuitive wizard-based approach to register a new model, as well as mechanisms to update existing models, add attachments such as trained model artifacts, and to submit a model for productionization.
CLI: streamlined the approach to register new models via the CLI, with flexible options for adding in schemas, as appropriate.
DataIku DSS: added support to integrate with DataIku’s API’s to onboard code-based Python models created in DataIku DSS.
API: added new API to support registration and persistence of new models, allowing for systematic onboarding of new models, as required.
Model Lifecycle (MLC) Automation:
MLC Engine: new micro service that automates and manages the common processes in the lifecycle of a model, effectively providing the underpinning for scaled Model Operations (ModelOps). The MLC engine allows for the creation of customized model lifecycle (MLC) processes via a drag and drop user interface, including allowing for defining custom business rules around triggering proactive notifications.
MLC Templates: starter model lifecycle templates to automate and manage common processes in the lifecycle of a model, such as model onboarding, model promotion, on-going backtesting, etc.
Champion / Challenger: added support for both automated and manual champion / challenger comparisons across model versions or different models.
Score & Monitor
Batch Jobs: added support for manually or automatically executing batch jobs, which may include batch scoring jobs, batch validation/metrics jobs, or batch training jobs. Each batch run is monitored, tracked, and has its results persisted with the model’s metadata for traceability.
Runtimes: added support for generic runtimes, which may consist of ModelOp Center’s runtime (called “ModelOp Center Engine”) or external runtimes (e.g. DataIku). ModelOp Center can configure, manage, and monitor model execution across these runtimes, allowing for centralized monitoring across all of your existing and future investments in data/analytic platforms.
Endpoints
Notifications & Alerting
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