AutoML Runner

All component configurations are classified broadly into 3 sections.

• ​Basic ​

• Metadata

• ​Resource Configuration

Steps to configure Auto ML Runner

• Drag and drop the Auto ML Runner component to the Workflow Editor.

• The Auto ML Runner requires input data from an Event and sends the processed data to another Event. Create two Events and drag them on the Workspace.

• Connect the input and output events with the Auto ML Runner component as displayed below.

• The data in the input event can come from any Ingestion, Readers, Any script from DS Lab Module or shared events.

• Click the Auto ML Runner component to get the component properties tabs below.

Basic Information

It is the default tab to open for the component.

• Select an Invocation type from the drop-down menu to confirm the running mode of the reader component. Select ‘Real-Time’ or ‘Batch’ from the drop-down menu.

• Deployment Type: It displays the deployment type for the component. This field comes pre-selected.

• Container Image Version: It displays the image version for the docker container. This field comes pre-selected.

• Failover Event: Select a failover Event from the drop-down menu.

• Batch Size (min 10): Provide the maximum number of records to be processed in one execution cycle (Min limit for this field is 10).

Meta Information

• Project Name: Name of the project where you have created your model in DS Lab Module.

• Model Name: Name of the saved model in project in the DS Lab module.

Saving the Auto ML Runner Component

• Click the Save Component in Storage icon.

• A success notification message appears when the component gets saved.

• The Auto ML Runner component reads the data coming to the input event, runs the model and gives the output data with predicted columns to the output event.