See the supported connectors for Application Integration.

AI Platform - Prediction task

Preview

This feature is subject to the "Pre-GA Offerings Terms" in the General Service Terms section of the Service Specific Terms. Pre-GA features are available "as is" and might have limited support. For more information, see the launch stage descriptions.

The AI Platform - Prediction task lets you create and submit a Batch prediction job to the Cloud AI Platform Prediction service. Use the Batch prediction service when you don't need your predictions right away, or when you have many instances to get predict. AI Platform Prediction only supports getting Batch predictions from TensorFlow models.

AI Platform Prediction is a Google Cloud service that allows you to serve predictions based on a trained model, whether or not the model was trained on AI Platform.

Before you begin

Ensure that you perform the following tasks in your Google Cloud project before configuring the AI Platform - Prediction task:

1. Enable the Platform Training & Prediction API (ml.googleapis.com).

   Enable the Platform Training & Prediction API

2. Create an authentication profile. Application Integration uses an authentication profile to connect to an authentication endpoint for the AI Platform - Prediction task.
   Note: If you're creating an authentication profile of Service account type, then ensure that the service account is assigned with the IAM role that contains the following IAM permission(s):

   • ml.jobs.create

   To know about IAM permissions and the predefined IAM roles that grant them, see IAM permissions reference.

   For information about granting additional roles or permissions to a service account, see Granting, changing, and revoking access.

Configure the AI Platform - Prediction task

1. In the Google Cloud console, go to the Application Integration page.

   Go to Application Integration

2. In the navigation menu, click Integrations.

   The Integrations page appears listing all the integrations available in the Google Cloud project.

3. Select an existing integration or click Create integration to create a new one.

   If you are creating a new integration:

   1. Enter a name and description in the Create Integration pane.
   2. Select a region for the integration.
      Note: The Regions dropdown only lists the regions provisioned in your Google Cloud project. To provision a new region, Click Enable Region. See Enable new region for more information.
   3. Select a service account for the integration. You can change or update the service account details of an integration any time from the Integration summary pane in the integration toolbar.
      Note: The option to select a service account is displayed only if you have enabled integration governance for the selected region.
   4. Click Create.

   This opens the integration in the integration editor.

4. In the integration editor navigation bar, click Tasks to view the list of available tasks and connectors.
5. Click and place the AI Platform - Prediction element in the integration editor.
6. Click the AI Platform - Prediction element on the designer to view the AI Platform - Prediction task configuration pane.
7. Go to Authentication, and select an existing authentication profile that you want to use.

   Optional. If you have not created an authentication profile prior to configuring the task, Click + New authentication profile and follow the steps as mentioned in Create a new authentication profile.

8. Go to Task Input, and configure the displayed inputs fields using the following Task input parameters table.

   Changes to the inputs fields are saved automatically.

Task input parameters

The following table describes the input parameters of the AI Platform - Prediction task:

Property	Data type	Description
Region	String	Region where you want to run the prediction job. For example, us-central1.
ProjectsId	String	Your Google Cloud project ID.
Request	JSON	See request JSON structure.

Task output

The AI Platform - Prediction task returns the newly created instance of the job.

Error handling strategy

An error handling strategy for a task specifies the action to take if the task fails due to a temporary error. For information about how to use an error handling strategy, and to know about the different types of error handling strategies, see Error handling strategies.

Quotas and limits

For information about quotas and limits, see Quotas and limits.

What's next

• Add edges and edge conditions.
• Test and publish your integration.
• Configure a trigger.
• Add a Data Mapping task.
• See all tasks for Google Cloud services.