Control-M for GCP Vertex AI

GCP Vertex AI enables you to build generative AI applications, and train and deploy machine learning models.

Control-M for GCP Vertex AI enables you to do the following:

  • Run GCP Vertex AI pipelines.

  • Control the state of GCP notebooks.

  • Manage GCP Vertex AI credentials in a secure connection profile.

  • Connect to any GCP Vertex AI endpoint.

  • Introduce all Control-M capabilities to Control-M for GCP Vertex AI, including advanced scheduling criteria, complex dependencies, resource pools, lock resources, and variables.

  • Integrate GCP Vertex AI jobs with other Control-M jobs into a single scheduling environment.

  • Monitor the status, results, and output of GCP Vertex AI jobs.

  • Attach an SLA job to the GCP Vertex AI jobs.

Setting up Control-M for GCP Vertex AI

This procedure describes how to deploy the GCP Vertex AI plug-in, create a connection profile, and define a GCP Vertex AI job in Control-M Web and Automation API.

Before You Begin

Begin

  1. Do one of the following:

    • Install: Run one of the following provision image commands:

      • Linux: ctm provision image GCP_Vertex_AI_plugin.Linux

      • Windows: ctm provision image GCP_Vertex_AI_plugin.Windows

    • Upgrade: Run the following command:

      ctm provision agent::update

  2. Create a GCP Vertex AI connection profile in Control-M SaaS or Automation API, as follows:

  3. Define a GCP Vertex AI job in Control-M Web or Automation API, as follows:

To remove this plug-in from an Agent, see Removing a Plug-in. The plug-in ID is GVA092025.

Change Log

The following table describes changes that were introduced in new versions of this plug-in.

Plug-in Version

Details

1.0.01

Initial version