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.

Control-M for GCP Vertex AI Compatibility

The following table lists the prerequisites that are required to use the GCP Vertex AI plug-in, each with its minimum required version.

Component	Version
Control-M/EM	9.0.22.000
Control-M/Agent	9.0.22.000
Control-M Application Integrator	9.0.22.000
Control-M Automation API	9.0.22.000

Control-M for GCP Vertex AI is supported on Control-M Web and Control-M Automation API, but not on the Control-M client. You cannot use Promotion with the plug-in.

To download the installation files for each prerequisite, see Obtaining Control-M Installation Files.

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.

Integration plug-ins released by BMC require an Application Integrator installation. However, these plug-ins are not editable and you cannot import them into Application Integrator. To deploy these integrations to your Control-M environment, import them directly into Control-M with Control-M Automation API.

Before You Begin

Verify that Java is installed, as described in Control-M External Java Installation.
Verify that Automation API is installed, as described in Automation API Installation.

Begin

Create a temporary directory to save the downloaded files.
Download the GCP Vertex AI plug-in from the Control-M for GCP Vertex AI download page in the EPD site.
Do the following to install the GCP Vertex AI plug-in with the Control-M Automation API provision service:
1. Log in as an administrator to the Control-M/EM server host and save the downloaded ZIP file to the following location:
  - Linux: $HOME/ctm_em/AUTO_DEPLOY
  - Windows: <EM_HOME>\AUTO_DEPLOY
2. Log in to the account where Control-M/Agent is installed and run the following provision image command:
  - Linux: ctm provision image GCP_Vertex_AI_plugin.Linux
  - Windows: ctm provision image GCP_Vertex_AI_plugin.Windows
Create a GCP Vertex AI connection profile in Control-M Web or Automation API, as follows:
- Web: Create a Centralized Connection Profile with GCP Vertex AI Connection Profile Parameters
- Automation API: ConnectionProfile:GCP Vertex AI
Define a GCP Vertex AI job in Control-M Web or Automation API, as follows:
- Web: Create a Job with GCP Vertex AI Job Parameters
- Automation API: Job:GCP Vertex AI

To remove this plug-in from an Agent, see Removing a Plug-in from the Agent. 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
1.0.02	Resolved issue to create a connection profile
1.0.01	Initial version