Control-M for Azure Machine Learning

Azure Machine Learning enables you to build, train, deploy, and manage machine learning models on premises, in the cloud, and on edge devices.

Control-M for Azure Machine Learning enables you to do the following:

• Execute an Azure Machine Learning endpoint pipeline and stop, start, restart, or delete a host or cluster.

• Manage Azure Machine Learning credentials in a secure connection profile.

• Connect to any Azure Machine Learning endpoint.

• Introduce all Control-M capabilities to Control-M for Azure Machine Learning, including advanced scheduling criteria, complex dependencies, Resource Pools, Lock Resources, and variables.

• Integrate Azure Machine Learning jobs with other Control-M jobs into a single scheduling environment.

• Monitor the status, results, and output of Azure Machine Learning jobs.

• Attach an SLA job to the Azure Machine Learning jobs.

• Run 50 Azure Machine Learning jobs simultaneously per Agent.

Control-M for Azure Machine Learning Compatibility

The following table lists the prerequisites that are required to use the Azure Machine Learning plug-in, each with its minimum required version.

Component	Version
Control-M/EM	9.0.20.200
Control-M/Agent	9.0.20.200
Control-M Application Integrator	9.0.20.200
Control-M Automation API	9.0.20.250

Control-M for Azure Machine Learning is supported on Control-M Web and Control-M Automation API, but not on the Control-M client.

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

Setting up Control-M for Azure Machine Learning

This procedure describes how to deploy the Azure Machine Learning plug-in, create a connection profile, and define an Azure Machine Learning job in Control-M Web and Automation API.

Before You Begin

Verify that Automation API is installed, as described in Automation API Installation.

Begin

1. Create a temporary directory to save the downloaded files.

2. Download the Azure Machine Learning plug-in from the Control-M for Azure Machine Learning download page in the EPD site.

3. Install the Azure Machine Learning plug-in via one of the following methods:

   • (9.0.21 or higher) Use the Automation API Provision service, as follows:

     1. Log in to the Control-M/EM Server machine as an Administrator and store the downloaded zip file in the one of the following locations:

        • Linux: $HOME/ctm_em/AUTO_DEPLOY

        • Windows: <EM_HOME>\AUTO_DEPLOY

     2. Log in to the Control-M/Agent machine and run the provision image command, as follows:

        • Linux: ctm provision image ZML_plugin.Linux

        • Windows: ctm provision image ZML_plugin.Windows

   • (9.0.20.200 or lower) Run the Automation API Deploy service, as described in deploy jobtype.

4. Create an Azure Machine Learning connection profile in Control-M Web or Automation API, as follows:

   • Web: Create a Centralized Connection Profile with Azure Machine Learning Connection Profile Parameters

   • Automation API: ConnectionProfile:Azure Machine Learning

5. Define an Azure Machine Learning job in Control-M Web or Automation API, as follows:

   • Web: Create a Job with Azure Machine Learning Job parameters

   • Automation API: Job:Azure Machine Learning

Change Log

The following table provides details about changes that were introduced in new versions of this plug-in:

Plug-in Version	Details
1.0.01	Internal changes to post-API calls
1.0.00	Initial version