AAI Integration for Control-M

Automic Automation Intelligence (AAI) for Control-M allows you to put the runtime information of executions from different Clients in multiple Control-M systems into a single view. This means that you can see running executions (and possible failed ones) of more than one Control-M system in a single interface, without having to switch from one Control-M interface to another.

This page includes the following:

Overview

The Control-M Connector establishes the communication between Control-M and Automic Automation Intelligence. It is a stand-alone component. As such, it runs in its own process space, has its own installer and writes its own log files. It consists of two main parts:

  1. The universal connector framework, which handles the communication between the Control-M Connector and AAI. It also triggers, or determines, when the Connector fetches job definitions and events (executions) from Control-M.
  2. A mapper, which extracts job definitions and events (executions) from Control-M and translates them into a format that Automic Automation Intelligence can process.

Therefore, it is recommended to install the Control-M Connector near the Control-M installation.

The Connector connects with the Control-M database to periodically extract job definitions and executions (current and historical runs) and import them into AAI.

The Control-M Connector has different settings that can be modified at any time. For example, you can define the following behaviors:

  • The interval in which the job definitions and events (executions) are fetched. You can set the interval for fetching both individually.
  • Upon starting, how far back should the Connector look the first time it fetches information.
  • How far forward should the Connector look, thus gathering information on planned start times.

Once the Connector is installed and running for the first time, it reaches to Automic Automation Intelligence and registers itself. The user sets up the Control-M configuration in the Automic Automation Intelligence client. Once Automic Automation Intelligence has configured the Connector to talk to Control-M, the Connector schedules retrieving the job definitions and events (executions) from Control-M, translates them into the relevant format and passes the information to Automic Automation Intelligence.

Each Control-M datacenter that you want to add to your AAI environment requires its own Control-M scheduler configuration. Several schedulers can be linked to one Connector. However, only one Connector can be linked to an Automic Automation Intelligence environment.

Setup and Configuration

Before adding a Control-M instance to your Automic Automation Intelligence system, you must have Automic Automation Intelligence up and running. For more information, see Installation Guide.

The Control-M Connector has to be installed as well. You can find the relevant installation files (Windows or UNIX) at https://support.broadcom.com/.

Important! For performance reasons, it is recommended to install the Control-M Connector near the Control-M installation, not near Automic Automation Intelligence.

Also, you can secure your Connectors using TLS 1.2 based secure connections. For more information, see Two-Way Certificate-Based Authentication over TLS 1.2.

Installing the Control-M Connector

  1. Log into the Broadcom support site. You require a Broadcom account to log in.

  2. Go to Enterprise Software > Product Downloads > Automic Automation Intelligence and download the relevant product.

  3. Follow the instructions in the setup wizard. You can define a destination directory, if you want to create a Start Menu folder and / or shortcuts for all users.

    When you are done with the wizard, you can find the Control-M Connector folder in the directory that you defined. The Connector starts as a Service.

You also have to add Control-M schedulers to your Automic Automation Intelligence environment. To do so, go to System > Schedulers in your web interface and follow the steps in the dialog to add a Control-M scheduler. For more information, see Adding a Control-M Scheduler.

If the process was successful, the new schedulers are listed with all the schedulers available in your system.

Notes:

  • You must add a new Control-M scheduler for each Control-M datacenter that you want to integrate into your AAI environment.
  • You can add the Control-M schedulers in AAI before installing the Control-M Connector. However, you will not be able to use them until the Connector is up and running.

Supported Control-M Objects

The Control-M integration into Automic Automation Intelligence supports the following objects:

  • Jobs

    A Control-M Job is a definition of a command to run. This definition includes the conditions, execution frequency, and the target machine in which to run the command.

  • Events

    A Control-M Event is the definition of a Job's state change, error, or success. These are used to determine if jobs succeeded, failed, and/or were retried. Dependent jobs occasionally use these events as conditions.

  • Folders (Smart, Simple, Complex and so on)

    A Control-M Folder is a container definition for Jobs and subfolders. Folders enable you to configure various settings such as scheduling, event management, resources, or notifications. Folder-level definitions are inherited by the Jobs or subfolders within the folder.

  • Resources

    A Control-M Resource is something that a Control-M Job depends on and use. Control-M Resources can be Logical or Quantitative. Logical Resources include physical drives, tables, or databases. Quantitative Resources is a physical or logical entity that you can count, such as a CPU, or Table/Data set.

  • Node

    A Control-M Node is a host computer that a Job is sent to, to be executed. Each Node is running a Control-M Agent that orchestrates and monitors the Job and its result.

For more information, please refer to the Control-M documentation at documents.bmc.com.

You can use those Control-M objects to carry out the following actions in Automic Automation Intelligence :

  • Create (SLA) for different jobstream setups (simple, complex and/or with external dependencies)
  • Locate a possible bottleneck in a jobstream (critical path)
  • Create dashboards

See also: