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Control-M for Apache Airflow

Apache Airflow enables you to monitor and manage Directed Acyclic Graphs (DAGs) workflows in Control-M.

Control-M for Apache Airflow enables you to do the following:

  • Manage Apache Airflow credentials in a secure connection profile.
  • Connect to any Apache Airflow endpoint.
  • Introduce all Control-M capabilities to Control-M for Apache Airflow, including advanced scheduling criteria, complex dependencies, Resource Pools, Lock Resources, and variables.
  • Integrate Apache Airflow jobs with other Control-M jobs into a single scheduling environment.
  • Monitor the job status, results, and output of Apache Airflow.
  • Attach an SLA job to the Apache Airflow jobs.

Setting up Control-M for Apache Airflow

This procedure describes how to install the Apache Airflow plug-in, create a connection profile, and define an Apache Airflow job in Helix Control-M and Automation API.

Before You Begin

  • Verify that Automation API is installed, as described in Setting up the API.
  • Verify that Agent version 9.0.21.080 or later is installed.

Begin

  1. On the Agent host, set the Java environment variable by running one of the following commands through a command line:
    • Linux:
      • Bourne shell/bash: export BMC_INST_JAVA_HOME=<java_11_directory>
      • csh/tcsh: setenv BMC_INST_JAVA_HOME <java_11_directory>
    • Windows: set BMC_INST_JAVA_HOME="<java_11_directory>"
  2. Run one of the following API commands:
    • For a fresh installation, use the provision image command:
      • Linux: ctm provision image Apache_Airflow_plugin.Linux
      • Windows: ctm provision image Apache_Airflow_plugin.Windows
    • For an upgrade, use the following command:
      ctm provision agent::update
  3. Create an Apache Airflow connection profile in Helix Control-M or Automation API, as follows:
  4. Define an Apache Airflow job in Helix Control-M or Automation API, as follows:
Warning

Note

To remove this plug-in from an Agent, see Removing a Plug-in. The plug-in ID is AAF112024.

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

Rerun DAG action added.

 

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