Control-M for Azure Data Factory
Azure Data Factory is a cloud-based extract, transform, load (ETL) and data integration service that allows you to create data-driven workflows to automate the movement and transformation of data.
Control-M for Azure Data Factory enables you to do the following:
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Execute Azure Data Factory jobs.
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Manage Azure Data Factory credentials in a secure connection profile.
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Connect to any Azure Data Factory endpoint.
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Introduce all Control-M capabilities to Control-M for Azure Data Factory, including advanced scheduling criteria, complex dependencies, resource pools, lock resources, and variables.
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Integrate Azure Data Factory jobs with other Control-M jobs into a single scheduling environment.
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Monitor the status, results, and output of Azure Data Factory jobs.
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Attach an SLA job to the Azure Data Factory jobs.
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Run 100 Azure Data Factory jobs simultaneously per Agent.
Control-M for Azure Data Factory Compatibility
The following table lists the prerequisites that are required to use the Azure Data Factory plug-in, each with its minimum required version.
|
Component |
Version |
|---|---|
|
Control-M/EM |
9.0.22.000 |
|
Control-M/Agent |
9.0.22.052 |
|
Control-M Application Integrator |
9.0.22.052 |
|
Control-M Automation API |
9.0.22.050 |
Control-M for Azure Data Factory is supported on Control-M Web and Control-M Automation API, but not on the Control-M client.
To download the installation files for each prerequisite, see Obtaining Control-M Installation Files.
Setting up Control-M for Azure Data Factory
This procedure describes how to deploy the Azure Data Factory plug-in, create a connection profile, and define an Azure Data Factory job in
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.
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Verify that Automation API is installed, as described in Automation API Installation.
Begin
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Create a temporary directory to save the downloaded files.
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Download the Azure Data Factory plug-in from the Control-M for Azure Data Factory download page in the EPD site.
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Do one of the following to install the Azure Data Factory plug-in:
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(9.0.21 or higher) Do the following to run the Control-M Automation API provision service:
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Log in as an administrator to the Control-M/EM server host and save the downloaded ZIP file to the following location:
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Linux: $HOME/ctm_em/AUTO_DEPLOY
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Windows: <EM_HOME>\AUTO_DEPLOY
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Log in to the account where Control-M/Agent is installed and run the following provision image command:
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Linux: ctm provision image ADF_plugin.Linux
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Windows: ctm provision image ADF_plugin.Windows
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-
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(9.0.20.200 or lower) Run the Control-M Automation API deploy service, as described in deploy jobtype.
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Create an Azure Data Factory connection profile in Control-M Web or Automation API, as follows:
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Define an Azure Data Factory job in Control-M Web or Automation API, as follows:
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Automation API: Job:ADF (Azure Data Factory)
To remove this plug-in from an Agent, see Removing a Plug-in from the Agent. The plug-in ID is ADF062021.
Change Log
The following table provides details about changes that were introduced in new versions of this plug-in:
|
Plug-in Version |
Details |
|---|---|
|
1.0.08 |
Added Workload Identity as a new Identity Type in centralized connection profile |
|
1.0.07 |
Runtime performance improvements. |
|
1.0.06 |
|
|
1.0.05 |
Added resolve on rerun for job parameters |
|
1.0.04 |
|
|
1.0.03 |
Fixed the abort operation for REST API steps |
|
1.0.02 |
New job icon |
|
1.0.00 |
Initial version |
