Management hub in Azure Data Factory

APPLIES TO: Azure Data Factory Azure Synapse Analytics


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The management hub, accessed by the Manage tab in the Azure Data Factory UX, is a portal that hosts global management actions for your data factory. Here, you can manage your connections to data stores and external computes, source control configuration, and trigger settings.

Manage connections

Linked services

Linked services define the connection information for Azure Data Factory to connect to external data stores and compute environments. For more information, see linked services concepts. Linked service creation, editing, and deletion is done in the management hub.

Manage linked services

Integration runtimes

An integration runtime is a compute infrastructure used by Azure Data Factory to provide data integration capabilities across different network environments. For more information, learn about integration runtime concepts. In the management hub, you can create, delete, and monitor your integration runtimes.

Manage integration runtimes

Manage source control

Git configuration

You can view/ edit all the Git-related information under the Git configuration settings in the management hub.

Last published commit information is listed as well and can help to understand the precise commit, which was last published/ deployed across environments. It can also be helpful when doing Hot Fixes in production.

For more information, learn about source control in Azure Data Factory.

Manage git repo

Parameterization template

To override the generated Resource Manager template parameters when publishing from the collaboration branch, you can generate or edit a custom parameters file. For more information, learn how to use custom parameters in the Resource Manager template. The parameterization template is only available when working in a git repository. If the arm-template-parameters-definition.json file doesn't exist in the working branch, editing the default template will generate it.

Manage custom params

Manage authoring


Triggers determine when a pipeline run should be kicked off. Currently triggers can be on a wall clock schedule, operate on a periodic interval, or depend on an event. For more information, learn about trigger execution. In the management hub, you can create, edit, delete, or view the current state of a trigger.

Screenshot that shows where to create, edit, delete, nor view the current state of a trigger.

Global parameters

Global parameters are constants across a data factory that can be consumed by a pipeline in any expression. For more information, learn about global parameters.

Create global parameters

Learn how to configure a git repository to your ADF