More Options or Features of Data Pipeline Studio

The home page of the Data Pipeline Studio provides a set of useful features which you can access from the ellipsis (...) in the top right corner of the screen.

Option Description
Schedule Run Schedule a pipeline run with the required recurrence.
Promote Promote the pipeline to the next stage.
Deploy Deploy the tech stacks used for pipeline creation.
Manage Notifications

You can receive notifications for actions like failed or successful data pipeline runs, changes in data pipeline, aborting a data pipeline run, promoting a data pipeline to next stage and so on.

You can configure the following types of notifications:

For SNS and SQS you must configure the tools from Systems Integration under Cloud Platform Tools and Technologies. See Configure Amazon SNS and Configure Amazon SQS for detailed instructions.

Manage Wheel Package

Manage Wheel Package lets you upgrade to a latest available version of wheel package or change to any available wheel package version.

Audit Logs Logs each event in Data Pipeline Studio. See Audit Logs in Data Pipeline Studio.
Pipeline Run Timeout

You can set the time after which a pipeline that is running is timed out. Click the option and provide the following details:

  • Default rerun attempts for all nodes of the pipeline - Specify the maximum number of times the node is rerun in case of failure.

  • Pipeline Run Timeout - Specify the duration after which the pipeline run is timed out, irrespective of the run status. In case this parameter is not specified, then default setting of 24 hours is considered.

  • Note:

    Depending on the start time of the pipeline run, the pipeline run timeout limit may exceed by a maximum of 5 minutes, which is the threshold limit of the pipeline scheduler.

 

Dependent Pipelines Shows the number of pipelines that are dependent on this pipeline.
Export as File Export a data pipeline as a file.
Export as Template Export a data pipeline as a template.
Import Template Import a data pipeline template to create a new pipeline based on the template.

 

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What's next? Create a Data Pipeline