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Interacting with data migration pipelines

Updated on February 4, 2021

Create and run data migration pipelines in Deployment Manager 5.1.x to automatically export simulation data from a production environment into a simulation environment in which you can test simulation data. You can also use Deployment Manager to monitor and obtain information about your simulations, for example, by running diagnostics to ensure that your environment configurations are correct and by and viewing reports that display key performance indicators (KPIs).

  • Starting a pipeline manually

    If you do not run a data migration pipeline based on a job scheduler, you can run it manually in Deployment Manager.

  • Pausing a pipeline

    Pause a pipeline to stop processing the data migration. When you pause a data migration, the pipeline completes the current task and stops the data migration.

  • Stopping a pipeline

    Stop a pipeline to stop data migrations from being exported and imported.

  • Stopping and resuming a pipeline that has errors

    If a data migration has errors, the pipeline stops processing on it, and you can either resume or stop running the pipeline.

  • Deleting a pipeline

    When you delete a pipeline, its associated application packages are not deleted from the pipeline repositories.

  • Viewing data migration logs

    View the logs for a data migration to see the completion status of operations, for example, when a data migration moves to a new stage. You can change the logging level to control the events are displayed in the log. For example, you can change logging levels of your deployment from INFO to DEBUG for troubleshooting purposes. For more information, see Logging Level Settings tool.

  • Viewing a report for a specific data migration

    You can view a report for a specific data migration to gain more visibility into data migrations on a pipeline.

  • Viewing reports for all data migrations in a pipeline

    Reports provide a variety of information about all the data migrations in your pipeline so that you can gain more visibility into data migration processing. For example, you can view the average time taken to complete data migrations.

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