Job Status

When you view the list of jobs in the JobsJob Instances view or when you monitor a job, you can view the job status. You can also view the status of remote pipeline instances run from active jobs.

The job status is color-coded, providing an easy visual indicator of which jobs need your attention. A red status indicates that an error has occurred that you must resolve. A green status indicates that all is well.
Note: A job template is simply a job definition and does not have a status.

The following table describes each job status:

Job Status Description
Job is inactive. A job transitions from an active to an inactive status when you stop the job or when all remote pipeline instances run from the job have reached a finished state.
Job is inactive after stopping automatically due to an error.

For example, a red inactive status can occur when either the pipeline or Data Collector generates an error that causes Control Hub to stop the job.

Job is inactive and has an error that you must acknowledge.

This status can occur when at least one execution engine reported an error while attempting to stop the remote pipeline instance. For example, one Data Collector might have shut down and so could not properly stop the remote pipeline instance.

You cannot perform actions on jobs with an inactive_error status until you acknowledge the error message. To acknowledge the error, view the job details or monitor the job and acknowledge reading the error message. For more information, see Acknowledging Job Errors.
Control Hub is in the process of starting the job.

You cannot perform actions on activating jobs.
Job is active and remote pipeline instances are running on the execution engines assigned the same labels as the job.
Job is active, but there are some issues you must look into.
For example, a red active status can indicate one of the following issues:
  • One of the assigned execution engines is not currently running.
  • One of the assigned execution engines encountered an error while running the pipeline.
  • All assigned execution engines have exceeded their resource thresholds.
  • The Data Collector pipeline is running and is configured to write statistics to Amazon Kinesis Streams, Kafka, MapR Streams, or SDC RPC, but the system pipeline is not running.
Control Hub is in the process of stopping a job as requested or as expected. Control Hub is communicating with the execution engines to stop all remote pipeline instances.

You cannot perform actions on deactivating jobs.
Control Hub is in the process of stopping a job automatically due to an error. Control Hub is communicating with the execution engines to stop all remote pipeline instances.

You cannot perform actions on deactivating jobs.