> ## Documentation Index
> Fetch the complete documentation index at: https://docs.nx1cloud.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Monitor

> Overview of NexusOne's Monitor feature used for managing Airflow DAGs represented as jobs.

The Monitor feature allows you to view *jobs* within NexusOne. On the NexusOne portal, a job is a
summarized view of an [Apache Airflow](/platform-components/apache-airflow) DAG.
When a user clicks on a job, it displays a page to a DAG on Apache Airflow.

## Key features

* **Centralized job monitoring**: You can view the status of a job. This includes:

  * **New**: Successful job creation but it hasn't executed yet.
  * **Running**: The job has executed and is currently in progress.
  * **Completed**: The job completed successfully.
  * **Failed**: The job failed.

* **Job types**: There are different job types. This includes:

  * **Ingestion**: Ingested database, file, or lakehouse.
  * **Data engineering**: Rules to transform your data.
  * **Ask**: Rules to get insights from your data.
  * **Data mirroring**: Mirrored database in real time.

* **Role-based access control**: Depending on the role assigned to you by your administrator,
  you might have varying levels of visibility:

  * **nx1\_monitor**: This role ensures you can view your jobs.
  * **nx1\_monitor\_admin**: This role ensures that an administrator can view jobs from all users.

## Use cases

These examples show how different industries can use NexusOne's monitor capabilities:

* **Financial services**: Monitor scheduled jobs that generate recurring reports such as income statements and regulatory
  filings submitted to government authorities or other regulatory bodies.
* **Education**: Monitor scheduled jobs for ingested student records.

## Additional resources

* For more information about data ingestion, refer to [Ingest Overview](/documentation/data-pipeline/overview/ingest).
* For more information about data insights, refer to [Ask Overview](/documentation/ai/overview/ask).
* For more information about data transformation, refer to [Engineer Overview](/documentation/data-pipeline/overview/engineer).