**Update**

We discussed and decide this CLI should always only clean up pods created by Airflow.

<hr>

### Description

Currently command `kubernetes cleanup-pods` cleans up Pods that meet specific conditions in a given namespace.

Underlying code: https://github.com/apache/airflow/blob/2.0.1/airflow/cli/commands/kubernetes_command.py#L70

### Use case / motivation

The problem to me is: users may have other non-Airflow stuff running in this specific namespace, and they may want to have different strategy/logic for Pod cleaning-up for these non-Airflow pods.

We may want to have an additional boolean flag for this command, like `--only-airflow-pods`, so that users can decide if they only want to clean up Airflow-created Pods.

It should not be hard to identify Airflow-created pods, given the specific labels Airflow adds to the Pods it creates (https://github.com/apache/airflow/blob/2.0.1/airflow/kubernetes/pod_generator.py#L385)




airflow/cli/cli_parser.py
func=lazy_load_command('airflow.cli.commands.dag_command.dag_delete'),
        args=(ARG_DAG_ID, ARG_YES),
    ),
    ActionCommand(
        name='show',
        help="Displays DAG's tasks with their dependencies",
        description=(
            "The --imgcat option only works in iTerm.\n"
            "\n"
            "For more information, see: https://www.iterm2.com/documentation-images.html\n"
            "\n"
            "The --save option saves the result to the indicated file.\n"
            "\n"
            "The file format is determined by the file extension. "
            "For more information about supported "
            "format, see: https://www.graphviz.org/doc/info/output.html\n"
            "\n"
            "If you want to create a PNG file then you should execute the following command:\n"
            "airflow dags show <DAG_ID> --save output.png\n"
            "\n"
            "If you want to create a DOT file then you should execute the following command:\n"
            "airflow dags show <DAG_ID> --save output.dot\n"
        ),
        func=lazy_load_command('airflow.cli.commands.dag_command.dag_show'),
        args=(
            ARG_DAG_ID,
            ARG_SUBDIR,
            ARG_SAVE,
            ARG_IMGCAT,
        ),