### Description

Add a process_line callback to KubernetesPodOperator 
Like https://github.com/apache/airflow/blob/main/airflow/providers/apache/beam/operators/beam.py#LL304C36-L304C57 the `BeamRunPythonPipelineOperator`, which allows the user to add stateful plugins based on the logging from docker job 

### Use case/motivation

I can add a plugin based on the logging and also allow cleanup on_kill based on the job creation log. 

### Related issues

_No response_

### Are you willing to submit a PR?

- [ ] Yes I am willing to submit a PR!

### Code of Conduct

- [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

"""When we expect to be able to find a pod but cannot."""
class KubernetesPodOperator(BaseOperator):
    """
    Execute a task in a Kubernetes Pod.
    .. seealso::
        For more information on how to use this operator, take a look at the guide:
        :ref:`howto/operator:KubernetesPodOperator`
    .. note::
        If you use `Google Kubernetes Engine <https://cloud.google.com/kubernetes-engine/>`__
        and Airflow is not running in the same cluster, consider using
        :class:`~airflow.providers.google.cloud.operators.kubernetes_engine.GKEStartPodOperator`, which
        simplifies the authorization process.
    :param kubernetes_conn_id: The :ref:`kubernetes connection id <howto/connection:kubernetes>`
        for the Kubernetes cluster.
    :param namespace: the namespace to run within kubernetes.
    :param image: Docker image you wish to launch. Defaults to hub.docker.com,
        but fully qualified URLS will point to custom repositories. (templated)
    :param name: name of the pod in which the task will run, will be used (plus a random