### 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)

#
#
from __future__ import annotations
import json
import logging
import os
import shutil
import sys
from copy import copy
from tempfile import NamedTemporaryFile
from unittest import mock
from unittest.mock import ANY, MagicMock
from uuid import uuid4
import pendulum
import pytest
from kubernetes import client
from kubernetes.client import V1EnvVar, V1PodSecurityContext, V1SecurityContext, models as k8s
from kubernetes.client.api_client import ApiClient
from kubernetes.client.rest import ApiException
from pytest import param
from airflow.exceptions import AirflowException, AirflowSkipException
from airflow.models import DAG, Connection, DagRun, TaskInstance
from airflow.providers.cncf.kubernetes.hooks.kubernetes import KubernetesHook
from airflow.providers.cncf.kubernetes.operators.pod import KubernetesPodOperator