### 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)

fixture = sys.path[0] + "/tests/providers/cncf/kubernetes/basic_pod.yaml"
        pod_spec = k8s.V1Pod(
            metadata=k8s.V1ObjectMeta(
                labels={"test_label": test_label, "fizz": "buzz"},
            ),
            spec=k8s.V1PodSpec(
                containers=[
                    k8s.V1Container(
                        name="base",
                        env=[k8s.V1EnvVar(name="env_name", value="value")],
                    )
                ]
            ),
        )
        k = KubernetesPodOperator(
            task_id=str(uuid4()),
            labels=self.labels,
            in_cluster=False,
            pod_template_file=fixture,
            full_pod_spec=pod_spec,
            do_xcom_push=True,
        )