### 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)

def __getattr__(self, name):
            raise KeyError(name)
    context = {
        "password": "secretpassword",
        "var": Var(),
    }
    from airflow.providers.cncf.kubernetes.operators.pod import (
        KubernetesPodOperator,
    )
    task = KubernetesPodOperator(
        task_id="dry_run_demo",
        name="hello-dry-run",
        image="python:3.8-slim-buster",
        cmds=["printenv"],
        env_vars=[
            V1EnvVar(name="password", value="{{ password }}"),
            V1EnvVar(name="VAR2", value="{{ var.value.nonexisting}}"),
        ],
    )
    with pytest.raises(KeyError):
        task.render_template_fields(context=context)
    assert "password" in caplog.text
    assert "secretpassword" not in caplog.text
class TestKubernetesPodOperator(BaseK8STest):