### 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 setup_method(self):
        self.mock_kube_client = mock.Mock()
        self.pod_manager = PodManager(kube_client=self.mock_kube_client)
    def test_read_pod_logs_successfully_returns_logs(self):
        mock.sentinel.metadata = mock.MagicMock()
        self.mock_kube_client.read_namespaced_pod_log.return_value = mock.sentinel.logs
        logs = self.pod_manager.read_pod_logs(pod=mock.sentinel, container_name="base")
        assert type(logs) == PodLogsConsumer
        assert logs.response == mock.sentinel.logs
    def test_read_pod_logs_retries_successfully(self):