### 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)

"Set log level to DEBUG for traceback.",
                    container_name,
                    e,
                )
                self.log.debug(
                    "Traceback for interrupted logs read for pod %r",
                    pod.metadata.name,
                    exc_info=True,
                )
            return last_captured_timestamp or since_time
        
        
        
        last_log_time = since_time
        while True:
            last_log_time = consume_logs(
                since_time=last_log_time, follow=follow, termination_timeout=post_termination_timeout
            )
            if not self.container_is_running(pod, container_name=container_name):
                return PodLoggingStatus(running=False, last_log_time=last_log_time)
            if not follow:
                return PodLoggingStatus(running=True, last_log_time=last_log_time)
            else:
                self.log.warning(
                    "Pod %s log read interrupted but container %s still running",
                    pod.metadata.name,
                    container_name,
                )
                time.sleep(1)
    def fetch_requested_container_logs(