### 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)

self, pod: V1Pod, container_logs: Iterable[str] | str | Literal[True], follow_logs=False
    ) -> list[PodLoggingStatus]:
        """
        Follow the logs of containers in the specified pod and publish it to airflow logging.
        Returns when all the containers exit.
        """
        pod_logging_statuses = []
        all_containers = self.get_container_names(pod)
        if all_containers:
            if isinstance(container_logs, str):
                
                if container_logs in all_containers:
                    status = self.fetch_container_logs(
                        pod=pod, container_name=container_logs, follow=follow_logs
                    )
                    pod_logging_statuses.append(status)
                else:
                    self.log.error(
                        "container %s whose logs were requested not found in the pod %s",
                        container_logs,
                        pod.metadata.name,
                    )
            elif isinstance(container_logs, bool):
                
                if container_logs is True:
                    for container_name in all_containers:
                        status = self.fetch_container_logs(