### 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)

"""
    Responsible for pulling pod logs from a stream with checking a container status before reading data.
    This class is a workaround for the issue https://github.com/apache/airflow/issues/23497.
    :param response: HTTP response with logs
    :param pod: Pod instance from Kubernetes client
    :param pod_manager: Pod manager instance
    :param container_name: Name of the container that we're reading logs from
    :param post_termination_timeout: (Optional) The period of time in seconds representing for how long time
        logs are available after the container termination.
    :param read_pod_cache_timeout: (Optional) The container's status cache lifetime.
        The container status is cached to reduce API calls.
    :meta private:
    """
    def __init__(