### 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)

volume_mounts = [
            k8s.V1VolumeMount(mount_path="/etc/foo", name="test-volume", sub_path=None, read_only=True)
        ]
        init_environments = [
            k8s.V1EnvVar(name="key1", value="value1"),
            k8s.V1EnvVar(name="key2", value="value2"),
        ]
        init_container = k8s.V1Container(
            name="init-container",
            image="ubuntu:16.04",
            env=init_environments,
            volume_mounts=volume_mounts,
            command=["bash", "-cx"],
            args=["echo 10"],
        )
        volume = k8s.V1Volume(
            name="test-volume",
            persistent_volume_claim=k8s.V1PersistentVolumeClaimVolumeSource(claim_name="test-volume"),
        )
        expected_init_container = {
            "name": "init-container",
            "image": "ubuntu:16.04",
            "command": ["bash", "-cx"],