### Apache Airflow version

Other Airflow 2 version (please specify below)

### What happened

We are experiencing issue with error log message being shown in every task that is KubernetesPodOperator. We get 

```
{pod_manager.py:558} ERROR - Error parsing timestamp (no timestamp in message ''). Will continue execution but won't update timestamp
```

after execution is finished in every task.

### What you think should happen instead

No such error should be shown

### How to reproduce

```python
'''doc'''
from kubernetes.client import models as k8s
from airflow.providers.cncf.kubernetes.operators.pod import KubernetesPodOperator
from airflow.models import DAG
import pendulum
import datetime

DAG_ID = 'test-dag'

default_args = {
	'owner': 'owner',
	'depends_on_past': False,
	'start_date': datetime.datetime(2023, 9, 15),
	'sla': datetime.timedelta(hours = 1),
	'execution_timeout': datetime.timedelta(hours = 1, minutes = 30),
	'email_on_failure': False,
	'email_on_retry': False,
	'retries': 3,
	'retry_delay': datetime.timedelta(minutes = 1),
	'retry_exponential_backoff': True,
	'max_retry_delay': datetime.timedelta(minutes = 10),
	'max_active_tis_per_dag': 8,
	'pool': 'SomePool',
	'get_logs': True,
}

dag = DAG(
	dag_id = DAG_ID,
	doc_md = __doc__,
	tags = ['tag'],
	schedule = AfterWorkdayTimetable(pendulum.Time(2, 0)),
	default_args = default_args,
	catchup = True,
	dagrun_timeout = datetime.timedelta(hours = 6),
	max_active_runs = 5
)

task = KubernetesPodOperator(
	affinity = {
		'nodeAffinity': {
			'requiredDuringSchedulingIgnoredDuringExecution': {
				'nodeSelectorTerms': [
					{'matchExpressions': [{'key': 'dataDriveSizeClass', 'operator': 'In', 'values': ['large', 'medium']}]}
				]
			}
		}
	},
	priority_class_name = 'l3',
	namespace = 'some--namespace',
	in_cluster = True,
	image_pull_policy = 'IfNotPresent',
	container_resources = k8s.V1ResourceRequirements(
		requests = {'memory': '150Mi', 'cpu': '1m'},
		limits = {'memory': '512Mi', 'cpu': '500m'},
	),
	cmds = [
		'sleep',
		'10'
	],
	dag = dag,
	task_id = 'kubernetes_task',
	labels = {
		'runner': 'airflow',
	},
	annotations = {'version': '1.0.0'},
	image = 'ubuntu',
	env_vars = [k8s.V1EnvVar(name = name, value = value) for name, value in {'name':'value'}.items()]
)

task
```

### Operating System

Debian GNU/Linux 10 (buster)

### Versions of Apache Airflow Providers

```
apache-airflow-providers-amazon==8.4.0
apache-airflow-providers-cncf-kubernetes==7.5.1
apache-airflow-providers-common-sql==1.6.1
apache-airflow-providers-ftp==3.4.2
apache-airflow-providers-http==4.5.0
apache-airflow-providers-imap==3.2.2
apache-airflow-providers-postgres==5.6.0
apache-airflow-providers-slack==7.3.2
apache-airflow-providers-sqlite==3.4.3
```

### Deployment

Other Docker-based deployment

### Deployment details

Kubernetes 1.26.5
airflow 2.6.3
python 3.10.12
LocalExecutor
Database: Postgres 14.6

### Anything else

_No response_

### Are you willing to submit 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)

pod_name_too_long = "a" * 221
        with pytest.raises(AirflowException):
            KubernetesPodOperator(
                namespace="default",
                image="ubuntu:16.04",
                cmds=["bash", "-cx"],
                arguments=["echo 10"],
                labels=self.labels,
                name=pod_name_too_long,
                task_id=str(uuid4()),
                in_cluster=False,
                do_xcom_push=False,
            )
    def test_on_kill(self, mock_get_connection):