### Official Helm Chart version

1.7.0

### Apache Airflow version

2.4.0

### Kubernetes Version

K3s Kubernetes Version: v1.24.2+k3s2

### Helm Chart configuration

_No response_

### Docker Image customizations

_No response_

### What happened



Same as https://github.com/apache/airflow/issues/12229 
```
[2023-03-31T17:47:08.304+0000] {kubernetes_executor.py:112} ERROR - Unknown error in KubernetesJobWatcher. Failing
Traceback (most recent call last):
  File "/home/airflow/.local/lib/python3.10/site-packages/airflow/executors/kubernetes_executor.py", line 103, in run
    self.resource_version = self._run(
  File "/home/airflow/.local/lib/python3.10/site-packages/airflow/executors/kubernetes_executor.py", line 148, in _run
    for event in list_worker_pods():
  File "/home/airflow/.local/lib/python3.10/site-packages/kubernetes/watch/watch.py", line 182, in stream
    raise client.rest.ApiException(
kubernetes.client.exceptions.ApiException: (410)
Reason: Expired: too old resource version: 202541353 (202544371)

Process KubernetesJobWatcher-3:
Traceback (most recent call last):
  File "/usr/local/lib/python3.10/multiprocessing/process.py", line 314, in _bootstrap
    self.run()
  File "/home/airflow/.local/lib/python3.10/site-packages/airflow/executors/kubernetes_executor.py", line 103, in run
    self.resource_version = self._run(
  File "/home/airflow/.local/lib/python3.10/site-packages/airflow/executors/kubernetes_executor.py", line 148, in _run
    for event in list_worker_pods():
  File "/home/airflow/.local/lib/python3.10/site-packages/kubernetes/watch/watch.py", line 182, in stream
    raise client.rest.ApiException(
kubernetes.client.exceptions.ApiException: (410)
Reason: Expired: too old resource version: 202541353 (202544371)

[2023-03-31T17:47:08.832+0000] {kubernetes_executor.py:291} ERROR - Error while health checking kube watcher process. Process died for unknown reasons
```

### What you think should happen instead

no errors in the logs?

### How to reproduce

appears soon after AF-scheduler pod restart

### 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)

"""Check if any pending worker pods have timed out."""
        if TYPE_CHECKING:
            assert self.scheduler_job_id
        timeout = self.kube_config.worker_pods_pending_timeout
        self.log.debug("Looking for pending worker pods older than %d seconds", timeout)
        kwargs = {
            "limit": self.kube_config.worker_pods_pending_timeout_batch_size,
            "field_selector": "status.phase=Pending",
            "label_selector": f"airflow-worker={self.scheduler_job_id}",
            **self.kube_config.kube_client_request_args,
        }
        pending_pods = self._list_pods(kwargs)
        cutoff = timezone.utcnow() - timedelta(seconds=timeout)
        for pod in pending_pods:
            self.log.debug(
                'Found a pending pod "%s", created "%s"', pod.metadata.name, pod.metadata.creation_timestamp
            )
            if pod.metadata.creation_timestamp < cutoff:
                self.log.error(
                    (
                        'Pod "%s" has been pending for longer than %d seconds.'
                        "It will be deleted and set to failed."
                    ),
                    pod.metadata.name,
                    timeout,
                )
                self.kube_scheduler.delete_pod(pod.metadata.name, pod.metadata.namespace)
    def _change_state(self, key: TaskInstanceKey, state: str | None, pod_id: str, namespace: str) -> None: