### Apache Airflow version

main (development)

### What happened

_list_pods function uses kube list_namespaced_pod and list_pod_for_all_namespaces kube functions. Right now, these Kube functions will get the entire pod spec though we are interested in the pod metadata alone. This _list_pods is refered in clear_not_launched_queued_tasks. try_adopt_task_instances and _adopt_completed_pods functions.

When we run the airflow at large scale (with worker pods of more than > 500). The _list_pods function takes a significant amount of time (upto 15 - 30 seconds with 500 worker pods) due to unnecessary data transfer (V1PodList up to a few 10 MBs) and JSON deserialization overhead. This is blocking us from scaling the airflow to run at large scale

### What you think should happen instead

Request the Pod metadata instead of entire Pod payload. It will help to reduce significant network data transfer and JSON deserialization overhead.

### How to reproduce

I have reproduced the performance issue while running 500 concurrent jobs. Monitor  kubernetes_executor.clear_not_launched_queued_tasks.duration and kubernetes_executor.adopt_task_instances.duration metrics.

### Operating System

CentOS 6

### Versions of Apache Airflow Providers

apache-airflow-providers-cncf-kubernetes

### Deployment

Other Docker-based deployment

### Deployment details

Terraform based airflow deployment

### Anything else

_No response_

### Are you willing to submit PR?

- [X] 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)

if TYPE_CHECKING:
            assert self.result_queue
        self.log.debug("Executor shutting down, result_queue approximate size=%d", self.result_queue.qsize())
        with contextlib.suppress(Empty):
            while True:
                results = self.result_queue.get_nowait()
                self.log.warning("Executor shutting down, flushing results=%s", results)
                try:
                    key, state, pod_name, namespace, resource_version = results
                    self.log.info(
                        "Changing state of %s to %s : resource_version=%d", results, state, resource_version
                    )
                    try:
                        self._change_state(key, state, pod_name, namespace)
                    except Exception as e:
                        self.log.exception(
                            "Ignoring exception: %s when attempting to change state of %s to %s.",
                            e,
                            results,
                            state,
                        )
                finally:
                    self.result_queue.task_done()
    def end(self) -> None: