### 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)

from airflow.cli.cli_config import (
        ARG_DAG_ID,
        ARG_EXECUTION_DATE,
        ARG_OUTPUT_PATH,
        ARG_SUBDIR,
        ARG_VERBOSE,
        ActionCommand,
        Arg,
        GroupCommand,
        lazy_load_command,
        positive_int,
    )
except ImportError:
    try:
        from airflow import __version__ as airflow_version
    except ImportError:
        from airflow.version import version as airflow_version
    import packaging.version
    from airflow.exceptions import AirflowOptionalProviderFeatureException
    base_version = packaging.version.parse(airflow_version).base_version
    if packaging.version.parse(base_version) < packaging.version.parse("2.7.0"):
        raise AirflowOptionalProviderFeatureException(
            "Kubernetes Executor from CNCF Provider should only be used with Airflow 2.7.0+.\n"
            f"This is Airflow {airflow_version} and Kubernetes and CeleryKubernetesExecutor are "
            f"available in the 'airflow.executors' package. You should not use "
            f"the provider's executors in this version of Airflow."
        )
    raise
from airflow.configuration import conf
from airflow.executors.base_executor import BaseExecutor