**Apache Airflow version**: 2.0.1
**Kubernetes version**: v1.19.7
**Executor**: KubernetesExecutor

**What happened**:

If you have a worker that gets stuck in pending forever, say with a missing volume mount, the task will stay in the queued state forever. Nothing is applying a timeout on it actually being able to start.

**What you expected to happen**:

Eventually the scheduler will notice that the worker hasn't progressed past pending after a given amount of time and will mark it as a failure.

**How to reproduce it**:
```python
from airflow import DAG
from airflow.operators.bash import BashOperator
from airflow.utils.dates import days_ago
from kubernetes.client import models as k8s


default_args = {
    "owner": "airflow",
}

with DAG(
    dag_id="pending",
    default_args=default_args,
    schedule_interval=None,
    start_date=days_ago(2),
) as dag:
    BashOperator(
        task_id="forever_pending",
        bash_command="date; sleep 30; date",
        executor_config={
            "pod_override": k8s.V1Pod(
                spec=k8s.V1PodSpec(
                    containers=[
                        k8s.V1Container(
                            name="base",
                            volume_mounts=[
                                k8s.V1VolumeMount(mount_path="/foo/", name="vol")
                            ],
                        )
                    ],
                    volumes=[
                        k8s.V1Volume(
                            name="vol",
                            persistent_volume_claim=k8s.V1PersistentVolumeClaimVolumeSource(
                                claim_name="missing"
                            ),
                        )
                    ],
                )
            ),
        },
    )
```


**Anything else we need to know**:
Related to:

* #15149 (This is reporting that these pending pods don't get deleted via "Mark Failed")
* #14556 (This handles when these pending pods get deleted and is already fixed)

tests/executors/test_kubernetes_executor.py
pod_template_file_path = "/bar/biz"
        get_base_pod_from_template(pod_template_file_path, None)
        assert "deserialize_model_dict" == mock_generator.mock_calls[0][0]
        assert pod_template_file_path == mock_generator.mock_calls[0][1][0]
        mock_kubeconfig.pod_template_file = "/foo/bar"
        get_base_pod_from_template(None, mock_kubeconfig)
        assert "deserialize_model_dict" == mock_generator.mock_calls[1][0]
        assert "/foo/bar" == mock_generator.mock_calls[1][1][0]
    def test_make_safe_label_value(self):
        for dag_id, task_id in self._cases():
            safe_dag_id = pod_generator.make_safe_label_value(dag_id)
            assert self._is_safe_label_value(safe_dag_id)
            safe_task_id = pod_generator.make_safe_label_value(task_id)
            assert self._is_safe_label_value(safe_task_id)
            dag_id = "my_dag_id"
            assert dag_id == pod_generator.make_safe_label_value(dag_id)
            dag_id = "my_dag_id_" + "a" * 64
            assert "my_dag_id_" + "a" * 43 + "-0ce114c45" == pod_generator.make_safe_label_value(dag_id)
    def test_execution_date_serialize_deserialize(self):
        datetime_obj = datetime.now()
        serialized_datetime = pod_generator.datetime_to_label_safe_datestring(datetime_obj)
        new_datetime_obj = pod_generator.label_safe_datestring_to_datetime(serialized_datetime)
        assert datetime_obj == new_datetime_obj
class TestKubernetesExecutor(unittest.TestCase):