**Apache Airflow version**: 2.0.0a2

**Kubernetes version (if you are using kubernetes)** (use `kubectl version`): v1.15.12

**Environment**:
- **OS** (e.g. from /etc/os-release): CentOS 7


**What happened**:

When using KubernetesExecutor, a single SIGTERM doesn't result in the scheduler actually exiting cleanly. However, it will exit after receiving a second SIGTERM.

The same behavior happens if you have an exception in the scheduler. An easy way to replicate it is to raise in `pod_mutation_hook`.

In practice, this means the scheduler doesn't get restarted by K8s after encountering a exception. Or, when terminating the scheduler pod, it sticks around until k8s ultimately sends it a SIGKILL after its grace period is up.

**What you expected to happen**:

The scheduler to exit after a single SIGTERM.

**How to reproduce it**:
The easiest way to reproduce it is to simply send a SIGKILL to your KubernetesExecutor scheduler pod:

```
$ kubectl exec {scheduler_pod_name} kill 1
```

Note, the pod stays running, while the logs report:

```
[2020-10-30 17:34:09,581] {scheduler_job.py:794} INFO - Exiting gracefully upon receiving signal 15
[2020-10-30 17:34:10,586] {process_utils.py:97} INFO - Sending Signals.SIGTERM to GPID 59
[2020-10-30 17:34:10,879] {process_utils.py:63} INFO - Process psutil.Process(pid=59, status='terminated', exitcode=0, started=
'17:33:23') (59) terminated with exit code 0
[2020-10-30 17:34:10,882] {process_utils.py:97} INFO - Sending Signals.SIGTERM to GPID 59
[2020-10-30 17:34:10,882] {scheduler_job.py:1329} INFO - Exited execute loop
```

Issue another `kill`:
```
$ kubectl exec {scheduler_pod_name} kill 1
```

And the pod will be restarted by k8s.

If you can't reproduce it, let me know and I'll try and get something running on kind.

**Anything else we need to know**:

The same behavior happens if you have an exception in the scheduler. An easy way to replicate it is to raise in a `pod_mutation_hook`.


tests/jobs/test_scheduler_job.py
non_serialized_dagbag = DagBag(read_dags_from_db=False, include_examples=False)
        non_serialized_dagbag.sync_to_db()
        cls.dagbag = DagBag(read_dags_from_db=True)
    def test_dag_file_processor_sla_miss_callback(self):
        """
        Test that the dag file processor calls the sla miss callback
        """
        session = settings.Session()
        sla_callback = MagicMock()
        
        
        test_start_date = days_ago(1)
        dag = DAG(
            dag_id='test_sla_miss',
            sla_miss_callback=sla_callback,
            default_args={'start_date': test_start_date, 'sla': datetime.timedelta()},
        )
        task = DummyOperator(task_id='dummy', dag=dag, owner='airflow')
        session.merge(TaskInstance(task=task, execution_date=test_start_date, state='success'))
        session.merge(SlaMiss(task_id='dummy', dag_id='test_sla_miss', execution_date=test_start_date))
        dag_file_processor = DagFileProcessor(dag_ids=[], log=mock.MagicMock())
        dag_file_processor.manage_slas(dag=dag, session=session)
        assert sla_callback.called
    def test_dag_file_processor_sla_miss_callback_invalid_sla(self):