**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
"""Test SLA Callbacks are not sent when no task SLAs are defined"""
        dag_id = 'test_send_sla_callbacks_to_processor_sla_no_task_slas'
        dag = DAG(dag_id=dag_id, start_date=DEFAULT_DATE, schedule_interval='@daily')
        DummyOperator(task_id='task1', dag=dag)
        with patch.object(settings, "CHECK_SLAS", True):
            self.scheduler_job = SchedulerJob(subdir=os.devnull)
            mock_agent = mock.MagicMock()
            self.scheduler_job.processor_agent = mock_agent
            self.scheduler_job._send_sla_callbacks_to_processor(dag)
            self.scheduler_job.processor_agent.send_sla_callback_request_to_execute.assert_not_called()
    def test_send_sla_callbacks_to_processor_sla_with_task_slas(self):
        """Test SLA Callbacks are sent to the DAG Processor when SLAs are defined on tasks"""
        dag_id = 'test_send_sla_callbacks_to_processor_sla_with_task_slas'
        dag = DAG(dag_id=dag_id, start_date=DEFAULT_DATE, schedule_interval='@daily')
        DummyOperator(task_id='task1', dag=dag, sla=timedelta(seconds=60))
        
        dag = SerializedDAG.from_json(SerializedDAG.to_json(dag))
        with patch.object(settings, "CHECK_SLAS", True):
            self.scheduler_job = SchedulerJob(subdir=os.devnull)
            mock_agent = mock.MagicMock()
            self.scheduler_job.processor_agent = mock_agent
            self.scheduler_job._send_sla_callbacks_to_processor(dag)
            self.scheduler_job.processor_agent.send_sla_callback_request_to_execute.assert_called_once_with(
                full_filepath=dag.fileloc, dag_id=dag_id
            )
    @freeze_time(DEFAULT_DATE + datetime.timedelta(days=1, seconds=9))
    @mock.patch('airflow.jobs.scheduler_job.Stats.timing')
    def test_create_dag_runs(self, stats_timing):