**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 various invariants of _create_dag_runs.
        - That the run created has the creating_job_id set
        - That we emit the right DagRun metrics
        """
        dag = DAG(dag_id='test_create_dag_runs', start_date=DEFAULT_DATE)
        DummyOperator(
            task_id='dummy',
            dag=dag,
        )
        dagbag = DagBag(
            dag_folder=os.devnull,
            include_examples=False,
            read_dags_from_db=True,
        )
        dagbag.bag_dag(dag=dag, root_dag=dag)
        dagbag.sync_to_db()
        dag_model = DagModel.get_dagmodel(dag.dag_id)
        self.scheduler_job = SchedulerJob(executor=self.null_exec)
        self.scheduler_job.processor_agent = mock.MagicMock()
        with create_session() as session:
            self.scheduler_job._create_dag_runs([dag_model], session)
        stats_timing.assert_called_once_with(
            "dagrun.schedule_delay.test_create_dag_runs", datetime.timedelta(seconds=9)
        )
        assert dag.get_last_dagrun().creating_job_id == self.scheduler_job.id
    def test_extra_operator_links_not_loaded_in_scheduler_loop(self):