**Apache Airflow version**: 2.0.1


**Kubernetes version (if you are using kubernetes)** (use `kubectl version`): 1.18.14

Environment:

Cloud provider or hardware configuration: Azure
OS (e.g. from /etc/os-release):
Kernel (e.g. uname -a):
Install tools:
Others:

**What happened**:

An occasional airflow tasks fails with the following error

```
[2021-06-21 05:39:48,424] {local_task_job.py:184} WARNING - State of this instance has been externally set to up_for_retry. Terminating instance.
[2021-06-21 05:39:48,425] {process_utils.py:100} INFO - Sending Signals.SIGTERM to GPID 259
[2021-06-21 05:39:48,426] {taskinstance.py:1238} ERROR - Received SIGTERM. Terminating subprocesses.
[2021-06-21 05:39:48,426] {bash.py:185} INFO - Sending SIGTERM signal to bash process group
[2021-06-21 05:39:49,133] {process_utils.py:66} INFO - Process psutil.Process(pid=329, status='terminated', started='04:32:14') (329) terminated with exit code None
[2021-06-21 05:39:50,278] {taskinstance.py:1454} ERROR - Task received SIGTERM signal
Traceback (most recent call last):
  File "/usr/local/lib/python3.7/site-packages/airflow/models/taskinstance.py", line 1112, in _run_raw_task
    self._prepare_and_execute_task_with_callbacks(context, task)
  File "/usr/local/lib/python3.7/site-packages/airflow/models/taskinstance.py", line 1284, in _prepare_and_execute_task_with_callbacks
    result = self._execute_task(context, task_copy)
  File "/usr/local/lib/python3.7/site-packages/airflow/models/taskinstance.py", line 1309, in _execute_task
    result = task_copy.execute(context=context)
  File "/usr/local/lib/python3.7/site-packages/airflow/operators/bash.py", line 171, in execute
    for raw_line in iter(self.sub_process.stdout.readline, b''):
  File "/usr/local/lib/python3.7/site-packages/airflow/models/taskinstance.py", line 1240, in signal_handler
    raise AirflowException("Task received SIGTERM signal")
airflow.exceptions.AirflowException: Task received SIGTERM signal
```

There is no indication as to what caused this error. The worker instance is healthy and task did not hit the task timeout.

**What you expected to happen**:

Task to complete successfully. If a task fad to fail for unavoidable reason (like timeout), it would be helpful to provide the reason for the failure.

**How to reproduce it**:

I'm not able to reproduce it consistently. It happens every now and then with the same error as provided above.

I'm also wish to know how to debug these failures 



airflow/jobs/scheduler_job.py
ti_concurrency_query: List[Tuple[str, str, int]] = (
            session.query(TI.task_id, TI.dag_id, func.count('*'))
            .filter(TI.state.in_(states))
            .group_by(TI.task_id, TI.dag_id)
        ).all()
        dag_map: DefaultDict[str, int] = defaultdict(int)
        task_map: DefaultDict[Tuple[str, str], int] = defaultdict(int)
        for result in ti_concurrency_query:
            task_id, dag_id, count = result
            dag_map[dag_id] += count
            task_map[(dag_id, task_id)] = count
        return dag_map, task_map
    @provide_session
    def _executable_task_instances_to_queued(self, max_tis: int, session: Session = None) -> List[TI]:
        """
        Finds TIs that are ready for execution with respect to pool limits,
        dag max_active_tasks, executor state, and priority.
        :param max_tis: Maximum number of TIs to queue in this loop.
        :type max_tis: int
        :return: list[airflow.models.TaskInstance]
        """
        executable_tis: List[TI] = []
        
        
        pools = models.Pool.slots_stats(lock_rows=True, session=session)
        
        
        pool_slots_free = max(0, sum(pool['open'] for pool in pools.values()))
        if pool_slots_free == 0:
            self.log.debug("All pools are full!")