**Apache Airflow version**: 2.0.0


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

**Environment**:

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

**What happened**:

I have the following DAG:

```py
from datetime import datetime, timedelta

from airflow import DAG
from airflow.operators.bash_operator import BashOperator

with DAG(
    dag_id="sla_trigger",
    schedule_interval="* * * * *",
    start_date=datetime(2020, 2, 3),
) as dag:
    BashOperator(
        task_id="bash_task",
        bash_command="sleep 30",
        sla=timedelta(seconds=2),
    )

```

And in my understanding this dag should result in SLA miss every time it is triggered (every minute). However, after few minutes of running I don't see any SLA misses...

**What you expected to happen**:

I expect to see SLA if task takes longer than expected.

**How to reproduce it**:

Use the dag from above.

**Anything else we need to know**:

N/A

airflow/jobs/scheduler_job.py
file_path: str,
        callback_requests: List[CallbackRequest],
        dag_ids: Optional[List[str]],
        pickle_dags: bool,
    ) -> DagFileProcessorProcess:
        """Creates DagFileProcessorProcess instance."""
        return DagFileProcessorProcess(
            file_path=file_path, pickle_dags=pickle_dags, dag_ids=dag_ids, callback_requests=callback_requests
        )
    def _run_scheduler_loop(self) -> None:
        """
        The actual scheduler loop. The main steps in the loop are:
            #. Harvest DAG parsing results through DagFileProcessorAgent
            #. Find and queue executable tasks
                #. Change task instance state in DB
                #. Queue tasks in executor
            #. Heartbeat executor
                #. Execute queued tasks in executor asynchronously
                #. Sync on the states of running tasks
        Following is a graphic representation of these steps.
        .. image:: ../docs/apache-airflow/img/scheduler_loop.jpg
        :rtype: None
        """
        if not self.processor_agent:
            raise ValueError("Processor agent is not started.")
        is_unit_test: bool = conf.getboolean('core', 'unit_test_mode')
        timers = sched.scheduler()
        def call_regular_interval(