**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

tests/jobs/test_scheduler_job.py
"""
        DagRuns with one successful and one future root task -> SUCCESS
        Noted: the DagRun state could be still in running state during CI.
        """
        clear_db_dags()
        dag_id = 'test_dagrun_states_root_future'
        dag = self.dagbag.get_dag(dag_id)
        dag.sync_to_db()
        scheduler = SchedulerJob(num_runs=1, executor=self.null_exec, subdir=dag.fileloc)
        scheduler.run()
        first_run = DagRun.find(dag_id=dag_id, execution_date=DEFAULT_DATE)[0]
        ti_ids = [(ti.task_id, ti.state) for ti in first_run.get_task_instances()]
        assert ti_ids == [('current', State.SUCCESS)]
        assert first_run.state in [State.SUCCESS, State.RUNNING]
    def test_dagrun_deadlock_ignore_depends_on_past_advance_ex_date(self):