**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
"""
        Test to check that a DAG returns its active runs
        """
        now = timezone.utcnow()
        six_hours_ago_to_the_hour = (now - datetime.timedelta(hours=6)).replace(
            minute=0, second=0, microsecond=0
        )
        start_date = six_hours_ago_to_the_hour
        dag_name1 = 'get_active_runs_test'
        default_args = {'owner': 'airflow', 'depends_on_past': False, 'start_date': start_date}
        dag1 = DAG(dag_name1, schedule_interval='* * * * *', max_active_runs=1, default_args=default_args)
        run_this_1 = DummyOperator(task_id='run_this_1', dag=dag1)
        run_this_2 = DummyOperator(task_id='run_this_2', dag=dag1)
        run_this_2.set_upstream(run_this_1)
        run_this_3 = DummyOperator(task_id='run_this_3', dag=dag1)
        run_this_3.set_upstream(run_this_2)
        session = settings.Session()
        orm_dag = DagModel(dag_id=dag1.dag_id)
        session.merge(orm_dag)
        session.commit()
        session.close()
        dag1.clear()
        dr = dag1.create_dagrun(
            run_type=DagRunType.SCHEDULED,
            execution_date=start_date,