**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
"""
        Integration test of the scheduler not accidentally resetting
        the try_numbers for a task
        """
        dag = self.dagbag.get_dag('test_retry_handling_job')
        dag_task1 = dag.get_task("test_retry_handling_op")
        dag.clear()
        scheduler = SchedulerJob(dag_id=dag.dag_id, num_runs=1)
        scheduler.heartrate = 0
        scheduler.run()
        session = settings.Session()
        ti = (
            session.query(TaskInstance)
            .filter(TaskInstance.dag_id == dag.dag_id, TaskInstance.task_id == dag_task1.task_id)
            .first()
        )
        
        assert ti.try_number == 2
        assert ti.state == State.UP_FOR_RETRY
    def test_dag_get_active_runs(self):