**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
self,
        dag_id,
        expected_task_states,  
        dagrun_state,
        run_kwargs=None,
        advance_execution_date=False,
        session=None,
    ):  
        """
        Helper for testing DagRun states with simple two-task DAGS.
        This is hackish: a dag run is created but its tasks are
        run by a backfill.
        """
        if run_kwargs is None:
            run_kwargs = {}
        dag = self.dagbag.get_dag(dag_id)
        dr = dag.create_dagrun(
            run_type=DagRunType.SCHEDULED,
            execution_date=dag.next_dagrun_after_date(None),
            state=State.RUNNING,
        )
        if advance_execution_date: