**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
"""Find Dag Models needing DagRuns and Create Dag Runs with retries in case of OperationalError"""
        for attempt in run_with_db_retries(logger=self.log):
            with attempt:
                try:
                    self.log.debug(
                        "Running SchedulerJob._create_dagruns_for_dags with retries. " "Try %d of %d",
                        attempt.retry_state.attempt_number,
                        settings.MAX_DB_RETRIES,
                    )
                    query = DagModel.dags_needing_dagruns(session)
                    self._create_dag_runs(query.all(), session)
                    
                    guard.commit()
                    
                except OperationalError:
                    session.rollback()
                    raise
    def _create_dag_runs(self, dag_models: Iterable[DagModel], session: Session) -> None: