**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
self,
        file_path: str,
        callback_requests: List[CallbackRequest],
        pickle_dags: bool = False,
        session: Session = None,
    ) -> Tuple[int, int]:
        """
        Process a Python file containing Airflow DAGs.
        This includes:
        1. Execute the file and look for DAG objects in the namespace.
        2. Execute any Callbacks if passed to this method.
        3. Serialize the DAGs and save it to DB (or update existing record in the DB).
        4. Pickle the DAG and save it to the DB (if necessary).
        5. Record any errors importing the file into ORM
        :param file_path: the path to the Python file that should be executed
        :type file_path: str
        :param callback_requests: failure callback to execute
        :type callback_requests: List[airflow.utils.dag_processing.CallbackRequest]
        :param pickle_dags: whether serialize the DAGs found in the file and
            save them to the db
        :type pickle_dags: bool
        :param session: Sqlalchemy ORM Session
        :type session: Session
        :return: number of dags found, count of import errors
        :rtype: Tuple[int, int]
        """