**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,
        pickle_dags: bool,
        dag_ids: Optional[List[str]],
        callback_requests: List[CallbackRequest],
    ):
        super().__init__()
        self._file_path = file_path
        self._pickle_dags = pickle_dags
        self._dag_ids = dag_ids
        self._callback_requests = callback_requests
        
        self._process: Optional[multiprocessing.process.BaseProcess] = None
        
        self._result: Optional[Tuple[int, int]] = None
        
        self._done = False
        
        self._start_time: Optional[datetime.datetime] = None
        
        
        self._instance_id = DagFileProcessorProcess.class_creation_counter
        self._parent_channel: Optional[MultiprocessingConnection] = None
        DagFileProcessorProcess.class_creation_counter += 1
    @property
    def file_path(self) -> str: