**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
assert tis[dummy2.task_id].state == State.SUCCESS
        
        assert tis[dummy3.task_id].state == State.SKIPPED
class TestSchedulerJobQueriesCount(unittest.TestCase):
    """
    These tests are designed to detect changes in the number of queries for
    different DAG files. These tests allow easy detection when a change is
    made that affects the performance of the SchedulerJob.
    """
    def setUp(self) -> None:
        clear_db_runs()
        clear_db_pools()
        clear_db_dags()
        clear_db_sla_miss()
        clear_db_errors()
        clear_db_serialized_dags()
        clear_db_dags()
    @parameterized.expand(
        [
            
            
            (23, 1, 1),  
            
            (23, 1, 5),  
            
            (95, 10, 10),  
        ]
    )
    @pytest.mark.quarantined
    def test_execute_queries_count_with_harvested_dags(self, expected_query_count, dag_count, task_count):