**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
with mock.patch.dict(
            "os.environ",
            {
                "PERF_DAGS_COUNT": str(dag_count),
                "PERF_TASKS_COUNT": str(task_count),
                "PERF_START_AGO": "1d",
                "PERF_SCHEDULE_INTERVAL": "30m",
                "PERF_SHAPE": "no_structure",
            },
        ), conf_vars(
            {
                ('scheduler', 'use_job_schedule'): 'True',
                ('core', 'load_examples'): 'False',
                ('core', 'store_serialized_dags'): 'True',
            }
        ), mock.patch.object(
            settings, 'STORE_SERIALIZED_DAGS', True
        ):
            dagruns = []