**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/serialization/test_dag_serialization.py
return dag.following_schedule(execution_date)
    default_args = {'start_date': datetime(2019, 7, 10)}
    dag = DAG(
        'user_defined_macro_filter_dag',
        default_args=default_args,
        user_defined_macros={
            'next_execution_date': compute_next_execution_date,
        },
        user_defined_filters={'hello': lambda name: f'Hello {name}'},
        catchup=False,
    )
    BashOperator(
        task_id='echo',
        bash_command='echo "{{ next_execution_date(dag, execution_date) }}"',
        dag=dag,
    )
    return {dag.dag_id: dag}
def collect_dags(dag_folder=None):