**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
<pre><code>{task_list}\n<code></pre>
            Blocking tasks:
            <pre><code>{blocking_task_list}<code></pre>
            Airflow Webserver URL: {conf.get(section='webserver', key='base_url')}
            """
            tasks_missed_sla = []
            for sla in slas:
                try:
                    task = dag.get_task(sla.task_id)
                except TaskNotFound:
                    
                    self.log.warning(
                        "Task %s doesn't exist in DAG anymore, skipping SLA miss notification.", sla.task_id
                    )
                    continue
                tasks_missed_sla.append(task)
            emails: Set[str] = set()
            for task in tasks_missed_sla:
                if task.email:
                    if isinstance(task.email, str):
                        emails |= set(get_email_address_list(task.email))
                    elif isinstance(task.email, (list, tuple)):
                        emails |= set(task.email)
            if emails:
                try:
                    send_email(emails, f"[airflow] SLA miss on DAG={dag.dag_id}", email_content)
                    email_sent = True
                    notification_sent = True
                except Exception:  
                    Stats.incr('sla_email_notification_failure')