**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
)
                .group_by(TI.dag_id, TI.execution_date)
            )
            for dag_id, execution_date in query:
                active_runs_by_dag_id[dag_id].add(execution_date)
            for dag_run in dag_runs:
                
                
                
                
                
                
                try:
                    self._schedule_dag_run(dag_run, active_runs_by_dag_id.get(dag_run.dag_id, set()), session)
                except SerializedDagNotFound:
                    self.log.exception("DAG '%s' not found in serialized_dag table", dag_run.dag_id)
                    continue
            guard.commit()
            
            session.expunge_all()
            
            try:
                if self.executor.slots_available <= 0:
                    
                    self.log.debug("Executor full, skipping critical section")
                    return 0
                timer = Stats.timer('scheduler.critical_section_duration')
                timer.start()
                
                num_queued_tis = self._critical_section_execute_task_instances(session=session)