### Apache Airflow version

2.5.1

### What happened

I'd expect the `scheduler.tasks.running` metric to represent the number of running tasks, but it is always zero. It appears that #10956 broke this when it removed [the line that increments `num_tasks_in_executor`](https://github.com/apache/airflow/pull/10956/files#diff-bde85feb359b12bdd358aed4106ef4fccbd8fa9915e16b9abb7502912a1c1ab3L1363). Right now that variable is set to 0, never incremented, and the emitted as a gauge.

### What you think should happen instead

`scheduler.tasks.running` should either represent the number of tasks running or be removed altogether.

### How to reproduce

_No response_

### Operating System

Ubuntu 18.04

### Versions of Apache Airflow Providers

_No response_

### Deployment

Official Apache Airflow Helm Chart

### Deployment details

_No response_

### Anything else

_No response_

### Are you willing to submit PR?

- [X] Yes I am willing to submit a PR!

### Code of Conduct

- [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

"""
        Unconditionally create a DAG run for the given DAG, and update the dag_model's fields to control
        if/when the next DAGRun should be created
        """
        
        
        
        
        existing_dagruns = (
            session.query(DagRun.dag_id, DagRun.execution_date)
            .filter(
                tuple_in_condition(
                    (DagRun.dag_id, DagRun.execution_date),
                    ((dm.dag_id, dm.next_dagrun) for dm in dag_models),
                ),
            )
            .all()
        )
        active_runs_of_dags = defaultdict(
            int,
            DagRun.active_runs_of_dags(dag_ids=(dm.dag_id for dm in dag_models), session=session),
        )
        for dag_model in dag_models:
            dag = self.dagbag.get_dag(dag_model.dag_id, session=session)