### 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)

"""Find DagRuns in queued state and decide moving them to running state."""
        dag_runs = self._get_next_dagruns_to_examine(DagRunState.QUEUED, session)
        active_runs_of_dags = defaultdict(
            int,
            DagRun.active_runs_of_dags((dr.dag_id for dr in dag_runs), only_running=True, session=session),
        )
        def _update_state(dag: DAG, dag_run: DagRun):
            dag_run.state = DagRunState.RUNNING
            dag_run.start_date = timezone.utcnow()
            if dag.timetable.periodic:
                
                
                
                
                
                expected_start_date = dag.get_run_data_interval(dag_run).end
                schedule_delay = dag_run.start_date - expected_start_date
                
                Stats.timing(f"dagrun.schedule_delay.{dag.dag_id}", schedule_delay)
                Stats.timing(
                    "dagrun.schedule_delay",