### 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)

DagRun.dag_id == dag.dag_id,
                        DagRun.execution_date < exec_date,
                        DagRun.run_type == DagRunType.DATASET_TRIGGERED,
                    )
                    .order_by(DagRun.execution_date.desc())
                    .first()
                )
                dataset_event_filters = [
                    DagScheduleDatasetReference.dag_id == dag.dag_id,
                    DatasetEvent.timestamp <= exec_date,
                ]
                if previous_dag_run:
                    dataset_event_filters.append(DatasetEvent.timestamp > previous_dag_run.execution_date)
                dataset_events = (
                    session.query(DatasetEvent)
                    .join(
                        DagScheduleDatasetReference,
                        DatasetEvent.dataset_id == DagScheduleDatasetReference.dataset_id,
                    )
                    .join(DatasetEvent.source_dag_run)
                    .filter(*dataset_event_filters)
                    .all()
                )
                data_interval = dag.timetable.data_interval_for_events(exec_date, dataset_events)
                run_id = dag.timetable.generate_run_id(
                    run_type=DagRunType.DATASET_TRIGGERED,
                    logical_date=exec_date,
                    data_interval=data_interval,
                    session=session,
                    events=dataset_events,