### 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)

dag_id = task_instance.dag_id
                current_active_tasks_per_dag = dag_active_tasks_map[dag_id]
                max_active_tasks_per_dag_limit = task_instance.dag_model.max_active_tasks
                self.log.info(
                    "DAG %s has %s/%s running and queued tasks",
                    dag_id,
                    current_active_tasks_per_dag,
                    max_active_tasks_per_dag_limit,
                )
                if current_active_tasks_per_dag >= max_active_tasks_per_dag_limit:
                    self.log.info(
                        "Not executing %s since the number of tasks running or queued "
                        "from DAG %s is >= to the DAG's max_active_tasks limit of %s",
                        task_instance,
                        dag_id,
                        max_active_tasks_per_dag_limit,
                    )
                    starved_dags.add(dag_id)
                    continue
                if task_instance.dag_model.has_task_concurrency_limits:
                    
                    
                    serialized_dag = self.dagbag.get_dag(dag_id, session=session)
                    
                    if not serialized_dag:
                        self.log.error(
                            "DAG '%s' for task instance %s not found in serialized_dag table",
                            dag_id,