### Description

A count of datasets that are currently registered/declared in an Airflow deployment.

### Use case/motivation

Would be nice to see how deployments are adopting datasets.

### Related issues

_No response_

### Are you willing to submit a PR?

- [ ] 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,