### Description

Auto-refresh is an awesome new feature! Right now it occurs every [3 seconds](https://github.com/apache/airflow/blob/79d85573591f641db4b5f89a12213e799ec6dea1/airflow/www/static/js/tree.js#L463), and this interval is not configurable. Making this interval configurable would be useful.

### Use case/motivation

On a DAG with many tasks and many active DAG runs, auto-refresh can be a significant strain on the webserver. We observed our production webserver reach 100% CPU today when we had about 30 running DAG runs of a DAG containing about 50 tasks. Being able to increase the interval to guard against this would be helpful.

### Related issues

_No response_

### Are you willing to submit a 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)

airflow/www/views.py
x_points = defaultdict(list)
        cumulative_y = defaultdict(list)
        task_instances = dag.get_task_instances_before(base_date, num_runs, session=session)
        if task_instances:
            min_date = task_instances[0].execution_date
        else:
            min_date = timezone.utc_epoch()
        ti_fails = (
            session.query(TaskFail)
            .filter(
                TaskFail.dag_id == dag.dag_id,
                TaskFail.execution_date >= min_date,
                TaskFail.execution_date <= base_date,
                TaskFail.task_id.in_([t.task_id for t in dag.tasks]),
            )
            .all()
        )
        fails_totals = defaultdict(int)
        for failed_task_instance in ti_fails:
            dict_key = (
                failed_task_instance.dag_id,
                failed_task_instance.task_id,
                failed_task_instance.execution_date,
            )
            if failed_task_instance.duration:
                fails_totals[dict_key] += failed_task_instance.duration
        for task_instance in task_instances:
            if task_instance.duration:
                date_time = wwwutils.epoch(task_instance.execution_date)
                x_points[task_instance.task_id].append(date_time)