### 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
.join(DagRun, DagRun.execution_date == TaskFail.execution_date)
            .filter(DagRun.execution_date == dttm, TaskFail.dag_id == dag_id)
        )
        tasks = []
        for ti in tis:
            
            
            
            try_count = ti.prev_attempted_tries if ti.prev_attempted_tries != 0 else ti.try_number
            task_dict = alchemy_to_dict(ti)
            task_dict['end_date'] = task_dict['end_date'] or timezone.utcnow()
            task_dict['extraLinks'] = dag.get_task(ti.task_id).extra_links
            task_dict['try_number'] = try_count
            tasks.append(task_dict)
        tf_count = 0
        try_count = 1
        prev_task_id = ""
        for failed_task_instance in ti_fails:
            if tf_count != 0 and failed_task_instance.task_id == prev_task_id:
                try_count += 1
            else:
                try_count = 1
            prev_task_id = failed_task_instance.task_id
            tf_count += 1
            task = dag.get_task(failed_task_instance.task_id)
            task_dict = alchemy_to_dict(failed_task_instance)
            end_date = task_dict['end_date'] or timezone.utcnow()
            task_dict['end_date'] = end_date
            task_dict['start_date'] = task_dict['start_date'] or end_date
            task_dict['state'] = State.FAILED