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**Apache Airflow version**: 2.0.0 but applicable to master

**Environment**: Running on ECS but not relevant to question


**What happened**: I am not seeing the metric dagrun.schedule_delay.<dag_id> being reported.  A search in the codebase seems to reveal that it no longer exists.   It was originally added in https://github.com/apache/airflow/pull/5050.

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<!-- What do you think went wrong? -->
I suspect either:
1.  This metric was intentionally removed, in which case the docs should be updated to remove it.
2. It was unintentionally removed during a refactor, in which case we should add it back.
3. I am bad at searching through code, and someone could hopefully point me to where it is reported from now. 

**How to reproduce it**:
https://github.com/apache/airflow/search?q=schedule_delay


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airflow/jobs/scheduler_job.py
"""
    This SchedulerJob runs for a specific time interval and schedules the jobs
    that are ready to run. It figures out the latest runs for each
    task and sees if the dependencies for the next schedules are met.
    If so, it creates appropriate TaskInstances and sends run commands to the
    executor. It does this for each task in each DAG and repeats.
    :param dag_id: if specified, only schedule tasks with this DAG ID
    :type dag_id: str
    :param dag_ids: if specified, only schedule tasks with these DAG IDs
    :type dag_ids: list[str]
    :param subdir: directory containing Python files with Airflow DAG
        definitions, or a specific path to a file
    :type subdir: str
    :param num_runs: The number of times to run the scheduling loop. If you
        have a large number of DAG files this could complete before each file
        has been parsed. -1 for unlimited times.
    :type num_runs: int
    :param num_times_parse_dags: The number of times to try to parse each DAG file.
        -1 for unlimited times.
    :type num_times_parse_dags: int
    :param processor_poll_interval: The number of seconds to wait between
        polls of running processors
    :type processor_poll_interval: int
    :param do_pickle: once a DAG object is obtained by executing the Python
        file, whether to serialize the DAG object to the DB
    :type do_pickle: bool
    """
    __mapper_args__ = {'polymorphic_identity': 'SchedulerJob'}
    heartrate: int = conf.getint('scheduler', 'SCHEDULER_HEARTBEAT_SEC')
    def __init__(