**Description**


It would be great if the metrics we publish in Airflow change to include TAGs for "variable" parts of those (such as dag_id, task_id, pool name) rather than being part of the metrics.

See here: https://airflow.apache.org/docs/1.10.12/metrics.html, https://airflow.readthedocs.io/en/latest/logging-monitoring/metrics.html  - those variable parts should be tags.

We might consider to change those metrics by default in 2.0 and possibly introduce a backport in 1.10.13 to allow people to migrate.


**Use case / motivation**

Having the variable parts of the metrics makes it really difficult to aggregate the metrics. Seems that statsd python library does not support tags, but there are possible solutions by installing extensions:

https://stackoverflow.com/questions/49852654/sending-statsd-metrics-with-tags-from-python-client

**Related Issues**

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"""Test that the _update_dagrun_state_for_paused_dag does not affect backfilled dagruns"""
        with dag_maker("testdag") as dag:
            EmptyOperator(task_id="task1")
        
        backfill_run = dag_maker.create_dagrun(run_type=DagRunType.BACKFILL_JOB)
        backfill_run.last_scheduling_decision = datetime.datetime.now(timezone.utc) - timedelta(minutes=1)
        ti = backfill_run.get_task_instances()[0]
        ti.set_state(TaskInstanceState.SUCCESS)
        dm = DagModel.get_dagmodel(dag.dag_id)
        dm.is_paused = True
        session.merge(dm)
        session.merge(ti)
        session.flush()
        assert backfill_run.state == State.RUNNING
        self.scheduler_job = SchedulerJob(subdir=os.devnull)
        self.scheduler_job.executor = MockExecutor()
        self.scheduler_job._update_dag_run_state_for_paused_dags()
        session.flush()
        (backfill_run,) = DagRun.find(dag_id=dag.dag_id, run_type=DagRunType.BACKFILL_JOB, session=session)
        assert backfill_run.state == State.RUNNING
    def test_dataset_orphaning(self, dag_maker, session):
        dataset1 = Dataset(uri="ds1")
        dataset2 = Dataset(uri="ds2")
        dataset3 = Dataset(uri="ds3")
        dataset4 = Dataset(uri="ds4")
        with dag_maker(dag_id="datasets-1", schedule=[dataset1, dataset2], session=session):
            BashOperator(task_id="task", bash_command="echo 1", outlets=[dataset3, dataset4])