**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 SLA Callbacks are not sent when DAG isn't scheduled"""
        dag_id = "test_send_sla_callbacks_to_processor_sla_no_task_slas"
        with dag_maker(dag_id=dag_id, schedule=schedule) as dag:
            EmptyOperator(task_id="task1", sla=timedelta(seconds=5))
        with patch.object(settings, "CHECK_SLAS", True):
            self.scheduler_job = SchedulerJob(subdir=os.devnull)
            self.scheduler_job.executor = MockExecutor()
            self.scheduler_job._send_sla_callbacks_to_processor(dag)
            self.scheduler_job.executor.callback_sink.send.assert_not_called()
    def test_create_dag_runs(self, dag_maker):
        """
        Test various invariants of _create_dag_runs.
        - That the run created has the creating_job_id set
        - That the run created is on QUEUED State
        - That dag_model has next_dagrun
        """
        with dag_maker(dag_id="test_create_dag_runs") as dag:
            EmptyOperator(task_id="dummy")
        dag_model = dag_maker.dag_model
        self.scheduler_job = SchedulerJob(executor=self.null_exec)
        self.scheduler_job.processor_agent = mock.MagicMock()
        with create_session() as session:
            self.scheduler_job._create_dag_runs([dag_model], session)
        dr = session.query(DagRun).filter(DagRun.dag_id == dag.dag_id).first()
        
        assert dr.state == State.QUEUED
        assert dr.start_date is None
        assert dag.get_last_dagrun().creating_job_id == self.scheduler_job.id
    @pytest.mark.need_serialized_dag
    def test_create_dag_runs_datasets(self, session, dag_maker):