**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**

<!-- Is there currently another issue associated with this? -->

pickle_dags=False,
            async_mode=True,
        )
        manager._run_parsing_loop()
        result = None
        while parent_pipe.poll(timeout=None):
            result = parent_pipe.recv()
            if isinstance(result, DagParsingStat) and result.done:
                break
        
        assert sum(stat.run_count for stat in manager._file_stats.values()) == 3
        with create_session() as session:
            assert session.get(DagModel, dag_id) is not None
    @conf_vars({("core", "load_examples"): "False"})
    @pytest.mark.backend("mysql", "postgres")
    @pytest.mark.execution_timeout(30)
    @mock.patch("airflow.dag_processing.manager.DagFileProcessorProcess")
    def test_pipe_full_deadlock(self, mock_processor):
        dag_filepath = TEST_DAG_FOLDER / "test_scheduler_dags.py"
        child_pipe, parent_pipe = multiprocessing.Pipe()
        
        for fd in (parent_pipe.fileno(),):
            sock = socket.socket(fileno=fd)
            sock.setsockopt(socket.SOL_SOCKET, socket.SO_SNDBUF, 1024)
            sock.setsockopt(socket.SOL_SOCKET, socket.SO_RCVBUF, 1024)
            sock.detach()
        exit_event = threading.Event()
        
        
        def keep_pipe_full(pipe, exit_event):