**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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DagFileProcessorManager,
    DagFileStat,
    DagParsingSignal,
    DagParsingStat,
)
from airflow.dag_processing.processor import DagFileProcessorProcess
from airflow.models import DagBag, DagModel, DbCallbackRequest, errors
from airflow.models.dagcode import DagCode
from airflow.models.serialized_dag import SerializedDagModel
from airflow.utils import timezone
from airflow.utils.net import get_hostname
from airflow.utils.session import create_session
from tests.core.test_logging_config import SETTINGS_FILE_VALID, settings_context
from tests.models import TEST_DAGS_FOLDER
from tests.test_utils.config import conf_vars
from tests.test_utils.db import clear_db_callbacks, clear_db_dags, clear_db_runs, clear_db_serialized_dags
TEST_DAG_FOLDER = pathlib.Path(__file__).parents[1].resolve() / "dags"
DEFAULT_DATE = timezone.datetime(2016, 1, 1)
class FakeDagFileProcessorRunner(DagFileProcessorProcess):
    
    
    def __init__(self, file_path, pickle_dags, dag_ids, dag_directory, callbacks):
        super().__init__(file_path, pickle_dags, dag_ids, dag_directory, callbacks)
        
        readable, writable = multiprocessing.Pipe(duplex=False)
        writable.send("abc")
        writable.close()
        self._waitable_handle = readable
        self._result = 0, 0
    def start(self):