**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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if is_lock_not_available_error(error=e):
                        self.log.debug("Critical section lock held by another Scheduler")
                        Stats.incr("scheduler.critical_section_busy")
                        session.rollback()
                        return 0
                    raise
            guard.commit()
        return num_queued_tis
    @retry_db_transaction
    def _get_next_dagruns_to_examine(self, state: DagRunState, session: Session):
        """Get Next DagRuns to Examine with retries."""
        return DagRun.next_dagruns_to_examine(state, session)
    @retry_db_transaction
    def _create_dagruns_for_dags(self, guard: CommitProhibitorGuard, session: Session) -> None:
        """Find Dag Models needing DagRuns and Create Dag Runs with retries in case of OperationalError."""
        query, dataset_triggered_dag_info = DagModel.dags_needing_dagruns(session)
        all_dags_needing_dag_runs = set(query.all())
        dataset_triggered_dags = [
            dag for dag in all_dags_needing_dag_runs if dag.dag_id in dataset_triggered_dag_info
        ]
        non_dataset_dags = all_dags_needing_dag_runs.difference(dataset_triggered_dags)
        self._create_dag_runs(non_dataset_dags, session)
        if dataset_triggered_dags:
            self._create_dag_runs_dataset_triggered(
                dataset_triggered_dags, dataset_triggered_dag_info, session
            )
        
        guard.commit()
        
    def _create_dag_runs(self, dag_models: Collection[DagModel], session: Session) -> None: