Vamsi-klu opened a new pull request, #67765:
URL: https://github.com/apache/airflow/pull/67765
### What / impact
When a Dag run timed out, the scheduler emitted the `dagrun.duration.failed`
timing metric with only a `dag_id` tag. Every other `dagrun.duration.*`
emission also carries `run_type`, so dashboards and alerts that segment by
`run_type` silently dropped timed-out runs (or saw an inconsistent tag set).
After this change the timeout path emits both `dag_id` and `run_type`,
consistent with normal completion.
### Why
The timeout branch in `_schedule_dag_run` hardcoded `tags={"dag_id":
dag_run.dag_id}`, while the canonical emitter
`DagRun._emit_duration_stats_for_finished_state` uses `dag_run.stats_tags`
(which includes `run_type`). This replaces the hardcoded dict with
`dag_run.stats_tags`. `run_type` is `NOT NULL` and low-cardinality, so the new
tag set is a safe strict superset of the old one and the metric name is
unchanged.
### How it unblocks
Makes timeout-duration metrics consistent and usable in `run_type`-segmented
observability. Supersedes #64768, which stalled on CI/static checks rather than
design — this keeps the diff to a single value change and ships green static
checks, including the metrics-registry sync check that blocked the prior
attempt.
### Tests
One new regression test in `test_scheduler_job.py`, verified to fail on the
unfixed code, asserting the `dagrun.duration.failed` timing call carries
`tags={"dag_id": …, "run_type": …}`. Full scheduler suite passes; mypy +
pre-commit + manual static checks (incl. metrics-registry sync) are green.
closes: #64765
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##### Was generative AI tooling used to co-author this PR?
- [X] Yes — Claude Code (Opus 4.8)
Generated-by: Claude Code (Opus 4.8) following [the
guidelines](https://github.com/apache/airflow/blob/main/contributing-docs/05_pull_requests.rst#gen-ai-assisted-contributions)
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