[PR] Add dag.schedule_overdue_seconds metric for Dags held back by max_active_runs [airflow]

["Abdel39 (via GitHub)" <gi...@apache.org>]

Abdel39 opened a new pull request, #74854:
URL: https://github.com/apache/airflow/pull/74854

   related: #73686
   
   When a time-scheduled Dag is at `max_active_runs`, `DagModel.dags_needing_dagruns` filters it out (`exceeds_max_non_backfill == false`), so its next run is never created. Nothing is queued, `scheduler.dagruns.queued` (#70013) stays at zero, and nothing tells you the Dag is falling behind its schedule until someone notices missing intervals.
   
   This adds a `dag.schedule_overdue_seconds` gauge, tagged by `dag_id`: seconds since the Dag's `next_dagrun_create_after`, emitted only while the Dag is due and held back by `max_active_runs`.
   
   - Emitted on the existing `[scheduler] dagrun_metrics_interval` timer, as a separate read-only query. It does not touch `dags_needing_dagruns`, which is row-locked and `LIMIT`ed.
   - Only Dags in the blocked state are emitted, so the series count is bounded by the number of blocked Dags, not the number of Dags. A healthy deployment emits nothing.
   - Asset-gated Dags are excluded, since `next_dagrun_create_after` alone does not make them due.
   
   We've run the same metric as a scheduler patch on our Airflow staging deployments. It was the signal teams needed to decide when to raise `max_active_runs` for scheduled Dags, where queued-run counts showed nothing.
   
   ---
   
   ##### Was generative AI tooling used to co-author this PR?
   
   - [x] Yes -- Claude Opus 5.5
   
   Generated-by: Claude Opus 5.5 following [the guidelines](https://github.com/apache/airflow/blob/main/contributing-docs/05_pull_requests.rst#gen-ai-assisted-contributions)
   


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Re: [PR] Add dag.schedule_overdue_seconds metric for Dags held back by max_active_runs [airflow]

["boring-cyborg[bot] (via GitHub)" <gi...@apache.org>]

boring-cyborg[bot] commented on PR #74854:
URL: https://github.com/apache/airflow/pull/74854#issuecomment-6216479846

   Congratulations on your first Pull Request and welcome to the Apache Airflow community! If you have any issues or are unsure about any anything please check our [Contributors' Guide](https://github.com/apache/airflow/blob/main/contributing-docs/README.rst)
   Here are some useful points:
   - Pay attention to the quality of your code (ruff, mypy and type annotations). Our [prek-hooks]( https://github.com/apache/airflow/blob/main/contributing-docs/08_static_code_checks.rst#prerequisites-for-prek-hooks) will help you with that.
   - In case of a new feature add useful documentation (in docstrings or in `docs/` directory). Adding a new operator? Check this short [guide](https://github.com/apache/airflow/blob/main/airflow-core/docs/howto/custom-operator.rst) Consider adding an example Dag that shows how users should use it.
   - Consider using [Breeze environment](https://github.com/apache/airflow/blob/main/dev/breeze/doc/README.rst) for testing locally, it's a heavy docker but it ships with a working Airflow and a lot of integrations.
   - Be patient and persistent. It might take some time to get a review or get the final approval from Committers.
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   - Always keep your Pull Requests rebased, otherwise your build might fail due to changes not related to your commits.
   Apache Airflow is a community-driven project and together we are making it better 🚀.
   In case of doubts contact the developers at:
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Re: [PR] Add dag.schedule_overdue_seconds metric for Dags held back by max_active_runs [airflow]

["hussein-awala (via GitHub)" <gi...@apache.org>]

hussein-awala commented on code in PR #74854:
URL: https://github.com/apache/airflow/pull/74854#discussion_r4348787760


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airflow-core/newsfragments/74854.feature.rst:
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Review Comment:
   Remove this file, it is only needed for significant changes



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