Emit scheduler.executor_events_duration per executor

[dkranchii]

Summary

Wrap _process_executor_events() in a per-executor stats.timer named scheduler.executor_events_duration, tagged by executor class name. Multi-executor deployments can now attribute per-loop event-processing cost to each configured executor, instead of only seeing it baked into the aggregate scheduler.scheduler_loop_duration.

This mirrors the precedent set by #66808, which added scheduler.executor_heartbeat_duration for executor.heartbeat(). The two timers sit side-by-side, so operators can localize which stage of the scheduler loop a given executor is slowing down.

Why

Today, when the scheduler loop runs long in a multi-executor deployment, operators can see the aggregate via scheduler.scheduler_loop_duration but cannot tell which executor's event processing is to blame. Adding a per-executor timer for _process_executor_events gives the same granular signal the heartbeat timer added — single-file, additive, zero-cost when metrics are disabled.

Changes

• airflow-core/src/airflow/jobs/scheduler_job_runner.py — wrap the per-executor _process_executor_events() call in stats.timer("scheduler.executor_events_duration", tags={"executor": type(executor).__name__}).
• shared/observability/src/airflow_shared/observability/metrics/metrics_template.yaml — declare the new timer in the metrics registry.
• airflow-core/tests/unit/jobs/test_scheduler_job.py — add test_process_executor_events_emits_timer, mirroring the existing test_executor_heartbeat_emits_timer structure.

Test plan

• New unit test test_process_executor_events_emits_timer asserts the timer is emitted once per executor with the expected tag.
• Existing test_executor_heartbeat_emits_timer still passes (sibling test, same loop).
• ruff format / ruff check clean.
• prek run --from-ref main --stage pre-commit and --stage manual clean (excluding host-only mypy/breeze hooks; CI will run them).

Notes

• Additive change — no behavioral impact when metrics are disabled.
• No newsfragment per CLAUDE.md: new optional metrics are not major/breaking.
• No config or schema changes.

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Was generative AI tooling used to co-author this PR?

• Yes — Cursor