Fix OTel timer metrics using Gauge instead of Histogram

[namratachaudhary]

Timer and timing metrics in the OTel logger were recorded using a Gauge instrument, which does not preserve multiple observations within an export interval. In practice, if the scheduler loop runs many times between exports, only a single value is retained, and the distribution of durations is lost.

This PR switches timing() and timer() to use a Histogram instrument, which captures duration distributions via count, sum, and bucketed observations. This enables accurate downstream analysis such as percentiles (p50, p95, p99).

The OTel supplementary guidelines recommend Histogram for measurements where "the statistics about this thing are likely to be meaningful" and durations are a canonical example.

Changes

• _OtelTimer.stop() and SafeOtelLogger.timing() now call record_histogram_value() instead of set_gauge_value()
• New InternalHistogram class wrapping meter.create_histogram(unit="ms")
• New MetricsMap.record_histogram_value() method
• Tests updated: test_timing_existing_metric now verifies both observations are recorded (record.call_count == 2), not just the last value

Users affected

Affected metrics: all timer/timing metrics emitted via the OTel logger (e.g. scheduler.scheduler_loop_duration, dagrun.dependency-check, task.duration, etc.)

OTel users: the instrument type for timer/timing metrics changes from Gauge to Histogram. Dashboards or alerts treating these as Gauges may need to be updated. An example is shown below :

Before (Gauge):

# Last recorded duration for a specific task
airflow_task_duration{dag_id="my_dag", task_id="my_task"}

# Using ti.finish counter to approximate task completions 
rate(airflow_ti_finish{dag_id="my_dag", task_id="my_task", state="success"}[5m])

After (Histogram):

# Average task duration over last 5 minutes
rate(airflow_task_duration_sum{dag_id="my_dag", task_id="my_task"}[5m])
/ rate(airflow_task_duration_count{dag_id="my_dag", task_id="my_task"}[5m])

# p95 — "95% of runs finished within X ms"
histogram_quantile(0.95,
  rate(airflow_task_duration_bucket{dag_id="my_dag", task_id="my_task"}[5m])
)

# How many task runs completed in the last 5 minutes
rate(airflow_task_duration_count{dag_id="my_dag", task_id="my_task"}[5m])

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[boring-cyborg]

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