feat : Add a scheduling helper for tpu_observability DAGs - part 1

[chengpinglin]

Description

This PR introduces the SchedulingHelper utility and the get_dag_timeout function to manage and calculate non-overlapping execution schedules for Airflow DAGs. This implementation ensures resource safety and configuration consistency across TPU clusters through automated time-slot allocation.

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1. The Registry: Simplified and Centralized

The implementation uses a centralized REGISTERED_DAGS registry with a refined data structure:
dict[str, dict[str, dt.timedelta]].

• Structure: It maps a cluster name (key) to a sub-dictionary where keys are dag_id strings and values are dt.timedelta objects.

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2. arrange_schedule_time: Discovery and Stacking Logic

The arrange_schedule_time method automates cron string generation using a "Linear Time Stacking" approach with Automatic Cluster Discovery.

Tests

• GCP Composer name: ml-automation-solutions-dev (under GCP project: cloud-ml-auto-solutions)
• GCP Composer version: 2.13.1

Checklist

Before submitting this PR, please make sure (put X in square brackets):

• I have performed a self-review of my code.
• I have necessary comments in my code, particularly in hard-to-understand areas.
• I have run one-shot tests and provided workload links above if applicable.
• I have made or will make corresponding changes to the doc if needed.