Robust Rate-Limited Concurrent Task Scheduler

Design a Python task scheduling system that can execute concurrent tasks with dynamic rate limiting across distributed workers. Implement a leaky bucket algorithm that adapts rate limits based on system load, tracks individual task priorities, and provides graceful degradation under high concurrency. Include comprehensive logging, error recovery mechanisms, and support for both sync and async task types. The solution should handle edge cases like burst traffic, worker failures, and dynamic reconfiguration without manual intervention.