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...It exposes detailed visibility into worker status, task execution history, and queue metrics through an interactive web dashboard. Developers and operators can remotely manage workers by restarting instances, adjusting pool sizes, revoking tasks, or applying rate limits without direct server access. Flower also supports broker monitoring and integrates with authentication providers and Prometheus for metrics export, making it suitable for production environments. The tool communicates with Celery using event streams, allowing near real-time updates on asynchronous workloads. Because Celery is widely used in Python microservices and background job systems, Flower has become a standard companion utility for teams that need operational insight and control over distributed task processing.