Flower is a web-based monitoring and administration tool for Celery distributed task queues.
Flower solves the problem of gaining visibility and control over Celery clusters by providing real-time monitoring through Celery Events. It displays task progress, history, and detailed task information including arguments, start time, and runtime. The tool enables remote control of workers, allowing operators to shutdown or restart instances, adjust pool sizes, modify queue assignments, and manage task execution through revocation or termination. It also monitors broker statistics across all queues and integrates with Prometheus for metrics collection.
Flower suits teams running Celery-based distributed task systems who need operational visibility and the ability to manage workers and tasks from a central interface. It works with brokers including RabbitMQ and Redis. The tool offers multiple authentication options including HTTP Basic Auth and OAuth providers like Google, Github, Gitlab, and Okta. Beyond the web interface, Flower exposes a REST API that enables programmatic cluster management, such as restarting worker pools or revoking tasks via HTTP requests.
The project maintains active development with regular updates to its codebase. Build workflows are consistently executed to validate changes. The tool is distributed through multiple channels including pip and Docker, indicating sustained attention to accessibility and deployment patterns. Documentation is maintained at a dedicated site, suggesting ongoing effort to keep guidance current alongside code evolution.
