Flower is a web based tool for monitoring and administrating Celery clusters.
Real-time monitoring using Celery Events
- Task progress and history
- Ability to show task details (arguments, start time, runtime, and more)
- Graphs and statistics
Remote Control
- View worker status and statistics
- Shutdown and restart worker instances
- Control worker pool size and autoscale settings
- View and modify the queues a worker instance consumes from
- View currently running tasks
- View scheduled tasks (ETA/countdown)
- View reserved and revoked tasks
- Apply time and rate limits
- Configuration viewer
- Revoke or terminate tasks
Broker monitoring
- View statistics for all Celery queues
- Queue length gra 8000 phs
HTTP API
Basic Auth and Google OpenID authentication
Flower API enables to manage the cluster via REST API, call tasks and receive task events in real-time via WebSockets.
For example you can restart worker's pool by:
$ curl -X POST http://localhost:5555/api/worker/pool/restart/myworker
Or call a task by:
$ curl -X POST -d '{"args":[1,2]}' http://localhost:5555/api/task/async-apply/tasks.add
Or terminate executing task by:
$ curl -X POST -d 'terminate=True' http://localhost:5555/api/task/revoke/8a4da87b-e12b-4547-b89a-e92e4d1f8efd
Or receive task completion events in real-time:
var ws = new WebSocket('ws://localhost:5555/api/task/events/task-succeeded/');
ws. (event) {
console.log(event.data);
}
For more info checkout API Reference and examples.
PyPI version:
$ pip install flower
Development version:
$ pip install https://github.com/mher/flower/zipball/master
Launch the server and open http://localhost:5555:
$ flower --port=5555
Or launch from celery:
$ celery flower -A proj --address=127.0.0.1 --port=5555
Broker URL and other configuration options can be passed through the standard Celery options:
$ celery flower -A proj --broker=amqp://guest:guest@localhost:5672//
Documentation is available at Read the Docs and IPython Notebook Viewer
More screenshots
Please head over to #celery IRC channel on irc.freenode.net or open an issue.
If you'd like to contribute, simply fork the repository, commit your changes, run the tests (python -m tests) and send a pull request. Make sure you add yourself to AUTHORS.