flower

SYNOPSIS

flower [OPTIONS]

DESCRIPTION

Flower is a web based tool for monitoring and administrating Celery clusters. It has these features:

  • 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 graphs

  • HTTP API

  • Basic Auth and Google OpenID authentication

  • Prometheus integration

OPTIONS

--address run on the given address
--auth regexp of emails to grant access
--auth_provider
 sets authentication provider class
--auto_refresh refresh workers automatically (default True)
--basic_auth colon separated user-password to enable basic auth
--broker_api inspect broker e.g. http://guest:guest@localhost:15672/api/
--ca_certs path to SSL certificate authority (CA) file
--certfile path to SSL certificate file
--conf flower configuration file path (default flowerconfig.py)
--cookie_secret
 secure cookie secret
--db flower database file (default flower.db)
--debug run in debug mode (default False)
--enable_events
 periodically enable Celery events (default True)
--format_task use custom task formatter
--help show this help information
--inspect inspect workers (default True)
--inspect_timeout
 inspect timeout (in milliseconds) (default 1000)
--keyfile path to SSL key file
--max_workers maximum number of workers to keep in memory (default 5000)
--max_tasks maximum number of tasks to keep in memory (default 10000)
--natural_time show time in relative format (default False)
--persistent enable persistent mode (default False)
--port run on the given port (default 5555)
--purge_offline_workers
 time (in seconds) after which offline workers are purged from workers
--state_save_interval
 state save interval (in milliseconds) (default 0)
--tasks_columns
 slugs of columns on /tasks/ page, delimited by comma (default name,uuid,state,args,kwargs,result,received,started,runtime,worker)
--unix_socket path to unix socket to bind flower server to
--url_prefix base url prefix
--xheaders enable support for the ‘X-Real-Ip’ and ‘X-Scheme’ headers. (default False)
--task_runtime_metric_buckets
 task runtime prometheus latency metric buckets (default prometheus latency buckets)

TORNADO OPTIONS

--log_file_max_size
 max size of log files before rollover (default 100000000)
--log_file_num_backups
 number of log files to keep (default 10)
--log_file_prefix=PATH
 Path prefix for log files. Note that if you are running multiple tornado processes, log_file_prefix must be different for each of them (e.g. include the port number)
--log_to_stderr
 Send log output to stderr (colorized if possible). By default use stderr if --log_file_prefix is not set and no other logging is configured.
–logging=debug|info|warning|error|none
Set the Python log level. If none, tornado won’t touch the logging configuration. (default info)

USAGE

Launch the Flower server at specified port other than default 5555 (open the UI at http://localhost:5566):

$ celery flower --port=5566

Specify Celery application path with address and port for Flower:

$ celery -A proj flower --address=127.0.0.6 --port=5566

Broker URL and other configuration options can be passed through the standard Celery options (notice that they are after Celery command and before Flower sub-command):

$ celery -A proj --broker=amqp://guest:guest@localhost:5672// flower