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