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celery-exporter Build Status Code style: black


Table of Contents

Why another exporter?

While I was adding Celery monitoring to a client site I realized that the existing brokers either didn't work, exposed incorrect metric values or didn't expose the metrics I needed. So I wrote this exporter which essentially wraps the built-in Celery monitoring API and exposes all of the event metrics to Prometheus in real-time.


  • Tested for both Redis and RabbitMQ
  • Uses the built in real-time monitoring component in Celery to expose Prometheus metrics
  • Tracks task status (task-started, task-succeeded, task-failed etc)
  • Tracks which workers are running and the number of active tasks
  • Follows the Prometheus exporter best practises
  • Deployed as a Docker image or Python single-file binary (via PyInstaller)
  • Exposes a health check endpoint at /health
  • Grafana dashboards provided by the Celery-mixin
  • Prometheus alerts provided by the Celery-mixin

Dashboards and alerts

Alerting rules can be found here. By default we alert if:

  • A task failed in the last 10 minutes.
  • No Celery workers are online.

Tweak these to suit your use-case.

The Grafana dashboard (seen in the image above) is here. You can import it directly into your Grafana instance.

There's another Grafana dashboards that shows an overview of Celery tasks. An image can be found in ./images/celery-tasks-overview.png. It can also be found here.


Celery needs to be configured to send events to the broker which the exporter will collect. You can either enable this via Celery configuration or via the Celery CLI.

Enable events using the CLI

To enable events in the CLI run the below command. Note that by default it doesn't send the task-sent event which needs to be configured in the configuration. The other events work out of the box.

$ celery -A <myproject> control enable_events

Enable events using the configuration:

# In
worker_send_task_events = True
task_send_sent_event = True

Configuration in Django:

# In
Running the exporter

Using Docker:

docker run -p 9808:9808 danihodovic/celery-exporter --broker-url=redis://redis.service.consul/1

Using the Python binary (for-non Docker environments):

curl -L -o ./celery-exporter
chmod+x ./celery-exporter
./celery-exporter --broker-url=redis://redis.service.consul/1

There's a Helm in the directory charts/celery-exporter for deploying the Celery-exporter to Kubernetes using Helm.

Environment variables

All arguments can be specified using environment variables with a CE_ prefix:

docker run -p 9808:9808 -e CE_BROKER_URL=redis://redis danihodovic/celery-exporter
Specifying optional broker transport options

While the default options may be fine for most cases, there may be a need to specify optional broker transport options. This can be done by specifying one or more --broker-transport-option parameters as follows:

docker run -p 9808:9808 danihodovic/celery-exporter --broker-url=redis://redis.service.consul/1 \
  --broker-transport-option global_keyprefix=danihodovic \
  --broker-transport-option visibility_timeout=7200

In case of extended transport options, such as sentinel_kwargs you can pass JSON string:, for example:

docker run -p 9808:9808 danihodovic/celery-exporter --broker-url=sentinel://sentinel.service.consul/1 \
  --broker-transport-option master_name=my_master \
  --broker-transport-option sentinel_kwargs="{\"password\": \"sentinelpass\"}"

The list of available broker transport options can be found here:

Specifying an optional retry interval

By default, celery-exporter will raise an exception and exit if there are any errors communicating with the broker. If preferred, one can have the celery-exporter retry connecting to the broker after a certain period of time in seconds via the --retry-interval parameter as follows:

docker run -p 9808:9808 danihodovic/celery-exporter --broker-url=redis://redis.service.consul/1 \
Grafana Dashboards & Prometheus Alerts

Head over to the Celery-mixin in this subdirectory to generate rules and dashboards suited to your Prometheus setup.


Name Description Type
celery_task_sent_total Sent when a task message is published. Counter
celery_task_received_total Sent when the worker receives a task. Counter
celery_task_started_total Sent just before the worker executes the task. Counter
celery_task_succeeded_total Sent if the task executed successfully. Counter
celery_task_failed_total Sent if the execution of the task failed. Counter
celery_task_rejected_total The task was rejected by the worker, possibly to be re-queued or moved to a dead letter queue. Counter
celery_task_revoked_total Sent if the task has been revoked. Counter
celery_task_retried_total Sent if the task failed, but will be retried in the future. Counter
celery_worker_up Indicates if a worker has recently sent a heartbeat. Gauge
celery_worker_tasks_active The number of tasks the worker is currently processing Gauge
celery_task_runtime_bucket Histogram of runtime measurements for each task Histogram
celery_queue_length The number of message in broker queue Gauge
celery_active_consumer_count The number of active consumer in broker queue (Only work for RabbitMQ and Qpid broker, more details at here) Gauge

Used in production at and


Pull requests are welcome here!

To start developing run commands below to prepare your environment after the git clone command:

# Install dependencies and pre-commit hooks
poetry install
pre-commit install

# Test everything works fine
pre-commit run --all-files
docker-compose up -d
pytest --broker=memory      --log-level=DEBUG
pytest --broker=redis       --log-level=DEBUG
pytest --broker=rabbitmq    --log-level=DEBUG