Warning: This document is for the development version of Dramatiq. The latest version is v1.3.0.

Advanced Topics

Brokers

Multi-tenancy

With Dramatiq you can run multiple logical apps on the same broker. The way you do this is different for each broker, but fairly simple in each case.

RabbitMQ

RabbitMQ has the concept of virtual hosts built into it. They provide logical grouping and separation of resources. You can create virtual hosts using the rabbitmqctl command:

$ rabbitmqctl add_vhost app1
$ rabbitmqctl set_permissions -p app1 my_user ".*" ".*" ".*"

You can then pass that vhost to RabbitmqBroker when you instantiate it.

Redis

The RedisBroker takes a namespace parameter that you can use to logically split queues across multiple apps.

Messages

Message Persistence

Messages sent to Dramatiq brokers are persisted to disk and survive across broker reboots. Exactly how often messages are flushed to disk depends on your broker.

Messages that have been pulled by workers but not processed are returned to the broker on graceful shutdown and any messages that are in flight when a worker is terminated are going to be redelivered later. Messages are only ever acknowledged to (removed from) the broker after they have been successfully processed.

When a worker goes down while processing messages (eg. due to hardware, power or network failure) then the messages it pulled from the broker will eventually be re-delivered to it (assuming it recovers) or another worker.

Message Results

Dramatiq can store actor return values to Memcached and Redis by leveraging the Results middleware. In most cases you can get by without needing this capability so the middleware is not turned on by default. When you do need it, however, it’s there.

Message Interrupts

Dramatiq may interrupt message processing mid-execution. This is achieved by asynchronously raising an exception in the worker thread that is currently processing the message.

Attention

Currently, interrupts are only supported on CPython and are subject to the restrictions of the GIL. This means the interupt exception will only be raised the next time that thread acquires the GIL, and they are unable to cancel system calls.

Interrupts are used by the following middleware:

In order to gracefully handle interrupts, wrap the code in a try/except block, catching the appropriate exception type. To attempt to requeue the message, raise an exception to indicate failure.

import dramatiq
from dramatiq.middleware import Interrupt

@dramatiq.actor(max_retries=3, notify_shutdown=True)
def long_running_task:
    try:
        setup()
        do_work()
    except Shutdown:
        cleanup()
        raise

Enqueueing Messages from Other Languages

You can enqueue Dramatiq messages using any language that has bindings to one of its brokers. All you have to do is push a JSON-encoded dictionary containing the following fields to your queue:

{
  "queue_name": "default",     // The name of the queue the message is being pushed on
  "actor_name": "add",         // The name of the actor that should handle this message
  "args": [1, 2],              // A list of positional arguments that are passed to the actor
  "kwargs": {},                // A dictionary of keyword arguments that are passed to the actor
  "options": {},               // Arbitrary options that are used by middleware. Leave this empty
  "message_id": "unique-id",   // A UUID4 value representing the message's unique id in the system
  "message_timestamp": 0,      // The UNIX timestamp in milliseconds representing when the message was first enqueued
}

Using RabbitMQ

Assuming you want to enqueue a message on a queue named default, publish a persistent message to that queue in RabbitMQ.

Using Redis

Assuming you want to enqueue a message on a queue named default, run:

> HSET default.msgs $YOUR_MESSAGE_ID $YOUR_MESSAGE_PAYLOAD
> RPUSH default $YOUR_MESSAGE_ID

Workers

Worker Exit Codes

Dramatiq uses process exit codes to denote several scenarios:

Code Description
0 Returned when the process exits gracefully.
1 Returned when the process is killed.
2 Returned when a module cannot be imported or when a command line argument is invalid.
3 Returned when a broker connection cannot be established during worker startup.
4 Returned when a PID file is set and Dramatiq is already running.

Controlling Workers

The main Dramatiq process responds to several signals:

$ kill -TERM [master-process-pid]

INT and TERM

Sending an INT or TERM signal to the main process triggers graceful shutdown. Consumer threads will stop receiving new work and worker threads will finish processing the work they have in flight before shutting down. Any tasks still in worker memory at this point are re-queued on the broker.

If you send a second INT or TERM signal then the worker processes will be killed immediately.

HUP

Sending HUP to the main process triggers a graceful shutdown followed by a reload of the workers. This is useful if you want to reload code without completely restarting the main process.

Using gevent

Dramatiq comes with a CLI utility called dramatiq-gevent that can run workers under gevent. The following invocation would run 8 worker processes with 250 greenlets per process for a total of 2k lightweight worker threads:

$ dramatiq-gevent my_app -p 8 -t 250

If your tasks spend most of their time doing network IO and don’t depend on C extensions to execute those network calls then using gevent could provide a significant performance improvement.

I suggest at least experimenting with it to see if it fits your use case.

Prometheus Metrics

Prometheus metrics are automatically exported by workers whenever you run them using the command line utility (assuming you’re using the Prometheus middleware). By default, the exposition server listens on port 9191 so you can tell Prometheus to scrape that or you can specify what host and port it should listen on by setting the dramatiq_prom_host and dramatiq_prom_port environment variables.

The following metrics are exported:

dramatiq_messages_total
A counter for the total number of messages processed.
dramatiq_message_errors_total
A counter for the total number of errored messages.
dramatiq_message_retries_total
A counter for the total number of retried messages.
dramatiq_message_rejects_total
A counter for the total number of dead-lettered messages.
dramatiq_messages_inprogress
A gauge for the number of messages currently being processed.
dramatiq_delayed_messages_inprogress
A gauge for the number of delayed messages currently in memory.
dramatiq_message_duration_milliseconds
A histogram for the time spent processing messages.

All metrics define labels for queue_name and actor_name.

Grafana Dashboard

You can find a Grafana dashboard that displays these metrics here.

Gotchas with Prometheus

The Prometheus client for Python is a bit finicky when it comes to exporting metrics from a multi-process configuration. If your own app uses Prometheus, then you should export prometheus_multiproc_dir and dramatiq_prom_db environment variables – both pointing to an existing folder – and remove any files in that folder before running Dramatiq. For example:

mkdir -p /tmp/dramatiq-prometheus \
  && rm -r /tmp/dramatiq-prometheus/* \
  && env prometheus_multiproc_dir=/tmp/dramatiq-prometheus \
         dramatiq_prom_db=/tmp/dramatiq-prometheus \
         dramatiq app

If you don’t do this, then metrics will likely fail to export properly.