django-hurricane 0.6.0

Hurricane is an initiative to fit Django perfectly with Kubernetes.

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Hurricane is an initiative to fit Django perfectly with Kubernetes. It is supposed to cover many capabilities in order to run Django in a cloud-native environment, including a Tornado-powered Django app server.

Intro

Django was developed with the batteries included-approach and already handles most of the challenges around web development with grace. It was initially developed at a time when web applications got deployed and run on a server (physical or virtual). With its pragmatic design it enabled many developers to keep up with changing requirements, performance and maintenance work.
However, service architectures have become quite popular for complex applications in the past few years. They provide a modular style based on the philosophy of dividing overwhelming software projects into smaller and more controllable parts. The advantage of highly specialized applications gained prominence among developers, but introduces new challenges to the IT-operation.
However, with the advent of Kubernetes and the cloud-native development philosophy a couple of new possibilities emerged to run those service-based applications even better. Kubernetes is a wonderful answer for just as many IT-operation requirements as Django is for web development. The inherent monolithic design of Django can be tempting to roll out recurring operation patterns with each application. It's not about getting Django to run in a Kubernetes cluster (you may already solved this), it's about integrating Django as tightly as possible with Kubernetes in order to harness the full power of that platform. Creating the most robust, scalable and secure applications with Django by leveraging the existing expertise of our favorite framework is the main goal of this initiative.

Parts

Hurricane is supposed to make the most out of the existing Django ecosystem without reinventing the wheel. We will collect best-practices and opinions about how to run Django in Kubernetes and put them on Hurricane's roadmap.

Application Server

Why another app server instead of uwsgi, gunicorn or mod_wsgi? We need a cloud-native app server which is much more tidily coupled to the Django application itself. Think of special url routes for Kubernetes probes! Building a special View in each and every Django application is not an appropriate solution. What about the Kubernetes Metrics API? That's all something we don't want to take care of in our Django code.
Those traditional app servers (i.e. uwsgi et.al.) have a highly optimized process model for bare-server deployments with many CPUs, multiple threads and so on. In Kubernetes the scaling of an application is done through the Replication-value in a workload description manifest. This is no longer something we configure with app server parameters.

Todo

• Basic setup, POC, logging
• Different endpoints for all Kubernetes probes
• Extensive documentation
• Django management command execution before serving
• actual Tornado integration (currently uses the tornado.wsgi.WSGIContainer)
• web sockets with Django 3
• Testing, testing in production
• Load-testing, automated performance regression testing
• Implement the Kubernetes Metrics API
• Implement hooks for calling webservices (e.g. for deployment or health state changes)
• Add another metrics collector endpoint (e.g Prometheus)

Celery

In the future, Hurricane should provide a sophisticated Django-celery integration with health checks and Kubernetes-scaling.

Todo

• Concept draft
• Kubernetes health probes for celery workers
• Kubernetes health probes for celery beat
• Implement hooks for calling webservices (e.g. for deployment or health state changes)
• Implement the Kubernetes Metrics API

AMQP Worker/Consumer

Hurricane provides a generic yet simple amqp worker with health checks and Kubernetes-scaling.

Todo

• Concept draft
• Kubernetes health probes for amqp workers
• Implement hooks for calling webservices (e.g. for deployment or health state changes)
• Implement the Kubernetes Metrics API

Guidelines

In order to keep Django as lean and swift as possible we have to get rid of several parts: unneeded middlewares, apps and other overhead. A small Django-based service does not need all the batteries Django comes with. In many cases the superb ORM (object relation mapper) and a simple HTTP-interface is all it needs.

Todo

• Concept draft
• Cookiecutter template
• Container (Docker) best-practices

Installation

Hurricane can be installed from Python Package Index:

pip3 install hurricane

Add "hurricane" to your INSTALLED_APPS:

INSTALLED_APPS += (
    'hurricane',
)

Usage

Application Server

Run the application server

In order to start the Django app run the management command serve:

python manage.py serve

It simply starts a Tornado-based application server ready to serve the Django application. No need for any other app server.

Command options for serve-command:

Option	Help
--static	Serve collected static files
--media	Serve media files
--autoreload	Reload code on change
--debug	Set Tornado's Debug flag (don't confuse with Django's DEBUG=True)
--port	The port for Tornado to listen on (default is port 8000)
--probe-port	The port for Tornado probe routes to listen on (default is the next port of --port)
--startup-probe	The exposed path (default is /startup) for probes to check startup
--readiness-probe	The exposed path (default is /ready) for probes to check readiness
--liveness-probe	The exposed path (default is /alive) for probes to check liveness
--no-probe	Disable probe endpoint
--no-metrics	Disable metrics collection
--req-queue-len	Threshold of length of queue of request, which is considered for readiness probe
--command	Repetitive command for adding execution of management commands before serving

Probes and the System Check Framework

The probe endpoint invokes Django's check framework (please see: https://docs.djangoproject.com/en/2.2/topics/checks/). This endpoint is called in a certain interval by Kubernetes, hence we get regular checks on the application. That's a well-suited approach to integrate custom checks (please refer to the Django documentation how to do that) and get health and sanity checks for free. Upon unhealthy declared applications (error-level) Kubernetes will restart the application and remove unhealthy PODs once a new instance is in healthy state.
The port for the probe route is separated from the application's port. If not specified, the probe port is one port added to the application's port.

Logging

It should be ensured, that the hurricane logger is added to Django logging configuration, otherwise log outputs will not be displayed when application server will be started. Log level can be easily adjusted to own needs.

AMQP Worker

Run the AMQP (0-9-1) Consumer

In order to start the Django-powered AMQP consumer following consume-command can be used:

python manage.py consume HANLDER 

This command starts a Pika-based amqp consumer which is observed by Kubernetes. The required Handler argument is the dotted path to an _AMQPConsumer implementation. Please use the TopicHandler as base class for your handler implementation as it is the only supported exchange type at the moment. It's primarily required to implement the on_message(...) method to handle incoming amqp messages.

In order to establish a connection to the broker one of the following options can be used:
Load from Django Settings or environment variables:

Variable	Help
AMQP_HOST	amqp broker host
AMQP_PORT	amqp broker port
AMQP_VHOST	virtual host (defaults to "/")
AMQP_USER	username for broker connection
AMQP_PASSWORD	password for broker connection

The precedence is: 1. command line option (if available), 2. django settings, 3. environment variable

Command options for consume-command:

Option	Help
--queue	The queue name this consumer declares and binds to
--exchange	The exchange name this consumer declares
--amqp-host	The broker host name in the cluster
--amqp-port	The broker service port
--amqp-vhost	The consumer's virtual host to use
--startup-probe	The exposed path (default is /startup) for probes to check startup
--readiness-probe	The exposed path (default is /ready) for probes to check readiness
--liveness-probe	The exposed path (default is /alive) for probes to check liveness
--probe-port	The port for Tornado probe routes to listen on (default is the next port of --port)
--no-probe	Disable probe endpoint
--autoreload	Reload code on change
--debug	Set Tornado's Debug flag (don't confuse with Django's DEBUG=True)
--reconnect	Reconnect the consumer if the broker connection is lost (not recommended)

Example AMQP Consumer

Implementation of a basic AMQP handler with no functionality:

# file: myamqp/consumer.py
from hurricane.amqp.basehandler import TopicHandler


class MyTestHandler(TopicHandler):
    def on_message(self, _unused_channel, basic_deliver, properties, body):
        print(body.decode("utf-8"))
        self.acknowledge_message(basic_deliver.delivery_tag)

This handler can be started using the following command:

python manage.py consume myamqp.consumer.MyTestHandler --queue my.test.topic --exchange test \ 
--amqp-host 127.0.0.1 --amqp-port 5672

Test Hurricane

In order to run the entire test suite following commands should be executed:

pip install -r requirements.txt
coverage run manage.py test
coverage combine
coverage report

Important: the AMQP testcase requires Docker to be accessible from your current user as it spins up a container with RabbitMQ. The AMQP consumer under test will connect to it and exchange messages using the TestPublisher class.

Docs

To build the docs following command should be started in a docs directory:

make html