DEV Community: Bugra Derre

Introduce Chaos Platform 2.0 for Azure

Bugra Derre — Sun, 24 Jan 2021 13:26:37 +0000

You develop systems? You operate them on Microsoft Azure? Then this post is for you.

Offering highly available systems means building resilient systems. Architecting your system to expect failure is a core approach nowadays. Chaos engineering embraces the uncertainty and aims at anticipate rare, unpredictable, and disruptive outcomes, so that you can minimize any potential impact on your customers.

The good: you can improve resiliency. Be proactive and embrace failure. Harden your system by breaking it. Do small steps and minimize your blast radius. A bunch of chaos engineering tools will assist you.

The bad: most of the tools require a new learning curve, another portal to log in or installing some black box agents on your virtual machine.

As the existing tooling was too complex for us, we decided to build our own easy-to-use Chaos Platform that focuses on and fully integrates itself into Azure and Azure DevOps.

No need for a new learning curve - the Chaos Platform GUI is easy to use.
Automatize your resilience with the well-known Azure pipeline tasks - we built it for you
Agentless approach - we fully exploit the potential of the Azure API
Safely minimize your blast radius with application level attacks, rather than blowing your virtual machine.
Build trust incrementally. Run Azure resource attacks, when you established a fundamental confidence on your system.

Enjoy to turn failures into resilience with Proofdock Chaos Platform. Check out the full article or jump directly into Chaos Platform in the Azure DevOps Marketplace.

We are happy to get feedback from you. We are Proofdock and enthusiastic about fresh ideas and feedback to improve ourselves.

Cover image is provided by Brett Jordan on Unsplash

Introduce Chaos Middleware for Python Flask: Simulate disruptions to improve resiliency

Bugra Derre — Mon, 28 Sep 2020 05:44:24 +0000

Resiliency is key to software nowadays. It contributes to your application's reliability and plays a major role in the competitive advantage of your business. Resilient applications smartly exploit the strengths of software patterns that handle timeouts, delays and faulty service responses.

Great authors and presenters like Uwe Friedrichsen and Donald Firesmith share their ideas and knowledge about resilient software design. Such articles describe software patterns that overcome disruptions and improve application resiliency in a handsome way.

However, deploying a resilience pattern requires you as a developer to verify your implementation. When touching the ground of verification, things appear to get difficult.

Chaos engineering tools advertise features like stopping a virtual machine, or to terminate pods in your Kubernetes cluster. The "blast radius" gets high here. Higher than a developer expects when exploring a resilience design pattern on Friday afternoon at 2PM.

That is where the Chaos Middleware package goes into action. The Cloud Bug Study states, that neglected error handling - buggy code, timeouts, and others - leads to a great portion of a system's unavailability.

The Chaos Middleware allows you to throw your application at turbulent conditions. It lets you simulate delayed responses or raise errors. Activate disruptions when needed and narrow them down on specific URL paths. The Chaos Middleware gives you the opportunity to minimize the "blast radius" and verify your application's resilience, even on a Friday afternoon.

The next sections will guide you through i) the installation and configuration process in your Flask application ii) and the simulation of delays and application faults. Simulations are enabled by HTTP header requests or by the Chaos Platform control panel.

Installation & configuration

Install the Chaos Middleware for the Flask application:

 cd /path/to/your/flask-application  # Enter your Flask application
 venv/bin/activate  # Active virtual environment
 pip install -U proofdock-chaos-middleware-flask

Configure the Flask application:

 from flask import Flask, jsonify
 from pdchaos.middleware.contrib.flask.flask_middleware import FlaskMiddleware

 app = Flask(__name__)
 app.config['CHAOS_MIDDLEWARE_APPLICATION_NAME'] = 'example-application-name'
 app.config['CHAOS_MIDDLEWARE_APPLICATION_ENV'] = 'example-environment'
 app.config['CHAOS_MIDDLEWARE_PROOFDOCK_API_TOKEN'] = 'eyJ0eXAi...05'

 middleware = FlaskMiddleware(app)

 # Your business logic here

 @app.route("/products")
 def hello():
     return "Hello, from the products"

 if __name__ == "__main__":
     app.run()

Start your application

Simulate delays

Trigger delays by setting the x-proofdock-attack request header. The Chaos Middleware detects any value inside this header.

Set the header's value to {"actions":[{"name":"delay","value":"15"}]}. The value describes the simulation name and its value in seconds. The described simulation delays the response by 15 seconds.

For the simulation, we use the Postman client to visualize the HTTP requests.

A delay simulation

Simulate faults

Raise exceptions by setting the x-proofdock-attack request header.

Set the header's value to {"actions":[{"name":"fault","value":"Exception"}]}. The value describes the simulation name and its value as a fully qualified name of the exception to be raised. The simulation will raise the Exception.

A fault simulation

A control panel for Azure DevOps users

A more appealing way to control such attacks is the usage of the control panel provided by Proofdock's Chaos Platform. The Chaos Platform extends the Azure DevOps with chaos engineering capabilities. The control panel allows you to control application attacks via a graphical user interface and lets your application cache the configured attack. Check out the docs when you are interested in the Chaos Platform.

The control panel in Azure DevOps

Thank you

We hope you had fun and learned some new aspects on resilience.

We are Proofdock, a software tech company located in Germany helping engineers build more resilient and reliable software products. Check out the Chaos Platform for Microsoft Azure and explore your system.

References

Check out the source code at GitHub
Read the docs
Install the Chaos Platform

Chaos Middleware: Simulate disruptions in Django applications to improve resiliency

Bugra Derre — Tue, 08 Sep 2020 05:38:03 +0000

However, deploying a resilience pattern requires you as a developer to verify your implementation. When touching the ground of verification, things appear to get difficult.

The next sections will guide you through i) the installation and configuration process in your Django application ii) and the simulation of delays and application faults. Simulations are enabled by HTTP header requests or by the Chaos Platform control center.

Installation & configuration

Install the Chaos Middleware for the Django application:

 cd /path/to/your/django-application  # Enter your Django application
 venv/bin/activate  # Active virtual environment
 pip install -U proofdock-chaos-middleware-django

Configure the Django application:

 # Activate the ``Chaos Middleware`` component by adding 
 # it to the MIDDLEWARE list in your Django settings
 MIDDLEWARE = [
   '..'
   'pdchaos.middleware.contrib.django.django_middleware.DjangoMiddleware',
   '..'
 ]

 # Set the Chaos Middleware settings
 CHAOS_MIDDLEWARE = {
   'CHAOS_MIDDLEWARE_APPLICATION_NAME': 'example-application-name',
   'CHAOS_MIDDLEWARE_APPLICATION_ENV': 'example-environment'
 }

Start your application