What is Chaos Engineering? The Ultimate Guide

Overview:

Unexpected outages and downtimes have not spared even giants like Microsoft, AWS, Atlassian, Google, Netflix, Instagram, and WhatsApp, to name a few. These outages impacted millions of users and millions of dollars in revenue and have lasted from minutes to hours. These incidents indicate that unplanned outages are inevitable even for the best in the business and need a different strategy to tackle for minimum loss.

Source – Downdetector® Insights

Contemporary systems are intricate and dispersed, with various independent and interdependent services interacting on the network to form a business application. These systems are designed with infinite scalability and resilience to ensure optimal performance and zero downtime for users. Despite adhering to best practices during the design and implementation stages, systems can still fail during production, causing a loss of business reputation and performance. To stay ahead of potential issues, organizations are adopting novel techniques to test their applications for expected “Chaos.” Chaos Engineering, a concept originally introduced by Netflix, offers a solution to this need.

What is Chaos Engineering?

Chaos Engineering is a framework and approach used to test the resilience of software systems by intentionally introducing controlled faults in the production system. The purpose is to observe how the system reacts to unexpected failures and provide early visibility to developers, architects, and operations teams so they can make necessary changes and avoid such failures. This approach is becoming increasingly popular and is used by businesses of all sizes, particularly those that rely heavily on software systems for critical operations. Chaos Engineering allows testing for various scenarios, such as Cloud region outages, database failures, network connectivity issues, or service failures, to ensure the system remains resilient. 

How Chaos Engineering works?

To conduct an effective Chaos Engineering experiment, it is essential to have a comprehensive understanding of the system components and their desired state. The Chaos Engineering framework consists of the following steps:

1. Defining a steady state – This involves documenting the expected resilient state of the system.
2. Formulating a hypothesis – Documenting hypothetical failure scenarios to test the system’s resilience against.
3. Designing experiments and defining blast radius – Setting up a controlled environment, often known as a blast radius, to ensure that the user experience of the production system is not compromised.
4. Conducting experiments – Injecting planned faults into the production system.
5. Analyzing results – Collecting and comparing results with the defined steady state. If outcomes do not align with the steady state, use the insights to make necessary improvements in the system and repeat the experiment.

Chaos Engineering Tools:

Chaos Engineering experiments are conducted in the production system with a defined blast radius to ensure that the system’s performance and user experience are not affected by intentional faults.

Various paid and open-source tools like Gremlin, Litmus Chaos, Chaos Toolkit, Chaos Monkey (by Netflix), AWS Fault Injection simulator, and Pumba are available for conducting experiments and injecting faults. The selection of tools depends on factors like test coverage, compatibility with distributed systems, cost, in-built features, ease of use, and available skills in the market.

However, implementing Chaos Engineering experiments without proper planning can lead to the following pitfalls:

1. Uncontrolled damage to the production system and a negative impact on customer experience
2. Downtimes
3. Waste of implementation cost without any fruitful outcomes
4. False positives and negatives due to an inappropriate hypothesis and blast radius.

What are the benefits of Chaos Engineering?

Implementing Chaos Engineering experiments improves system reliability and resilience which provides the following business benefits –

1. Reduced or no downtime resulting in cost savings
2. Advance identification of potential failure
3. Enhanced customer satisfaction
4. Competitive edge in the market

Challenges of Chaos Engineering and the best practices:

The idea of introducing faults in a system to enhance its resilience may seem appealing, but it necessitates technical proficiency and meticulous preparation to achieve success.

To create a successful plan for Chaos testing, the following considerations should be kept in mind:

1. Impact on the production system – Chaos experiments are conducted in the production environment and must be well-planned with a controlled blast radius to avoid any negative impact on end-user performance or system downtime.
2. Technical expertise – Writing chaos experiments requires technical expertise and a thorough understanding of the target system’s architecture.
3. Tooling – No single tool is suitable for every system, and choosing the right toolset for the target system can be challenging due to their limited features.
4. Cost – Significant investment is required to plan for Chaos Engineering.

To conduct Chaos testing effectively, consider the following best practices:

1. Thorough understanding of system components and a well-defined desired steady state.
2. Set hypothesis matching anticipated real-world scenarios.
3. Set a controlled blast radius to ensure no impact on the production system is made.
4. Automate the process and iterate regularly.
5. Choose the right toolset.
6. Implement observability in the system to gather all the necessary details of failure and plan improvements accordingly.

Conclusion:

For a business to succeed, customer trust is paramount. Being able to assure customers that the system works flawlessly all the time can give a competitive advantage. Therefore, ensuring the resilience of business-critical systems is necessary for maintaining consistent growth and service delivery improvement. Implementing Chaos Engineering practice can help achieve this goal, enabling organizations to stay prepared for potential disruptions. 

References:

1. Help Net Security – As per the report and survey conducted 37% of business said that they lost customers and lost 17% of revenue due to downtime and outages and 28% of them said that they are not prepared for unexpected outages
2. CRN – The 15 Biggest Cloud Outages Of 2022
3. CRN – The 10 Biggest Cloud Outages Of 2022 (So Far)