What Is Chaos Engineering? Principles, Best Practices, Advantages
As software systems get increasingly complex and distributed, adopting Agile practices that increase the flexibility and speed of development is the need of the hour. Developers need to have extreme confidence in the systems they build. They must ensure the interactions these systems have with other services in a distributed environment do not cause unpredictable or unfavorable outcomes. They also need to ensure that disruptive real-world events affecting production environments do not make these distributed systems inherently chaotic.
This is where chaos engineering comes in place, enabling development teams to ensure the high quality of the software they are developing while it is already in production. This new approach is slowly revolutionizing how teams test software resilience.
- What is chaos engineering?
- Principles of Chaos Engineering
- Difference Between Testing and Chaos Engineering
- How Chaos Engineering Works?
- Best Practices of Chaos Engineering
- Example of Chaos Engineering
- Challenges in Chaos Engineering
- Benefits of Chaos Engineering
- How Does Chaos Engineering Help Organizations?
- How Can Organizations Improve the Quality of Software with Chaos Testing?
What Is Chaos Engineering?
Chaos engineering is a practice that enables testers to improve the quality of the application under development. Instead of fixing errors and issues after they impact the functionality or performance of software, chaos engineering helps identify gaps and weaknesses before they manifest across the system and lead to abnormal behaviors.
Right from unavailable services to improperly tuned timeouts, outages, crashes, and more – by proactively addressing weaknesses, chaos engineering helps manage the "chaos" inherent in modern systems. Such management helps increase the speed and flexibility of software development and delivery.
Furthermore, it increases the teams confidence in their production deployments despite their complexity.
Moreover, chaos engineering ensures testing teams continue to test the software under development – even after it has reached the production stage. This paves the way for continuous testing.
Since teams can push the application as far as possible without causing major performance issues, it helps make the software extremely robust and resilient.
Principles of Chaos Engineering
- Start in a Controlled Environment: Begin testing in a non-production environment and gradually extend to production in a controlled manner.
- Define Steady State: Establish normal behavior to measure deviations effectively.
- Hypothesize About Potential Failures: Predict what could go wrong and how the system should behave under stress.
- Introduce Variables Gradually: Introduce chaos in a controlled, incremental manner to understand its impact.
- Learn and Adjust: Analyze the results, learn from the experiments, and make necessary adjustments.
Difference Between Testing and Chaos Engineering
- Scope: Traditional testing often focuses on known issues and predictable scenarios, whereas chaos engineering tests for unpredictable and random events.
- Objective: Testing generally aims for error-free functionality, while chaos engineering aims to uncover hidden vulnerabilities.
- Methodology: Testing is usually systematic and controlled, whereas chaos engineering involves introducing unexpected failures.
How Chaos Engineering Works?
- Establish a Baseline: Determine the normal operating conditions of the system.
- Formulate Hypotheses: Predict how the system will react under different failure scenarios.
- Conduct Experiments: Introduce failures in a controlled environment and observe the system’s response.
- Analyze Results: Evaluate the system’s behavior against the hypotheses and learn from the discrepancies.
Best Practices of Chaos Engineering
- Understand Normal System Behavior: Understand how the system operates under normal conditions.
- Simulate Realistic Scenarios: Focus on likely and relevant failure scenarios.
- Minimize Impact: Ensure that chaos experiments are conducted to minimize disruption to normal operations.
- Iterative Approach: Start with small experiments and gradually increase complexity.
- Cross-functional collaboration: Involve various teams (development, operations, security) in planning and executing chaos experiments.
Example of Chaos Engineering
Netflix's use of Chaos Monkey is a classic example. It randomly disables production instances to test system resilience. This proactive approach helped Netflix maintain service during major outages that affected other major websites.
Challenges in Chaos Engineering
- Controlling the Blast Radius: Ensuring the chaos experiments do not cause excessive damage or disruption.
- Complexity in Large Systems: The more complex the system, the more challenging it is to predict the outcomes of chaos experiments.
- Balancing Risk and Learning: Finding the right balance between learning from experiments and not risking critical system functionality.
Benefits of Chaos Engineering
- Identifies System Weaknesses: Chaos engineering helps uncover vulnerabilities in a system before they can be exploited or cause system failure.
- Increases System Resilience: By intentionally introducing failures, chaos engineering strengthens the system’s ability to withstand turbulent conditions.
- Improves Customer Satisfaction: Enhanced system resilience reduces downtime, improving the user experience.
- Facilitates Proactive Problem Solving: It allows teams to proactively address potential issues rather than reacting to them post-occurrence.
- Enhances Understanding of the System: Chaos engineering provides deeper insights into the system’s behavior under stress.
How Does Chaos Engineering Help Organizations?
- Ensure proper and frequent coordination between different teams, so everyone is aware of the different chaos experiments taking place.
Introduce random and unpredictable behavior in software systems and identify vulnerabilities.
- Thoroughly test distributed computing systems using real-world conditions and ensure they can endure unexpected disruptions.
Inject likely failures and bugs into the software and simulate as many realistic conditions as possible.
- Uncover blind spots, hidden bugs, and performance bottlenecks impacting system performance and/or user experience.
- Make necessary changes to enhance software resilience, thus increasing confidence in the system’s abilities.
- Have redundancy in place to ensure services remain available if chaos experiments cause issues.
How Can Organizations Improve the Quality of Software with Chaos Testing?
If you want to thoroughly test how certain challenges like network delays or power outages can wreak havoc on your software in production, you need to enable chaos testing. Using chaos testing, you can introduce different issues into your software and gauge how they tend to:
- Cause performance issues
- User experience challenges, or
- Entire data center segments to go offline.
Chaos testing also enables you to carry out health checks on your application. As such, you can identify security vulnerabilities and optimize or even get rid of unused system resources.
If you are looking to improve the quality of software via chaos testing, here are some things to consider:
- Understand and state how the system needs to operate under normal conditions while specifying the constituents of a normal working state.
Make a list of potential weaknesses that can impact the software’s availability, performance, security, or scalability.
- Formulate necessary test cases and what-if hypotheses to evaluate the performance and integrity of the system under development.
- Conduct the required experiments under a controlled environment to gauge the consequences of unfavorable circumstances. Measure and evaluate the impact of issues and take steps to fix them in time.
As companies move to the cloud, software systems are getting increasingly distributed – and thus more complicated. As the chaos within and outside these systems grows, organizations have to find ways to adapt to it.
To that end, chaos engineering allows teams to test how software systems perform under adverse conditions. By introducing unexpected or unfavorable circumstances into software in production, teams can enhance not just quality but also resiliency.
Enable chaos testing today to avoid things going wrong in the production environment and minimize the chances of your application going down, defects impacting user experience, or performance getting degraded. Reach out to us to know more.
Director, Product Evangelist at ACCELQ
Geosley is a Test Automation Evangelist and Community builder at ACCELQ. Being passionate about continuous learning, Geosley helps ACCELQ with innovative solutions to transform test automation to be simpler, more reliable, and sustainable for the real world.