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Chaos Engineering first emerged in 2010 by Netflix to test system stability, and it has become the next big thing for testing in DevOps. It began with the launch of various chaos testing tools, such as Chaos Monkey from Netflix, LitmusChaos, Chaos Gorilla, Gremlin, Chaos Mesh, and so on. It’s being adopted by numerous organizations and across engineering teams, including developers, quality assurance, and site reliability.
As defined by Google, “Chaos Engineering is simply the process of testing a system’s capability to ensure that it can withstand turbulent conditions. It relies on principles of Chaos Engineering, focusing on random and unpredictable behavior to build more resilient systems.”
Chaos Engineering emerged as a preventive measure to identify the failure scenarios in systems before they develop and cause downtime. You can identify and fix issues immediately by doing pragmatic chaos testing on how a system responds under injected breakage. This helps safeguard end users from any negative impacts.
Read on to learn how Chaos Engineering improves and benefits the resiliency of large-scale distributed systems and microservices.
Over the past few years, leading organizations in the industry have faced costly network outages. For example, the 2018 Amazon blackout incurred a loss of up to $99 Million, and the 2019 Meta Platforms Inc. (Facebook, Messenger, WhatsApp, and Instagram) downtime cost over $89.6 Million.
These mishaps are ongoing problems that every enterprise has faced since the internet began. Recently, the Information Technology Intelligence Testing (ITIC) 2021 Global Server Hardware, Server OS Reliability Survey indicated that the COVID-19 pandemic, security hacks, and remote working are the driving factors of these blackouts. All of these factors culminate in massive revenue loss and maintenance costs.
But money is not the only thing that an entity loses while facing outages. Outages also create a domino effect, and along with the money, there is the loss of customer and employee confidence, brand integrity, stock prices, and more. In some cases, companies are even subject to legal action by their stakeholders.
With such vast risks stemming from a single problem, a long-term solution for resilient systems was long overdue. Chaos Engineering now allows companies to:
For enterprises, these Chaos Engineering examples are essential in addressing the identified weaknesses before they cause data loss or service impacts.
Let’s dive into some of the significant benefits of Chaos Engineering.
Testing the limitations of your applications and distributed systems can provide a vast range of information for the development teams and organizations. Here are a handful of the benefits of Chaos Engineering in practice with chaos testing tools.
Using a Chaos Engineering tool to conduct planned chaos experiments will help test the system's capability and thus increase its resilience.
While conducting these chaos experiments, you must choose your metrics wisely and hypothesize the steady state. The initial Chaos Engineering experiments can take place in staging or any pre-production stage where the blast radius is minimal. This makes sure that if any negative impact occurs, users aren’t affected.
Once you and your team gain confidence to perform Chaos Engineering experiments, you can run experiments close to production. All experiments are conducted directly using the actual input received in the production environment in the ideal implementation.
As the production environment is treated as the real system, advancing your experiments here gives you a precise idea of what your end users would experience. The system will experience fewer network failures and service disruption, which will in turn improve the user experience.
The insights that chaos engineers gain from these chaotic experiments improve the engineering team's knowledge. This results in faster response times and improved collaboration and confidence. Furthermore, these insights can be used to educate newer colleagues.
With the technical team having been made aware and brought up to speed from the previous chaos experimentations, troubleshooting, repairs, and incident responses can increase in velocity. Therefore, insights received after running chaos testing can lead to a reduction in future production incidents.
Gamedays are one way to improve incident response time. The idea is to provide room in your workflow for the team to practice what they'll do if something goes wrong with the production environment.
Chaos testing is considered one of the most holistic approaches to performance engineering and testing methodologies. Regularly conducting chaos experiments develops confidence in the distributed systems, and it helps to make sure that applications perform well despite major unexpected failures.
In the current DevOps industry and Software Development Life Cycle, Chaos Engineering has evolved into a fantastic tool that may assist organizations not only in improving entire system resources, resiliency, flexibility, and velocity, but also in operating distributed systems.
Along with these advantages, it allows us to address problems before they can negatively impact the overall physical cloud infrastructure. Chaos Engineering implementation is critical and should be adopted for better results.
Leading companies like Microsoft, Amazon, LinkedIn, and many more have implemented Chaos Engineering in their tech stack. Chaos Engineering should be added as a performance-achieving metric for strengthening the resiliency of any organization that constructs and manages a distributed system and aspires to achieve a high rate of development velocity.
The marketplace for Chaos Engineers has opened many arenas and opportunities. Chaos Engineering is still a young field, with new techniques and Chaos Engineering tools emerging all the time. As a true supporter of this resilient technology, I have shared this article about integrating Chaos Engineering and its benefits as experienced by its customers.
Please feel free to look at the Harness Chaos Engineering tool, or the full Harness Software Delivery Platform to see how we can help you take software delivery to the next level.
LitmusChaos is an amazing Chaos Engineering tool for conducting chaos testing on your systems. With 2.7k+ GitHub Stars and around 1300 Slack Community Members, we’re a lively community for young learners. Check out our Chaos Hub, which is an open-source marketplace containing all of the different chaos experiments offered by LitmusChaos, pod-delete being our most popular chaos experiment.
With LitmusChaos, you can start your journey toward becoming a Chaos Engineer. Want to get help with queries, learnings, and contributions? Join the LitmusChaos Chaos Engineering Slack community. To join, just follow these steps!
Step 1: Join the Kubernetes Slack using the following link: https://slack.k8s.io/
Step 2: Join the #litmus channel on the Kubernetes Slack, or use this link after joining the Kubernetes Slack: https://slack.litmuschaos.io/
Looking forward to seeing all of the amazing folks from the open source world! Here are some important links for you to reference:
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