Chaos testing is an experimental approach rooted in chaos engineering that involves deliberately introducing failures such as shutting down servers, introducing latency or corrupting data in a controlled environment. The goal is to observe how systems respond to unexpected disruptions and identify any weaknesses that could lead to system failures or unplanned downtime. Originating from experiments conducted by pioneers like Netflix, who famously created Chaos Monkey as part of the Simian Army, chaos testing has been widely adopted by teams leveraging cloud providers like Amazon Web Services. By integrating chaos testing into your software development lifecycle, you strengthen incident response and ensure systems can respond gracefully to adverse conditions. Chaos testing is a critical strategy for API resilience and reliability, allowing teams to prepare for potential outages, enhance system reliability through iterative experiments, allow teams to learn from each chaos testing experiment and continuously improve their systems, test incident response protocols, and test error handling mechanisms. It simulates external service unavailability, introduces response delays, handles API errors such as 404s, 500s, and unauthorized requests, handles malformed data, simulates rate limiting, experiments with authentication and authorization failures, and integrates chaos testing and engineering tools to streamline the process of simulating real-world failures in a production-like environment.