Mallory Mooney discusses the challenges of identifying system failures in modern cloud applications and introduces chaos engineering as a solution to proactively find potential points of failure within cloud infrastructure. Chaos engineering tests a system's resilience by deliberately injecting failures into various components, allowing engineers to gain a better understanding of how their applications function under stress. Security-focused chaos engineering verifies that systems respond appropriately to common threats, similar to red, blue, and purple teaming. The key components of security-focused CE include defining a steady state for your systems, asking questions about potential vulnerabilities, injecting failure, and monitoring results. Engineers can use threat modeling practices like asking high-level questions about business-critical workflows and user journeys to guide the process. They can then focus on individual services and resources that make up those workflows, identifying components such as API servers, workloads, pods, and containers. Security-focused experiments can take many forms, including controlled denial-of-service (DoS) attacks or attempts to spin up new resources with malicious code. The last step in the process involves detecting vulnerabilities or other security issues that surfaced as a result of the experiment, using monitoring and threat detection systems. Mallory Mooney also discusses practical ways to apply these steps to Kubernetes workloads, which are critical yet complex components of cloud infrastructure. She provides examples of experiments, such as identifying misconfigured API servers or assessing visibility into new resources, and highlights the importance of tools like Datadog in enhancing chaos engineering experiments by automatically discovering common issues that leave systems vulnerable.