CPU attacks, commonly employed by Gremlin users, are strategic exercises to consume CPU capacity on various platforms like hosts, containers, and Kubernetes resources, revealing potential system vulnerabilities such as poor performance and instability. These attacks are crucial for ensuring systems maintain reliability even under heavy CPU usage, which can be unpredictable due to factors like increased production demands or unexpected traffic spikes. By simulating scenarios such as stress testing and noisy neighbor environments, CPU attacks help validate system stability for high-traffic events and optimize infrastructure capacity, thus reducing operating costs. Gremlin offers fine-grained control over these attacks, allowing users to specify CPU consumption percentage and the number of cores involved, thereby enabling tailored tests that can scale from small, focused experiments to larger, comprehensive ones. Monitoring CPU usage during these attacks is essential to understanding system performance, and Gremlin provides tools for visualizing these metrics. The process encourages gradual scaling of the attack's scope and magnitude to safely assess and improve system resilience, with the results documented for organizational learning and improvement.