If an application has 10 or less actions per minute, what will happen regarding anomaly detection?

When an application has 10 or fewer actions per minute, the system's capacity for effective anomaly detection is limited. Anomaly detection algorithms typically rely on a substantial amount of data over time to establish a baseline of normal behavior and identify deviations from that baseline. With such a low volume of actions, the system doesn't gather enough data points to create a reliable model for what would be considered 'normal' behavior.

As a result, the system will not automatically detect anomalies because it lacks sufficient data to perform this analysis meaningfully. Without user intervention or additional data, automatic detection capabilities may not trigger, leading to the conclusion that anomalies won't be detected in this low-traffic scenario. This operational characteristic underscores the relationship between data volume and the effectiveness of monitoring tools in dynamic environments.