Anomaly detection is like finding a puppy in a herd of kittens. It's about spotting unusual behavior in your application that could indicate a problem, such as a sudden spike in error rates or a significant increase in response time. For example, in a web application, anomaly detection could help identify a sudden increase in failed login attempts, which might indicate a new bug in the authentication flow.
Anomaly detection relies on statistical methods, machine learning algorithms, or rule-based systems to analyze and identify irregular patterns in the data.
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