Static thresholds on metrics have been falling out of fashion for a while, and for good reason. Modern tooling lets you analyze and monitor a lot more data points than you used to be able to, resulting in lots more noise. The hope is that anomaly detection answers some of this, by replacing static thresholds (anomalies) with dynamic ones. But it doesn’t work as well as most people think it will. In this talk I’ll explain how anomaly detection works, so you can understand why it isn’t a good general-purpose solution, and which specific cases it’s good at.