This presentation surveys a collection of techniques for detecting anomalies in a DevOps environment. Each of the techniques has strengths and weaknesses that are illustrated via real-world (anonymized) customer data. Techniques discussed include deterministic and statistical models as well as uni-variate and multi-variate analytics. Examples are given that show concrete evidence where each can succeed and each can fail. This presentation is about concepts and how to think about alternative anomaly detection techniques. This presentation is not an academic discourse in math, statistics or probability theory.

Speaker: Speaker 55

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