Mahalanobis Distance
Covariance-Adjusted Distance Metric for Multimodal & Correlated Feature Spaces
#Statistics#Covariance#Anomaly Detection#Multivariate Normal
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STAGE 1 / 7— Anti-Pattern
Section 1: The LLM Anti-Pattern vs Right-Sized Model
The Naive Generative LLM Approach:
Feeding multivariate telemetry data (CPU, memory, IOPS) to an LLM to detect if an incoming server metric is an anomalous outlier.
Why It Fails in Production:
LLMs have no concept of multivariate feature covariance matrices and will flag false positives when correlated features naturally scale together.
Targeted Algorithm (Mahalanobis Distance)
Latency:0.05ms
Cost / 1M Ops:$0.00
Determinism:Statistically Sound p-value
Generative LLM Alternative
Latency:2,200ms
Cost / 1M Ops:$8,000
Determinism:Hallucinated Anomaly Calls