LogCDM: Interpretable Log Anomaly Detection via Behavioral Graph Drift and Adaptive Signal Fusion

In 30 Sekunden

Was passiert ist

LogCDM detects log anomalies using three signals fused by a learned gate, reaching near-LLM performance with 8.1M parameters and no GPU required.

Warum es zählt

DevOps and SRE engineers deploying anomaly detection on resource-constrained monitoring nodes where logs originate.

Achtung

Performance varies by dataset; structural signals add little value on HDFS logs, suggesting the approach may not generalize equally across all log types.