TL;DR
Krone introduces a hierarchical log analysis framework augmented with LLMs, enabling precise anomaly detection, localization, and explanation in unstructured system logs, demonstrated through an interactive visualization system.
Contribution
This work presents a novel hierarchical log abstraction and modular detection framework combined with LLM reasoning, enhancing interpretability and accuracy in anomaly analysis.
Findings
Effective hierarchical decomposition of logs into semantic units.
Precise anomaly detection and localization with LLM explanations.
Interactive visualization supports human-in-the-loop review and revision.
Abstract
Logs are ubiquitous in modern systems. Unfortunately, their unstructured nature in flat sequences limits understanding of execution behaviors, hindering effective anomaly diagnosis. To address this, Krone introduces a novel hierarchical log abstraction that transforms flat log sequences into semantically coherent units across entity, action, and status levels. Building on this abstraction, Krone introduces a hierarchical orchestration framework that decomposes flat log sequences into hierarchical execution units and performs modular detection over them. It executes and optimizes the modular detection tasks across levels, enabling precise anomaly detection, localization, and explanation with selective invocation of LLM-based reasoning. In this work, we present Krone-viz, an interactive visualization system based on Krone, which makes hierarchical log analysis interpretable and actionable…
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