Log Parsing with AI at Bronto
Bronto is utilizing AI to enhance log parsing by automatically structuring logs, which simplifies the process for users. The company has developed a multi-layered approach that combines curated Java parsers with fallback options and AI-generated parsing for unknown formats. This innovation aims to improve performance and reduce complexity in handling diverse log formats.
- ▪Bronto's new log parsing method uses AI to automatically generate parsers, addressing the complexity of diverse log formats.
- ▪The approach includes a multi-layered system that separates real-time parsing from offline detection to ensure speed and flexibility.
- ▪Bronto maintains a library of high-performance Java parsers optimized for common log formats, while also utilizing fallback options like Dissect and Grok for less common formats.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3933240) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Patrick Londa for Bronto Posted on May 21 • Originally published at bronto.io Log Parsing with AI at Bronto #logging #ai #devops #observability Authored by Gary Nicholls This post follows on from our AWS Nova log benchmarking article, where we explored how smaller LLMs perform on log analysis tasks. That earlier post highlighted that LLMs are surprisingly good at parsing logs.
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