Logging
AssessTechniques
Recording events and state changes for debugging, audit, and control.
Why it's here
Placed in Assess: 3 article(s) of evidence from 2 source(s), led by research-stage coverage, with 1 in the last 30 days. Confidence 47%.
Evidence (3)
- 6InfoQ·9/15/2026researchAtlassian Automates Root Cause Analysis with Observability Correlation
Atlassian described an approach for automating root cause analysis in large-scale cloud incidents by correlating metrics, logs, distributed traces, and service topology. The system generates ranked hypotheses about where failures start and how they spread across services.
- 5InfoQ·8/26/2026researchUsing LLMs in Incident Response
Anthropic reliability engineer Alex Palcuie describes practical ways large language models can assist during incident response, especially by quickly scanning logs and traces. He also notes their limits in root-cause analysis, where they often struggle to distinguish causation from correlation, and outlines how teams can adopt them without weakening human operational expertise.
- 6Hacker News·7/5/2026researchThe Log as an Agent Framework
This arXiv paper argues that the log can be treated as the core agent abstraction for building reliable AI systems. It frames logging not just as observability, but as the mechanism that drives control, memory, and execution in agentic workflows.