PRAXIS: Integrating Program Analysis with Observability for Root-Cause Analysis
Researchers have developed PRAXIS, a new system designed to diagnose and resolve cloud incidents caused by code or configuration errors. PRAXIS utilizes an LLM-driven approach to traverse service dependency graphs and program dependence graphs, enabling more accurate root-cause analysis. In evaluations, PRAXIS demonstrated a significant improvement in accuracy compared to existing methods while also reducing computational resource usage. AI
IMPACT Introduces a novel LLM-driven approach for automated root-cause analysis, potentially reducing cloud incident resolution time and cost.