Jitendra Solanki, Anand Todkar, Ziran Min · 2026 · arXiv
DOI: 10.48550/arXiv.2610.28611 · open-access PDF
Moderne verteilte Mikroserviceleistungen erzeugen massive Mengen heterogener, mehrformatiger Beobachtungsprotokolle über physikalisch und logisch gespaltene Infrastrukturen. Die Isolierung der Ursachen bei Cascading-Fehlern bleibt eine anstrengende Aufgabe für Site Reliability Engineers (SREs), die durch manuelles Keyword-Filtern und getrennte zeitliche Korrelationen über Monitoring-Dashboards abgeschnitten sind.
Machine translation (Meta M2M100); the English original follows.
Modern distributed microservice deployments generate massive volumes of heterogeneous, multi-format observability logs across physically and logically partitioned infrastructure. Isolating root causes during cascading failures remains an arduous task for Site Reliability Engineers (SREs), bottlenecked by manual keyword filtering and disjointed temporal correlation across monitoring dashboards. We introduce Semantic Observability, an autonomous multi-agent framework that unifies disparate log streams into a dynamic, queryable Property Graph Database. By modeling physical infrastructure topologi
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