Data Fusion of Observability Signals to Detect Anomalies and Failures in Microservices

Authors

Fernando Trinta (ORCID: https://orcid.org/0000-0002-0206-1419)
Francisco Gomes (ORCID: https://orcid.org/0000-0003-4853-0361)
José Neuman de Souza (ORCID: https://orcid.org/0000-0002-2980-8877)
Andrey Chaves (ORCID: https://orcid.org/0000-0002-7000-3704)
Paulo A. L. Rêgo (ORCID: https://orcid.org/0000-0002-0936-9301)

Institutions

Universidade Federal do Ceará (BR)

Publication Details

Journal: SPIRE - Sciences Po Institutional REpository
Published: 2025-10-12
DOI: https://doi.org/10.48545/advance2025-fullpapers-3_2
Primary Topic: Software System Performance and Reliability
Type: article
Field-Weighted Citation Impact: 0.00

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article

Data Fusion of Observability Signals to Detect Anomalies and Failures in Microservices

Fernando Trinta, Francisco Gomes, José Neuman de Souza, Andrey Chaves et al.

Oct 12, 2025

SPIRE - Sciences Po Institutional REpository

Software System Performance and Reliability

article

Data Fusion of Observability Signals to Detect Anomalies and Failures in Microservices

Fernando Trinta, Francisco Gomes, José Neuman de Souza, Andrey Chaves, Paulo A. L. Rêgo

October 12, 2025article en

Abstract

No abstract available for this paper.

SPIRE - Sciences Po Institutional REpository

Universidade Federal do Ceará (BR)

Openalex Percentile: Top 66%

Software System Performance and Reliability

DOI Open Access PDF OpenAlex

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Data Fusion of Observability Signals to Detect Anomalies and Failures in Microservices — Fernando Trinta, Francisco Gomes, et al. · SPIRE - Sciences Po Institutional REpository (2025) | TGRS Research Map | TGRS