Online Diagnosis of Microservices Based Applications Via Partial Digital Twin

The increasing adoption of DevOps and microservices paradigm in enterprise software has not only brought about several benefits but also a host of challenges. In particular, such applications may suffer from frequent misconfigurations and other faults that need to be diagnosed promptly. In this paper, we propose a novel framework centered around the concept of Partial Digital Twin (PDT) to enable isolated testing without disrupting the main infrastructure. Our framework employs a systematic methodology to replicate the chain of dependencies relevant to reported faults, facilitating efficient root cause analysis. Additionally, we introduce a hierarchical categorization of faults leading to the selection of tests tailored to specific fault types. Through empirical evaluation, we demonstrate that the median number of tests required to diagnose a misconfiguration using our approach is only 7% above the ideal scenario.

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Publication Details

Published
2024-10-24
DOI
https://doi.org/10.1109/nca61908.2024.00034
Citations
1
Primary Topic
Software System Performance and Reliability
Type
article
Field-Weighted Citation Impact
0.35
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article

Online Diagnosis of Microservices Based Applications Via Partial Digital Twin

Jit Gupta, Krishna Kant, S. Das
1 citations
Software System Performance and Reliability
0.35
article

Online Diagnosis of Microservices Based Applications Via Partial Digital Twin

Jit Gupta, Krishna Kant, S. Das
article en
1 citations

Abstract

The increasing adoption of DevOps and microservices paradigm in enterprise software has not only brought about several benefits but also a host of challenges. In particular, such applications may suffer from frequent misconfigurations and other faults that need to be diagnosed promptly. In this paper, we propose a novel framework centered around the concept of Partial Digital Twin (PDT) to enable isolated testing without disrupting the main infrastructure. Our framework employs a systematic methodology to replicate the chain of dependencies relevant to reported faults, facilitating efficient root cause analysis. Additionally, we introduce a hierarchical categorization of faults leading to the selection of tests tailored to specific fault types. Through empirical evaluation, we demonstrate that the median number of tests required to diagnose a misconfiguration using our approach is only 7% above the ideal scenario.

Temple University (US)
Openalex Percentile: Top 33%
Software System Performance and Reliability
0.35
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