In this paper, we propose a novel root cause analysis approach named AAMR. AAMR firstly constructs a service dependency graph based on real-time metrics. Next, ...
With the support of cloud computing platforms, cloud-native applications will be easier to manage and maintain, together with higher scalability. However, it is ...
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AAMR: Automated Anomalous Microservice Ranking in Cloud-Native Environment. SEKE 2021: 86-91; 2020. [c16]. view. electronic edition @ thecvf.com (open access) ...
AAMR: Automated Anomalous Microservice Ranking in Cloud-. Native Environment. For. The 33rd International Conference on. Software Engineering and. Knowledge ...
This paper detects anomalies of microservices by comparing execution traces. We use dynamic instrumentations to monitor execution traces across components.
A collection of papers about Root Cause Analysis/Diagnosis/Localization in MicroService Systems, including invocation chain, multi-dimensional metrics and ...
Jan 7, 2025 · In large-scale cloud environments, microservices generate vast amounts of observability data, including metrics such as CPU usage, memory ...
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Jun 19, 2024 · AAMR: Automated Anomalous Microservice Ranking in Cloud-Native Environment. In The 33rd International Conference on Software Engineering and ...
Sep 7, 2021 · 论文中提出一种新的微服务根因定位方法AAMR（Automated Anomalous Microservice Ranking）。主要思想：首先根据实时指标构建服务依赖图，然后自动更新每个服务 ...
Oct 22, 2024 · AAMR: Automated Anomalous Microservice Ranking in Cloud-Native Environment. Conference Paper. Jul 2021. Zekun Zhang · View · MicroRank: End-to- ...