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Root Cause Analysis (RCA) is essential for pinpointing the root causes of failures in microservice systems. Traditional data-driven RCA methods are typically limited to offline applications due to high computational demands, and existing…

Machine Learning · Computer Science 2025-12-17 Lecheng Zheng , Zhengzhang Chen , Haifeng Chen

As Large-Scale Cloud Systems (LCS) become increasingly complex, effective anomaly detection is critical for ensuring system reliability and performance. However, there is a shortage of large-scale, real-world datasets available for…

Cloud-native systems are the mainstream for enterprise solutions, given their scalability, resilience, and other benefits. While the benefits of cloud-native systems fueled by microservices are known, less guidance exists on their…

Software Engineering · Computer Science 2025-01-22 Tomas Cerny , Gabriel Goulis , Amr S. Abdelfattah

Many social and economic systems can be represented as attributed networks encoding the relations between entities who are themselves described by different node attributes. Finding anomalies in these systems is crucial for detecting abuses…

Social and Information Networks · Computer Science 2020-10-27 Leonardo Gutiérrez-Gómez , Alexandre Bovet , Jean-Charles Delvenne

In response to the demand for higher computational power, the number of computing nodes in high performance computers (HPC) increases rapidly. Exascale HPC systems are expected to arrive by 2020. With drastic increase in the number of HPC…

Distributed, Parallel, and Cluster Computing · Computer Science 2019-10-21 Siavash Ghiasvand , Florina M. Ciorba

Software bugs in cloud management systems often cause erratic behavior, hindering detection, and recovery of failures. As a consequence, the failures are not timely detected and notified, and can silently propagate through the system. To…

Software Engineering · Computer Science 2022-03-09 Domenico Cotroneo , Luigi De Simone , Pietro Liguori , Roberto Natella , Angela Scibelli

In large-scale online services, crucial metrics, a.k.a., key performance indicators (KPIs), are monitored periodically to check their running statuses. Generally, KPIs are aggregated along multiple dimensions and derived by complex…

Artificial Intelligence · Computer Science 2022-09-02 Shifu Yan , Caihua Shan , Wenyi Yang , Bixiong Xu , Dongsheng Li , Lili Qiu , Jie Tong , Qi Zhang

Microservices become a fast growing and popular architectural style based on service-oriented development. One of the major advantages using component-based approaches is to support reuse. In this paper, we present a study of microservices…

Software Engineering · Computer Science 2018-05-31 Reza M. Parizi

The microservice software architecture leverages the idea of splitting large monolithic applications into multiple smaller services that interact using lightweight communication schemes. While the microservice architecture has proven its…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-03-06 Dāvis Kažemaks , Jérémie Decouchant

With the spread of services related to cloud environment, it is tiresome and time consuming for users to look for the appropriate service that meet with their needs. Therefore, finding a valid and reliable service is essential. However, in…

Software Engineering · Computer Science 2015-01-08 Nouha Khédiri , Montaceur Zaghdoud

Google uses continuous streams of data from industry partners in order to deliver accurate results to users. Unexpected drops in traffic can be an indication of an underlying issue and may be an early warning that remedial action may be…

Machine Learning · Statistics 2017-08-15 Dominique T. Shipmon , Jason M. Gurevitch , Paolo M. Piselli , Stephen T. Edwards

As modern software systems continue to grow in terms of complexity and volume, anomaly detection on multivariate monitoring metrics, which profile systems' health status, becomes more and more critical and challenging. In particular, the…

Software Engineering · Computer Science 2023-08-22 Jinyang Liu , Tianyi Yang , Zhuangbin Chen , Yuxin Su , Cong Feng , Zengyin Yang , Michael R. Lyu

Real-world graphs are complex to process for performing effective analysis, such as anomaly detection. However, recently, there have been several research efforts addressing the issues surrounding graph-based anomaly detection. In this…

Machine Learning · Computer Science 2024-05-13 Prabin B Lamichhane , William Eberle

The increasing complexity and usage of cloud systems have made it challenging for service providers to ensure reliability. This paper highlights two main challenges, namely internal and external factors, that affect the reliability of cloud…

Software Engineering · Computer Science 2023-10-03 Yintong Huo , Cheryl Lee , Jinyang Liu , Tianyi Yang , Michael R. Lyu

Cloud-native Applications are 'distributed, elastic and horizontal-scalable systems composed of (micro)services which isolate states in a minimum of stateful components'. Hence, an important property is to ensure a low coupling and a high…

Software Engineering · Computer Science 2024-11-19 Sebastiano Panichella , Mohammad Imranur Rahman , Davide Taibi

Anomaly and failure detection methods are crucial in identifying deviations from normal system operational conditions, which allows for actions to be taken in advance, usually preventing more serious damages. Long-lasting deviations…

Machine Learning · Computer Science 2026-03-20 Natalia Wojak-Strzelecka , Szymon Bobek , Grzegorz J. Nalepa , Jerzy Stefanowski

As the Industrial Internet of Things (IIoT) grows, systems are increasingly being monitored by arrays of sensors returning time-series data at ever-increasing 'volume, velocity and variety' (i.e. Industrial Big Data). An obvious use for…

Machine Learning · Computer Science 2019-10-29 Neil Caithness , David Wallom

The widespread use of information and communication technology (ICT) over the course of the last decades has been a primary catalyst behind the digitalization of power systems. Meanwhile, as the utilization rate of the Internet of Things…

Machine Learning · Computer Science 2022-12-06 Ugur Halden , Umit Cali , Ferhat Ozgur Catak , Salvatore D'Arco , Francisco Bilendo

Detecting anomalies is important for identifying inefficiencies, errors, or fraud in business processes. Traditional process mining approaches focus on analyzing 'flattened', sequential, event logs based on a single case notion. However,…

Statistical Finance · Quantitative Finance 2024-03-05 Alessandro Niro , Michael Werner

Cloud applications today deliver an increasingly larger portion of the Information and Communication Technology (ICT) services. To address the scale, growth, and reliability of cloud applications, self-aware management and scheduling are…

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