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Cloud computing is ubiquitous: more and more companies are moving the workloads into the Cloud. However, this rise in popularity challenges Cloud service providers, as they need to monitor the quality of their ever-growing offerings…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-08-04 Mohammad Saiful Islam , William Pourmajidi , Lei Zhang , John Steinbacher , Tony Erwin , Andriy Miranskyy

Distributed databases are fundamental infrastructures of today's large-scale software systems such as cloud systems. Detecting anomalies in distributed databases is essential for maintaining software availability. Existing approaches,…

Software Engineering · Computer Science 2024-06-13 Lingzhe Zhang , Tong Jia , Mengxi Jia , Ying Li , Yong Yang , Zhonghai Wu

Effective anomaly detection from logs is crucial for enhancing cybersecurity defenses by enabling the early identification of threats. Despite advances in anomaly detection, existing systems often fall short in areas such as post-detection…

Cryptography and Security · Computer Science 2025-04-04 Zhuoran Tan , Qiyuan Wang , Christos Anagnostopoulos , Shameem P. Parambath , Jeremy Singer , Sam Temple

Multivariate anomaly detection can be used to identify outages within large volumes of telemetry data for computing systems. However, developing an efficient anomaly detector that can provide users with relevant information is a challenging…

Machine Learning · Computer Science 2022-02-15 Bruno Wassermann , David Ohana , Ronen Schaffer , Robert Shahla , Elliot K. Kolodner , Eran Raichstein , Michal Malka

With the increasing prevalence of scalable file systems in the context of High Performance Computing (HPC), the importance of accurate anomaly detection on runtime logs is increasing. But as it currently stands, many state-of-the-art…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-01-20 Chris Egersdoerfer , Dong Dai , Di Zhang

Anomaly detection becomes increasingly important for the dependability and serviceability of IT services. As log lines record events during the execution of IT services, they are a primary source for diagnostics. Thereby, unsupervised…

Machine Learning · Computer Science 2021-09-21 Thorsten Wittkopp , Alexander Acker , Sasho Nedelkoski , Jasmin Bogatinovski , Dominik Scheinert , Wu Fan , Odej Kao

This paper introduces a scalable Anomaly Detection Service with a generalizable API tailored for industrial time-series data, designed to assist Site Reliability Engineers (SREs) in managing cloud infrastructure. The service enables…

Machine Learning · Computer Science 2025-01-29 Nimesh Jha , Shuxin Lin , Srideepika Jayaraman , Kyle Frohling , Christodoulos Constantinides , Dhaval Patel

Log analysis is one of the main techniques engineers use to troubleshoot faults of large-scale software systems. During the past decades, many log analysis approaches have been proposed to detect system anomalies reflected by logs. They…

Software Engineering · Computer Science 2022-09-19 Yongzheng Xie , Hongyu Zhang , Muhammad Ali Babar

Continuous Integration/Continuous Deployment (CI/CD) is fundamental for advanced software development, supporting faster and more efficient delivery of code changes into cloud environments. However, security issues in the CI/CD pipeline…

Software Engineering · Computer Science 2025-05-05 Sabbir M. Saleh , Ibrahim Mohammed Sayem , Nazim Madhavji , John Steinbacher

Modern software systems generate extensive heterogeneous log data with dynamic formats, fragmented event sequences, and varying temporal patterns, making anomaly detection both crucial and challenging. To address these complexities, we…

Artificial Intelligence · Computer Science 2025-12-17 Przemek Pospieszny , Wojciech Mormul , Karolina Szyndler , Sanjeev Kumar

Data centers play a key role in today's Internet. Cloud applications are mainly hosted on multi-tenant warehouse-scale data centers. Anomalies pose a serious threat to data centers' operations. If not controlled properly, a simple anomaly…

Networking and Internet Architecture · Computer Science 2019-06-18 Ashkan Aghdai , Kang Xi , H. Jonathan Chao

Anomalies or failures in large computer systems, such as the cloud, have an impact on a large number of users that communicate, compute, and store information. Therefore, timely and accurate anomaly detection is necessary for reliability,…

Artificial Intelligence · Computer Science 2021-02-24 Harold Ott , Jasmin Bogatinovski , Alexander Acker , Sasho Nedelkoski , Odej Kao

As software systems grow increasingly intricate, the precise detection of anomalies have become both essential and challenging. Current log-based anomaly detection methods depend heavily on vast amounts of log data leading to inefficient…

Software Engineering · Computer Science 2024-09-17 Lingzhe Zhang , Tong Jia , Kangjin Wang , Mengxi Jia , Yang Yong , Ying Li

Log anomaly detection is crucial for preserving the security of operating systems. Depending on the source of log data collection, various information is recorded in logs that can be considered log modalities. In light of this intuition,…

Machine Learning · Computer Science 2026-01-01 Mohammad Nasirzadeh , Jafar Tahmoresnezhad , Parviz Rashidi-Khazaee

Detecting and analyzing potential anomalous performances in cloud computing systems is essential for avoiding losses to customers and ensuring the efficient operation of the systems. To this end, a variety of automated techniques have been…

Human-Computer Interaction · Computer Science 2019-08-01 Ke Xu , Yun Wang , Leni Yang , Yifang Wang , Bo Qiao , Si Qin , Yong Xu , Haidong Zhang , Huamin Qu

Artificial Intelligence for IT Operations (AIOps) describes the process of maintaining and operating large IT systems using diverse AI-enabled methods and tools for, e.g., anomaly detection and root cause analysis, to support the…

Artificial Intelligence · Computer Science 2022-07-08 Jasmin Bogatinovski , Gjorgji Madjarov , Sasho Nedelkoski , Jorge Cardoso , Odej Kao

Most enterprise applications use logging as a mechanism to diagnose anomalies, which could help with reducing system downtime. Anomaly detection using software execution logs has been explored in several prior studies, using both classical…

Machine Learning · Computer Science 2023-11-01 Nadun Wijesinghe , Hadi Hemmati

The rapid progress of modern computing systems has led to a growing interest in informative run-time logs. Various log-based anomaly detection techniques have been proposed to ensure software reliability. However, their implementation in…

Software Engineering · Computer Science 2023-08-21 Yintong Huo , Yichen Li , Yuxin Su , Pinjia He , Zifan Xie , Michael R. Lyu

System logs are some of the most important information for the maintenance of software systems, which have become larger and more complex in recent years. The goal of log-based anomaly detection is to automatically detect system anomalies…

Machine Learning · Computer Science 2024-02-19 Yuuki Yamanaka , Tomokatsu Takahashi , Takuya Minami , Yoshiaki Nakajima

Logs have been an imperative resource to ensure the reliability and continuity of many software systems, especially large-scale distributed systems. They faithfully record runtime information to facilitate system troubleshooting and…

Software Engineering · Computer Science 2022-01-12 Zhuangbin Chen , Jinyang Liu , Wenwei Gu , Yuxin Su , Michael R. Lyu
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