Related papers: A Comprehensive Survey on Root Cause Analysis in (…
As the issue of robustness in AI systems becomes vital, statistical learning techniques that are reliable even in presence of partly contaminated data have to be developed. Preference data, in the form of (complete) rankings in the simplest…
Traditional banks face significant challenges in digital transformation, primarily due to legacy system constraints and fragmented ownership. Recent incidents show that such fragmentation often results in superficial incident resolutions,…
Root cause analysis (RCA) for time-series anomaly detection is critical for the reliable operation of complex real-world systems. Existing explanation methods often rely on unrealistic feature perturbations and ignore temporal and…
Despite the numerous benefits of microservices systems, security has been a critical issue in such systems. Several factors explain this difficulty, including a knowledge gap among microservices practitioners on properly securing a…
Root Cause Analysis (RCA) plays an indispensable role in distributed data system maintenance and operations, as it bridges the gap between fault detection and system recovery. Existing works mainly study multidimensional localization or…
Root cause analysis of anomalies aims to identify how and why a sample deviates from the normal process. Existing methods primarily focus on telling which features are responsible, ignoring that anomalies can arise through two fundamentally…
Microservice system solutions are driving digital transformation; however, fundamental tools and system perspectives are missing to better observe, understand, and manage these systems, their properties, and their dependencies.…
Researchers and practitioners have recently proposed many Microservices Architecture (MSA) patterns and strategies covering various aspects of microservices system life cycle, such as service design and security. However, selecting and…
The advent of Industrial Internet of Things (IIoT) has imposed more stringent requirements on industrial software in terms of communication delay, scalability, and maintainability. Microservice architecture (MSA), a novel software…
Modern distributed applications are moving toward a microservice architecture, in which each service is developed and managed independently, and new features and updates are delivered continuously. A guiding principle of microservice…
Context: Several companies are migrating their information systems into the Cloud. Microservices and DevOps are two of the most common adopted technologies. However, there is still a lack of understanding how to adopt a microservice-based…
Microservice architectures are a popular choice for deploying large-scale data-intensive applications. This architectural style allows microservice practitioners to achieve requirements related to loose coupling, fault contention, workload…
It is well recognized that design patterns improve system development and maintenance in many aspects. While we commonly recognize these patterns in monolithic systems, many patterns emerged for cloud computing, specifically microservices.…
Root cause analysis (RCA) in complex systems is challenging due to error propagation across multiple variables, the need for structural causal knowledge, and the computational cost of inference at test time. We introduce PRIM (Prior-fitted…
Microservices have become popular in the past few years, attracting the interest of both academia and industry. Despite of its benefits, this new architectural style still poses important challenges, such as resilience, performance and…
Architecture recovery tools help software engineers obtain an overview of their software systems during all phases of the software development lifecycle. This is especially important for microservice applications because their distributed…
Context: Microservices running and being powered by Edge Computing have been gaining much attention in the industry and academia. Since 2014, when Martin Fowler popularized the Microservice term, many studies have been published relating…
Microservices is an architectural style inspired by service-oriented computing that has recently started gaining popularity. Before presenting the current state-of-the-art in the field, this chapter reviews the history of software…
This paper describes the development of a counterfactual Root Cause Analysis diagnosis approach for an industrial multivariate time series environment. It drives the attention toward the Point of Incipient Failure, which is the moment in…
Machine learning tasks entail the use of complex computational pipelines to reach quantitative and qualitative conclusions. If some of the activities in a pipeline produce erroneous or uninformative outputs, the pipeline may fail or produce…