Microservices Architecture (MSA) has emerged as a dominant paradigm for building scalable and flexible distributed systems. By decomposing applications into loosely coupled services, MSA improves modularity and deployment agility, but also introduces significant challenges for system monitoring, anomaly detection, and root-cause identification. These challenges stem from the high degree of dynamic behaviour, service heterogeneity, and inter-service dependencies. This survey provides a comprehensive and systematic review of state-of-the-art approaches for anomaly detection and root-cause analysis in microservice-based systems, covering the period from 2012 to 2025. It examines 117 selected studies, categorized according to data collection methods, detection algorithms, diagnostic models, and evaluation metrics. Emphasis is placed on the role of machine learning, statistical inference, and trace-based methods in detecting and localizing faults. Furthermore, the survey highlights the limitations of existing techniques in terms of scalability, explainability, and real-time applicability. By consolidating scattered research into a unified analytical framework, this work contributes a detailed taxonomy of methods and a critical discussion of their effectiveness in container-based virtualized environments. The survey provides a representative and timely overview of the field, helping to map current progress and highlight remaining gaps. Finally, it outlines promising directions such as hybrid detection architectures, automated trace reasoning, and context-aware root-cause localization, offering guidance for researchers and practitioners seeking to enhance reliability, observability, and operational resilience in microservice systems.
This study analyses the relationship between air quality and sentiments expressed on social media, focusing on the Saharan dust episode that affected Lisbon in March 2022. Environmental data were collected alongside geolocated Twitter posts (now rebranded as X) from the Lisbon area. The content of these posts was analysed using the Valence Aware Dictionary and sEntiment Reasoner algorithm to identify emotional patterns and assess correlations with fluctuations in atmospheric pollutants. A predictive analysis was also conducted using Decision Tree and Random Forest machine learning algorithms. The findings suggest that despite high levels of inhalable particulate matter (PM10) during the event, there was no significant change in online sentiments, which remained mostly neutral or slightly positive. This implies that the publics environ-mental perception may not be clearly reflected on social media, possibly due to cultural factors or the limited influence of Twitter in Portugal. The study concludes that integrating environmental and social data is feasible and valuable, but further research is needed to explore longer periods, other cities, and more advanced techniques, thus contributing to the understanding of air pollution and public perception in Portugal.
In this study, we examined various selection methods relevant to resource selection process within Agile and Virtual Enterprises (A/V Es), focusing specifically on the time effort involved in both the pre-selection phase and the final selection of resources. Our review of the existing literature on selection models and algorithms in the context of A/V Es revealed a lack of studies that distinguish between selection methods or assess their impact on selection time effort. In line with the two research questions guiding this work, our findings indicate that: (1) the time effort required for the resource selection process in A/V Es can be quantified based on the chosen selection method; and (2) the time effort varies depending on the selection method used. Overall, the results suggest that the time effort for resources system selection phase with the dependent selection method with pre-selection of transport resources requires the most time effort, whereas the independent selection method demand the least.
This article discusses the historical construction of the identity of the viola and the violist in the context of the evolution of the Western orchestra between the 16th and 20th centuries. Based on a review of the literature in historical musicology, organology, and studies on orchestral practice, the article analyzes how the viola occupied, for centuries, a secondary position in the instrumental hierarchy, often associated with harmonic filling and performed by musicians from the violin section. The text examines transformations in orchestral writing, in the composition of instrumental ensembles, and in the aesthetic function of the viola throughout the Baroque, Classical, and Romantic periods, highlighting technical, social, and symbolic factors that contributed to the consolidation of stigmas associated with the violist. It also discusses how the development of the repertoire, instrumental pedagogy, and the work of specialized performers, especially from the 20th century onward, fostered the strengthening of the viola’s artistic autonomy and the construction of a distinct professional identity for the violist within the Western musical landscape.
Entrepreneurs’ digital entrepreneurial capabilities can enhance the interaction between digital innovation and digital entrepreneurship. This study explores the influence of digital entrepreneurial capabilities (digital entrepreneurial education, alertness, and knowledge) on the digital innovative attitude and entrepreneurial intention of higher education students. A sample of 417 Portuguese higher education students was collected, and the partial least squares method was applied to the research model. The results showed that higher education students’ innovative digital attitudes and digital entrepreneurial intentions are positively influenced by their digital entrepreneurial alertness and knowledge. Digital entrepreneurial education was not significant in affecting innovative digital attitudes. However, when an innovative digital attitude acts as a mediator, the relationship between digital entrepreneurial intentions and digital entrepreneurial capabilities is stronger. Thus, the importance of digital entrepreneurial education, alertness, and knowledge as precursors to the intention of digital entrepreneurship is emphasized, as well as the importance of these capabilities in promoting digital innovation. The main contribution of this study is to demonstrate the mediating role of the digital innovative attitude in the association between digital entrepreneurial capabilities and digital entrepreneurial intention. These effects intensify the associations between digital entrepreneurial alertness and digital entrepreneurial knowledge with digital entrepreneurial intention, shedding light on how digital entrepreneurship capabilities shape students’ innovative digital attitudes and entrepreneurial intentions and enable articulate digital innovation with digital entrepreneurship.
