Real-time Monitoring System for Container Networks in the Era of Microservices

Shiraishi, Takashi; Noro, Masaaki; Kondo, Reiko; Takano, Yosuke; Naoki, Oguchi

doi:10.23919/apnoms50412.2020.9237055

Cited by 10 publications

(2 citation statements)

References 7 publications

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“…Our study result shows that 3.18% of the issues are related to the monitoring of microservices systems, mainly due to LC&D (e.g., COMPATIBILITY ERROR) and GPE (e.g., INCONSISTENT PACKAGE USED), and most of the monitoring issues are addressed by fixing artifacts and upgrading tools and platforms. The monitoring of microservices systems is fascinating to researchers from several perspectives, including tracing, real-time monitoring, and monitoring tools [55], [56], [57]. Future research can design and develop intelligent systems for (i) monitoring hosts, processes, network, and real-time performance of microservices systems, and (ii) identifying the root causes of container issues.…”

Section: Discussionmentioning

confidence: 99%

Understanding the Issues, Their Causes and Solutions in Microservices Systems: An Empirical Study

Waseem¹,

Peng²,

Ahmad³

et al. 2023

Preprint

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Many small to large organizations have adopted the Microservices Architecture (MSA) style to develop and deliver their core businesses. Despite the popularity of MSA in the software industry, there is a limited evidence-based and thorough understanding of the types of issues (e.g., errors, faults, failures, and bugs) that microservices system developers experience, the causes of the issues, and the solutions as potential fixing strategies to address the issues. To ameliorate this gap, we conducted a mixed-methods empirical study that collected data from 2,641 issues from the issue tracking systems of 15 open-source microservices systems on GitHub, 15 interviews, and an online survey completed by 150 practitioners from 42 countries across 6 continents. Our analysis led to comprehensive taxonomies for the issues, causes, and solutions. The findings of this study inform that Technical Debt, Continuous Integration and Delivery, Exception Handling, Service Execution and Communication, and Security are the most dominant issues in microservices systems. Furthermore, General Programming Errors, Missing Features and Artifacts, and Invalid Configuration and Communication are the main causes behind the issues. Finally, we found 177 types of solutions that can be applied to fix the identified issues. Based on our study results, we formulated future research directions that could help researchers and practitioners to engineer emergent and next-generation microservices systems.

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Section: Discussionmentioning

confidence: 99%

Understanding the Issues, Their Causes and Solutions in Microservices Systems: An Empirical Study

Waseem¹,

Peng²,

Ahmad³

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Outros trabalhos propõem sistemas em tempo real usando eBPF. Por exemplo, um sistema baseado em eBPF capaz de monitorar a latência entre contêineres em tempo real é proposto por [Shiraishi et al 2020]. Já [Van Tu et al 2021] apresentam um método para monitorar o tempo de processamento de pacotes Network Function Virtualization (NFV) em tempo real.…”

Section: Detecc ¸ãO De Intrusões Baseadas Em Ebpfunclassified

BG-IDPS: Detecção e Prevenção de Intrusões em Tempo Real em Switches eBPF com o Filtro de Pacotes Berkeley e a Metaheurística GRASP-FS

Carvalho

Quincozes

et al. 2022

Anais Do XXII Simpósio Brasileiro De Segurança Da Informação E De Sistemas Computacionais (SBSeg 2022)

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Sistemas de detecção de intrusões modernos são comumente desenvolvidos com uso de algoritmos de aprendizado de máquina e seleção de atributos. No entanto, o custo computacional desses algoritmos limita a capacidade de resposta imediata às intrusões. Neste trabalho, é proposta uma arquitetura para a detecção e prevenção de intrusões em tempo real em switches eBPF a partir de modelos otimizados assincronamente através da meta-heurística GRASP-FS. Como prova de conceito, um modelo é construído a partir de um computador e atualizado periodicamente em um switch eBPF. Os resultados obtidos revelam que a solução proposta é capaz de detectar e prevenir intrusões em tempo real com baixa sobrecarga para os cenários avaliados.

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Container Network Performance Anomaly Detection Based on Extended Berkeley Packet Filter and Machine Learning

Liang

Chen

et al. 2022

Lecture Notes on Data Engineering and Communications Technologies

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Real-time Monitoring System for Container Networks in the Era of Microservices

Cited by 10 publications

References 7 publications

Understanding the Issues, Their Causes and Solutions in Microservices Systems: An Empirical Study

Understanding the Issues, Their Causes and Solutions in Microservices Systems: An Empirical Study

BG-IDPS: Detecção e Prevenção de Intrusões em Tempo Real em Switches eBPF com o Filtro de Pacotes Berkeley e a Metaheurística GRASP-FS

Container Network Performance Anomaly Detection Based on Extended Berkeley Packet Filter and Machine Learning

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