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12th International Conference on ICT Convergence (ICTC) - Beyond the Pandemic Era with ICT Convergence Innovation

作者： Cha, Donghun Kim, Younghan Soongsil Univ Sch Elect Engn Seoul South Korea

ISBN: (纸本)9781665423830

With the development of the latest technology, a flexible and efficient container-based cloud-native infrastructure that breaks away from the existing monolithic architecture is in the spotlight. As a result, the role of observability for visualization and fault detection of infrastructure has increased for the reliability of cloud-native infrastructures. distributed tracing, one of observability, is used as data useful for pinpointing request bottlenecks between services in a micro-service infrastructure However, in order to import distributed trace data from existing microservice environments, adding instrumentation libraries to service applications must be preceded Adding additional library makes difficult to expand or manage the service applications. In this paper, we propose a distributed tracing system that can be easily managed from the perspective of managers and developers by providing traces of services regardless of the structure or network interface of the service or infrastructure.

关键词： microservice architecture observability cloud-native distributed tracing container service mesh

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Analyzing and Monitoring Kubernetes Microservices based on distributed tracing and Service Mesh 29

Analyzing and Monitoring Kubernetes Microservices based on D...

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29th Asia-Pacific Software Engineering Conference (APSEC)

作者： Wang, Yu-Te Ma, Shang-Pin Lai, Yue-Jun Liang, Yan-Cih Natl Taiwan Ocean Univ Dept Comp Sci & Engn Keelung Taiwan

ISBN: (纸本)9781665455374

The microservice system architecture (MSA) outperforms the monolithic system architecture in terms of maintainability, extensibility, scalability, and fault tolerance. This is prompting a widescale migration of software systems from existing monolith systems to MSA. Most microservice systems utilize container technology for deployment. The fact that Kubernetes (K8s) provides a fully-fledged toolchain for managing container-based applications is prompting many organizations to adopt the K8s protocol for microservice system deployment and operations. Microservice monitoring is essential to the success of any service operation. The collection of logs and aggregation of metrics by most existing microservice monitoring systems is somewhat intrusive. Furthermore, the heterogeneity of Kubernetes technology means that most monitoring methods are inapplicable in situations where microservices are developed for a system using a variety of underlying languages and platforms. In the current study, we developed a monitoring mechanism that provides various metrics specific to microservice systems in a nonintrusive way. The proposed K8s-based microservice monitoring system, referred to as KMamiz (Kubernetes-based Microservice Analysis and Monitoring using Istio and Zipkin), enables the construction and visualization for service-level/endpoint-level dependency graphs and endpoint request chains, and the service cohesion/coupling analysis to enhance system quality for the development team.

关键词： Microservice Kubernetes Microservice Monitoring distributed tracing Service Mesh

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A data-centric approach to distributed tracing 11

A data-centric approach to distributed tracing

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11th IEEE Int Conf on Cloud Comp Technol and Sci (CloudCom) / 19th IEEE Int Conf Comp and Informat Technol (CIT) / 2019 Int Workshop on Resource Brokering with Blockchain (RBchain) / Asia-Pacific Serv Comp Conf (APSCC)

作者： Popa, Nicolae Marian Oprescu, Ana Media Distillery Amsterdam Netherlands Univ Amsterdam Informat Dept Amsterdam Netherlands

ISBN: (纸本)9781728150116

Modern applications are often implemented as distributed systems consisting of multiple application layers and spread across many machines. Monitoring and diagnosing are fundamental challenges of such systems, and many solutions have been proposed. They all aim to abstract the distributed nature and offer a concise overview of the system. distributed logging, monitoring and tracing solutions help with root cause analysis or assessing the performance of the system. In data processing situations, data is the main driver and it should be treated accordingly. Microservices are often used to implement highly distributed data processing systems, so troubleshooting from a data point of view is also difficult. Data should be monitored and traced across machines and applications in order to get reliable insights into how the data is stored and processed. However, existing approaches to distributed tracing are based on tracing requests that are propagated throughout the system instead on their content. In this work we take a data-centric perspective to tracing and data processing to investigate how content can be traced in a distributed system. We evaluate existing tracing approaches to see if they can be extended to the content itself, then we take into consideration new ones. We implement three different approaches to data-centric distributed tracing in a highly distributed data processing system built using microservices and discuss their advantages and disadvantages.

关键词： microservices distributed tracing observability instrumentation

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Real-Time Anomaly Detection Using distributed tracing in Microservice Cloud Applications 12

Real-Time Anomaly Detection Using Distributed Tracing in Mic...

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12th International Conference on Cloud Networking (CloudNet)

作者： Raeiszadeh, Mahsa Ebrahimzadeh, Amin Saleem, Ahsan Glitho, Roch H. Eker, Johan Mini, Raquel A. F. Concordia Univ CIISE Montreal PQ Canada Ericsson Res Lund Sweden Univ Western Cape Comp Sci Programme Cape Town South Africa

ISBN: (纸本)9798350313062;9798350313079

distributed tracing plays a vital role in microservice infrastructure, and learning-based trace analysis has been utilized to detect anomalies within such systems. However, existing approaches for learning-based trace-based anomaly detection face certain limitations. Some assume that trace patterns can be learned solely from normal executions, while others depend on anomaly injection to generate labeled traces categorized as normal or anomalous. However, in practical scenarios, anomalies may also happen during the normal execution. Moreover, a wide variety of anomalies may occur in practice, which cannot be captured solely through anomaly injection. To address these issues, we propose a Trace-Driven Anomaly Detection (TDAD) approach based on a Span Causal Graph (SCG) representation, which trains a model using a Graph Neural Network (GNN) and Positive and Unlabeled (PU) learning. This technique allows the model parameters to be optimized by estimating the underlying data distribution. As a result, TDAD can be effectively trained using a small number of labeled anomalous traces along with a relatively large number of unlabeled traces. Our evaluation reveals that TDAD outperforms not only the existing unsupervised trace-based anomaly detection methods by 11.9% in terms of F-1-score but also a supervised learning-based benchmark by 12x in terms of detection time.

关键词： Anomaly Detection distributed tracing Microservice Positive and Unlabeled Learning

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Automatic Anti-Pattern Detection in Microservice Architectures based on distributed tracing 44

Automatic Anti-Pattern Detection in Microservice Architectur...

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ACM/IEEE 44th International Conference on Software Engineering - Software Engineering in Practice (ICSE-SEIP)

作者： Hubener, Tim Chaudron, Michel R., V Luo, Yaping Vallen, Pieter van der Kogel, Jonck Liefheid, Tom Eindhoven Univ Technol Eindhoven Netherlands ING Bank Amsterdam Netherlands

ISBN: (纸本)9781665495905

The successful use of microservice-based applications by large companies has popularized this architectural style. One problem with the microservice architecture is that current techniques for visualising- and detecting anti-pattern are inadequate. This study contributes a method and tool for detecting anti-patterns in microservice architecture based on distributed execution traces. We demonstrate this on an industrial case study.

关键词： anti-patterns microservice architecture distributed tracing

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Network-Centric distributed tracing with DeepFlow: Troubleshooting Your Microservices in Zero Code 23

Network-Centric Distributed Tracing with DeepFlow: Troublesh...

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ACM SIGCOMM Conference (SIGCOMM)

作者： Shen, Junxian Zhang, Han Xiang, Yang Shi, Xingang Li, Xinrui Shen, Yunxi Zhang, Zijian Wu, Yongxiang Yin, Xia Wang, Jilong Xu, Mingwei Li, Yahui Yin, Jiping Song, Jianchang Li, Zhuofeng Nie, Runjie Tsinghua Univ Inst Network Sci & Cyberspace Beijing Peoples R China Yunshan Networks Beijing Peoples R China Tsinghua Univ Dept Comp Sci & Technol Beijing Peoples R China Zhongguancun Lab Beijing Peoples R China

ISBN: (纸本)9798400702365

Microservices are becoming more complicated, posing new challenges for traditional performance monitoring solutions. On the one hand, the rapid evolution of microservices places a significant burden on the utilization and maintenance of existing distributed tracing frameworks. On the other hand, complex infrastructure increases the probability of network performance problems and creates more blind spots on the network side. In this paper, we present DeepFlow, a network-centric distributed tracing framework for troubleshooting microservices. DeepFlow provides out-of-the-box tracing via a network-centric tracing plane and implicit context propagation. In addition, it eliminates blind spots in network infrastructure, captures network metrics in a low-cost way, and enhances correlation between different components and layers. We demonstrate analytically and empirically that DeepFlow is capable of locating microservice performance anomalies with negligible overhead. DeepFlow has already identified over 71 critical performance anomalies for more than 26 companies and has been utilized by hundreds of individual developers. Our production evaluations demonstrate that DeepFlow is able to save users hours of instrumentation efforts and reduce troubleshooting time from several hours to just a few minutes.

关键词： distributed tracing Application Performance Monitoring Network Performance Monitoring eBPF

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FaaSter Troubleshooting - Evaluating distributed tracing Approaches for Serverless Applications 9

FaaSter Troubleshooting - Evaluating Distributed Tracing App...

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9th IEEE International Conference on Cloud Engineering (IC2E)

作者： Borges, Maria C. Werner, Sebastian Kilic, Ahmet Tech Univ Berlin Informat Syst Engn Berlin Germany Tech Univ Berlin Berlin Germany

ISBN: (纸本)9781665449700

Serverless applications can be particularly difficult to troubleshoot, as these applications are often composed of various managed and partly managed services. Faults are often unpredictable and can occur at multiple points, even in simple compositions. Each additional function or service in a serverless composition introduces a new possible fault source and a new layer to obfuscate faults. Currently, serverless platforms offer only limited support for identifying runtime faults. Developers looking to observe their serverless compositions often have to rely on scattered logs and ambiguous error messages to pinpoint root causes. In this paper, we investigate the use of distributed tracing for improving the observability of faults in serverless applications. To this end, we first introduce a model for characterizing fault observability, then provide a prototypical tracing implementation-specifically, a developer-driven and a platform-supported tracing approach. We compare both approaches with our model, measure associated trade-offs (execution latency, resource utilization), and contribute new insights for troubleshooting serverless compositions.

关键词： Serverless Computing FaaS Platforms distributed tracing Observability

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Localizing and Explaining Faults in Microservices Using distributed tracing 15

Localizing and Explaining Faults in Microservices Using Dist...

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15th IEEE International Conference on Cloud Computing (IEEE CLOUD) / IEEE World Congress on Services (IEEE SERVICES)

作者： Rios, Jesus Jha, Saurabh Shwartz, Laura IBM Res Yorktown Hts NY 10598 USA

ISBN: (数字)9781665481373

ISBN: (纸本)9781665481373

Finding the exact location of a fault in a large distributed microservices application running in containerized cloud environments can be very difficult and time-consuming. We present a novel approach that uses distributed tracing to automatically detect, localize and aid in explaining application-level faults. We demonstrate the effectiveness of our proposed approach by injecting faults into a well-known microservice-based benchmark application. Our experiments demonstrated that the proposed fault localization algorithm correctly detects and localize the microservice with the injected fault. We also compare our approach with other fault localization methods. In particular, we empirically show that our method outperforms methods in which a graph model of error propagation is used for inferring fault locations using error logs. Our work illustrates the value added by distributed tracing for localizing and explaining faults in microservices.

关键词： microservices distributed tracing fault localization failure diagnosis debugging root cause analysis

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Using distributed tracing to Identify Inefficient Resources Composition in Cloud Applications 10

Using Distributed Tracing to Identify Inefficient Resources ...

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10th IEEE International Conference on Cloud Networking (IEEE CloudNet)

作者： Casse, Clement Berthou, Pascal Owezarski, Philippe Josset, Sebastien Univ Toulouse LAAS CNRS CNRS Toulouse France Orange Toulouse France Univ Toulouse LAAS CNRS UPS Toulouse France

ISBN: (纸本)9781665435383

Cloud-Applications are the new industry standard way of designing Web-Applications. With Cloud Computing, Applications are usually designed as microservices, and developers can take advantage of thousands of such existing microservices, involving several hundred of cross-component communications on different physical resources. Microservices orchestration (as Kubernetes) is an automatic process, which manages each component lifecycle, and notably their allocation on the different resources of the cloud infrastructure. Whereas such automatic cloud technologies ease development and deployment, they nevertheless obscure debugging and performance analysis. In order to gain insight on the composition of services, distributed tracing recently emerged as a way to get the decomposition of the activity of each component within a cloud infrastructure. This paper aims at providing methodologies and tools (leveraging state-of-the-art tracing) for getting a wider view of application behaviours, especially focusing on application performance assessment. In this paper, we focus on using distributed traces and allocation information from microservices to model their dependencies as a hierarchical property graph. By applying graph rewriting operations, we managed to project and filter communications observed between microservices at higher abstraction layers like the machine nodes, the zones or regions. Finally, in this paper we propose an implementation of the model running on a microservices shopping application deployed on a Zonal Kubernetes cluster monitored by Open Telemetry traces. We propose using the flow hierarchy metric on the graph model to pinpoint cycles that reveal inefficient resource composition inducing possible performance issues and economic waste.

关键词： distributed tracing Cloud Computing Property Graph Graph Rewriting Hierarchical Model

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An effective failure detection method for microservice-based systems using distributed tracing data

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ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 2024年 133卷

作者： Mazraemolla, Zahra Purfallah Rasoolzadegan, Abbas Ferdowsi Univ Mashhad Comp Engn Dept Software Qual Lab Mashhad Iran

Microservice architecture is the latest trend in the design and development of software systems based on modularization. In a microservice-based system, each microservice acts as an independent system;whereas, processing a request may require communication between two or more microservices. Therefore, increasing the complexity and size of microservice-based systems and increasing the communication between microservices increase the probability of runtime failures in such systems. On the other hand, failure detection in microservicebased systems faces challenges due to complex communications, frequent updates, dynamicity at runtime, and complex log management. In a microservice-based system, distributed tracing data is used to overcome the challenge of complex communication and dynamicity at runtime. distributed tracing data can be used to obtain call paths between microservices when responding to a request. The purpose of this study is to improve the performance of the process of failure detection in terms of increasing accuracy and reducing the false-positive rate to detect failure in the microservices' call paths using distributed tracing data. For this purpose, we selected a basic method among the existing failure detection methods, and according to the basic method, we designed a process in three phases. The process phases of the proposed method are 1) training and evaluating the failure detection model, 2) online failure detection, and 3) updating the failure detection model. The evaluation results of the proposed method show that with 98% Accuracy and a false-positive rate of 0.02, we achieved a significant improvement over the basic method.

关键词： Microservice architecture Failure detection distributed tracing Sequence -to -sequence multiclass classification

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