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Companion of the 16th ACM/SPEC International Conference on Performance Engineering

作者： Anders Nõu Sacheendra Talluri Alexandru Iosup Daniele Bonetta Vrije Universiteit Amsterdam Amsterdam Netherlands

ISBN: (纸本)9798400711305

distributed tracing is crucial to achieve observability in modern distributed systems. However, its adoption introduces performance trade-offs, impacting throughput and latency. This paper investigates the overhead of distributed tracing in microservices and serverless applications. We provide an analysis of the popular OpenTelemetry and Elastic APM distributed tracing frameworks, evaluating their performance impact on microservices and serverless workloads. We highlight and categorize the primary sources of overhead and measure their contribution to performance degradation. The results reveal significant throughput reductions (19-80%) and latency increases (up to 175%) depending on application configurations and execution environments. Our findings reveal that serializing trace data for export is the largest cause of overhead.

关键词： distributed tracing

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distributed tracing of OPC UA method calls

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ELEKTROTECHNIK UND INFORMATIONSTECHNIK 2021年第6期138卷 349-354页

作者： Mayr-Dorn, C. Pereszteghy, B. Holzweber, J. Mayrhofer, M. Johannes Kepler Univ Linz Inst Software Syst Engn Altenbergerstr 69 A-4040 Linz Austria Johannes Kepler Univ Linz Linz Austria Pro2Future GmbH Linz Austria

With increasing digitalization, shopfloor architectures transition to service-oriented, distributed layouts in which the complexity of monitoring communication between systems becomes a major challenge. distributed tracing assists in establishing causality and hence supports the analysis of latency aspects, wrongly configured communication endpoints, and bottlenecks. In this paper, we present a first feasibility study, which investigates to what extent it is possible to trace OPC UA method calls in a distributed manner using the Zipkin framework. We show how this standard can be used in conjunction with the Eclipse Milo OPC UA open source stack and how it can be integrated into our industry demonstrator "Factory in a Box".

关键词： distributed production systems distributed tracing OPC UA method invocation correlation propagation

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A Qualitative Interview Study of distributed tracing Visualisation: A Characterisation of Challenges and Opportunities

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IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS 2024年第7期30卷 3828-3840页

作者： Davidson, Thomas Wall, Emily Mace, Jonathan Univ Saarland Max Planck Inst Software Syst D-66123 Saarbrucken Germany Emory Univ Cognit & Visualizat Lab Comp Sci Atlanta GA 30322 USA

distributed tracing tools have emerged in recent years to enable operators of modern internet applications to troubleshoot cross-component problems in deployed applications. Due to the rich, detailed diagnostic data captured by distributed tracing tools, effectively presenting this data is important. However, use of visualisation to enable sensemaking of this complex data in distributed tracing tools has received relatively little attention. Consequently, operators struggle to make effective use of existing tools. In this article we present the first characterisation of distributed tracing visualisation through a qualitative interview study with six practitioners from two large internet companies. Across two rounds of 1-on-1 interviews we use grounded theory coding to establish users, extract concrete use cases and identify shortcomings of existing distributed tracing tools. We derive guidelines for development of future distributed tracing tools and expose several open research problems that have wide reaching implications for visualisation research and other domains.

关键词： Data visualization Interviews distributed databases Task analysis Social networking (online) Microservice architectures Guidelines distributed tracing systems visualisation

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A distributed tracing pipeline for improving locality awareness of microservices applications

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SOFTWARE-PRACTICE & EXPERIENCE 2024年第6期54卷 1118-1140页

作者： Colarusso, Carmine De Caro, Assunta Falco, Ida Goglia, Lorenzo Zimeo, Eugenio Univ Sannio Dept Engn Via Traiano 3 I-82100 Benevento Italy

The microservices architectural style aims at improving software maintenance and scalability by decomposing applications into independently deployable components. A common criticism about this style is the risk of increasing response times due to communication, especially with very granular entities. Locality-aware placement of microservices onto the underlying hardware can contribute to keeping response times low. However, the complex graphs of invocations originating from users' calls largely depend on the specific workload (e.g., the length of an invocation chain could depend on the input parameters). Therefore, many existing approaches are not suitable for modern infrastructures where application components can be dynamically redeployed to take into account user expectations. This paper contributes to overcoming the limitations of static or off-line techniques by presenting a big data pipeline to dynamically collect tracing data from running applications that are used to identify a given number k$$ k $$ of microservices groups whose deployment allows keeping low the response times of the most critical operations under a defined workload. The results, obtained in different working conditions and with different infrastructure configurations, are presented and discussed to draw the main considerations about the general problem of defining boundary, granularity, and optimal placement of microservices on the underlying execution environment. In particular, they show that knowing how a specific workload impacts the constituent microservices of an application, helps achieve better performance, by effectively lowering response time (e.g., up to a 61%$$ 61\% $$ reduction), through the exploitation of locality-driven clustering strategies for deploying groups of services.

关键词： clustering techniques distributed tracing locality microservices performance

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Constructing a service process model based on distributed tracing for conformance checking of microservices

Constructing a service process model based on distributed tr...

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IEEE/IFIP Network Operations and Management Symposium

作者： Sakai, Masaru Takahashi, Kensuke NTT Corp NTT Network Innovat Ctr Tokyo Japan

ISBN: (纸本)9781665406017

In recent years, microservices architectures have become widespread, where services are divided into smaller pieces, communicate with each other, and operate in chains. distributed tracing, which tracks the processing of user requests, is used to analyze and visualize microservices. In this paper, the trace data obtained from the distributed tracing is divided based on the parent-child relationship and converted into an event log. In addition, process discovery is performed on each of the split event logs to estimate the relationships between microservice processes. Then, generate a normal Petri net model that can reproduce each event log. Finally, the test trace data is used to verify the suitability of the Petri net model. We constructed a service model for two sample microservices with different scales and distributed tracing implementations and demonstrated the proposed method's feasibility through conformance checking using test trace data.

关键词： distributed tracing Process Model Process Mining Petri nets Conformance Checking

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Anomaly Detection and Classification using distributed tracing and Deep Learning 19

Anomaly Detection and Classification using Distributed Traci...

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19th Annual IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing (CCGRID)

作者： Nedelkoski, Sasho Cardoso, Jorge Kao, Odej TU Berlin Complex & Distributed IT Syst Grp Berlin Germany Huawei Technol Huawei Munich Res Ctr Munich Germany

ISBN: (纸本)9781728109121

Artificial Intelligence for IT Operations (AIOps) combines big data and machine learning to replace a broad range of IT Operations tasks including availability, performance, and monitoring of services. By exploiting log, tracing, metric, and network data, AIOps enable detection of faults and issues of services. The focus of this work is on detecting anomalies based on distributed tracing records that contain detailed information for the availability and the response time of the services. In large-scale distributed systems, where a service is deployed on heterogeneous hardware and has multiple scenarios of normal operation, it becomes challenging to detect such anomalous cases. We address the problem by proposing unsupervised, response time anomaly detection based on deep learning data modeling techniques;unsupervised dynamic error threshold approach;tolerance module for false positive reduction;and descriptive classification of the anomalies. The evaluation shows that the approach achieves high accuracy and solid performance in both, experimental testbed and large-scale production cloud.

关键词： AIOps anomaly detection service reliability time series distributed tracing autoencoders RNNs GRUs CNNs

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LatenSeer: Causal Modeling of End-to-End Latency Distributions by Harnessing distributed tracing 14

LatenSeer: Causal Modeling of End-to-End Latency Distributio...

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14th Annual ACM Symposium on Cloud Computing (SoCC)

作者： Zhang, Yazhuo Isaacs, Rebecca Yue, Yao Yang, Juncheng Zhang, Lei Vigfusson, Ymir Emory Univ Atlanta GA 30322 USA Amazon Web Serv Seattle WA USA IOP Syst San Francisco CA USA Carnegie Mellon Univ Pittsburgh PA 15213 USA Princeton Univ Princeton NJ 08544 USA Keystrike Atlanta GA USA

ISBN: (纸本)9798400703874

End-to-end latency estimation in web applications is crucial for system operators to foresee the effects of potential changes, helping ensure system stability, optimize cost, and improve user experience. However, estimating latency in microservices-based architectures is challenging due to the complex interactions between hundreds or thousands of loosely coupled microservices. Current approaches either track only latency-critical paths or require laborious bespoke instrumentation, which is unrealistic for end-to-end latency estimation in complex systems. This paper presents LatenSeer, a modeling framework for estimating end-to-end latency distributions in microservicebased web applications. LatenSeer proposes novel data structures to accurately represent causal relationships between services, overcoming the drawbacks of simple dependency representations that fail to capture the complexity of microservices. LatenSeer leverages distributed tracing data to practically and accurately model end-to-end latency at scale. Our evaluation shows that LatenSeer predicts latency within a 5.35% error, outperforming the state-of-the-art that has an error rate of more than 9.5%.

关键词： microservices distributed tracing latency estimation end-to-end latency

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A Comparison of distributed tracing Tools in Serverless Applications 17

A Comparison of Distributed Tracing Tools in Serverless Appl...

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17th IEEE International Congress on Intelligent and Service-Oriented Systems Engineering (CISOSE)

作者： Eder, Christina Winzinger, Stefan Lichtenthaeler, Robin Univ Bamberg Distributed Syst Grp Bamberg Germany

ISBN: (纸本)9798350322392

Serverless computing can favor the emergence of complex and error-prone applications. In order to gain observability in such applications, distributed tracing can be used. However, as serverless computing relies on the pay-per-use billing model, utilizing distributed tracing tools can have a noticeable impact on the resulting costs. Therefore, this paper investigates the impact of distributed tracing in serverless applications by exploring and comparing the efficiency characteristics of three selected distributed tracing tools - Zipkin, OpenTelemetry, and SkyWalking. In particular, the runtime, the memory usage, and the initialization duration were examined by benchmarking AWS Lambda function invocations. In the experiments, Zipkin imposed the lowest runtime overhead with an average of 10.73 %, while SkyWalking introduced the highest overhead with an average runtime overhead of 50.67 %. OpenTelemetry added 24.19% additional runtime. Besides runtime overheads, significantly higher memory usage and initialization durations were detected for all tools. Therefore, the results suggest that distributed tracing can significantly impact the efficiency of serverless applications. Nevertheless, differences could be observed concerning tracing mechanisms and use cases. This helps developers to carefully select the most suitable tracing tool considering factors such as runtime overhead, memory usage, and initialization durations.

关键词： distributed tracing Serverless AWS Lambda Benchmarking

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Accelerating distributed tracing in Serverless Computing Using Differential tracing

Accelerating Distributed Tracing in Serverless Computing Usi...

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Coupling of Sensing & Computing in AIoT Systems (CSCAIoT)

作者： Yang, Yuhan Wei, Xingda Shanghai Jiao Tong Univ Shanghai Peoples R China

ISBN: (纸本)9798350363395;9798350363388

distributed tracing is a fundamental tool for analyzing the execution of applications that involve multiple devices, such as AIoT systems. Meanwhile, serverless computing is a promising edge-cloud cooperation scheme that offers improved resource and cost efficiency. However, the efficiency of distributed tracing in serverless computing is compromised due to the excessive traces generated by various system components. In this paper, we introduce Differential tracing, an efficient and accurate distributed tracing system specifically designed for serverless computing, which minimizes overhead of tracing while maintaining high accuracy.

关键词： distributed tracing Serverless Performance Monitoring

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Detecting Cyber Security Attacks against a Microservices Application using distributed tracing 7th

Detecting Cyber Security Attacks against a Microservices App...

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7th International Conference on Information Systems Security and Privacy (ICISSP)

作者： Jacob, Stephen Qiao, Yuansong Lee, Brian Athlone Inst Technol Dept Comp & Software Engn Dublin Rd Athlone Ireland

ISBN: (纸本)9789897584916

Microservices are emerging as the dominant software design architecture for many different applications, and cyber attacks are targeting more software organisations every day. Newer techniques for detecting cyber intrusions against such applications are in high demand. Application functionality that is executed within a microservices application can be monitored and logged using distributed tracing. distributed tracing is normally used for performance management of microservices applications. In this paper, we used distributed tracing for detecting cyber-security attacks. Each microservice call, or sequence of calls, executed in response to a request by an end user of the application is logged as a trace. Anomaly detection is a means of detecting irregular or unusual events or patterns in a data set that occur to a greater or a lesser degree than the majority of the data. In this paper, we present initial work that identifies anomalous distributions of traces. A frequency distribution of traces is obtained from normal data and traffic is identified as an anomaly candidate if it differs sufficiently from the base distribution. This approach is evaluated using a password guessing attack. In addition, we briefly discuss a NoSQL injection attack which we argue is difficult to detect using trace data.

关键词： Microservices Cyber Security distributed tracing Anomaly Detection

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