Enjoy your observability: an industrial survey of microservice tracing and analysis

Li, Bowen; Peng, Xin; Xiang, Qilin; Wang, Hanzhang; Xie, Tao; Sun, Jun; Liu, Xuanzhe

doi:10.1007/s10664-021-10063-9

Cited by 58 publications

(15 citation statements)

References 21 publications

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“…This section presents the findings of the study by answering the research questions in separate subsections. [11] 2022 Microservices-based systems visualization: student research abstract [4] 2021 A method for monitoring the coupling evolution of microservice-based architectures [12] 2021 Automated Analysis of Distributed Tracing: Challenges and Research Directions [13] 2020 Graph-based root cause analysis for service-oriented and microservice architectures [14] 2021 Offline Trace Generation for Microservice Observability [15] 2017 MicroART: A Software Architecture Recovery Tool for Maintaining Microservice-Based Systems [16] 2017 Towards Recovering the Software Architecture of Microservice-Based Systems [17] 2020 Graph-based trace analysis for microservice architecture understanding and problem diagnosis [18] 2020 Architectural runtime models for integrating runtime observations and component-based models [19] 2016 Architectural Run-time Models for Performance and Privacy Analysis in Dynamic Cloud Applications [20] 2022 Code Smell Prioritization with Business Process Mining and Static Code Analysis: A Case Study [21] 2021 Enjoy your observability: an industrial survey of microservice tracing and analysis [22] 2021 Characterizing Microservice Dependency and Performance: Alibaba Trace Analysis [23] 2019 Graph-based and scenario-driven microservice analysis, retrieval, and testing [24] 2018 Using Service Dependency Graph to Analyze and Test Microservices [25] 2018 Execution-Based Model Profiling [26] 2017 Supporting Microservice Evolution [27] 2010 Dapper, a large-scale distributed systems tracing infrastructure [28] 2021 µViz: Visualization of Microservices [29] 2021 Temporal Relations Extraction and Analysis of Log Events for Micro-service Framework…”

Section: Resultsmentioning

confidence: 99%

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Visualizing Microservice Architecture in the Dynamic Perspective: A Systematic Mapping Study

et al. 2022

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As microservices become more popular, more drawbacks become apparent to developers. One issue that many teams face today is the failure to visualize the entire system architecture holistically. Without a full view of the system, the architecture can become convoluted as teams add and subtract from their system without reconciling their changes. One established practice to determine a view on the entire system involves dynamic analysis of microservice interaction and dependencies. In this mapping study, we investigate dynamic analysis as a way to visualize system architecture. Capturing the architectural view with dynamic analysis has the ability to build the system and then show its behavior at run-time. We identify dynamic analysis techniques, the corresponding tools, and the models that these practices can generate. The findings of this study are relevant to developers of decentralized systems looking for a way to visualize their system architecture in a dynamic perspective.

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Section: Resultsmentioning

confidence: 99%

“…The messages involving the trace or correlation ID are recorded and collected. They are preprocessed and then sent to storage where they are analyzed [21]. These traces can be used to visualize architecture dynamically as they capture system workflow and record services and dependencies while the system is running [12].…”

Section: ) Distributed Tracingmentioning

confidence: 99%

Visualizing Microservice Architecture in the Dynamic Perspective: A Systematic Mapping Study

et al. 2022

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“…Various research studies and surveys are emerging in the area of observability mechanisms that include distributed tracing techniques, focusing mainly on the exploitation of the collected information for analysis purposes. Based on an industrial survey on microservice tracing and analysis [16], distributed tracing and analysis is considered an important part of the infrastructure for industrial microservice systems, while the development of efficient data fusion mechanisms for trace analysis and production of business intelligence reports is considered challenging. In a similar qualitative study on identifying the challenges and good practices in the field of observability and monitoring of distributed systems [17], the main reported challenge was found to be the need for the management of heterogeneity in the adopted microservices-based development and deployment paradigms, since isolated monitoring and observability solutions are adopted even across teams within the same organization.…”

Section: Related Workmentioning

confidence: 99%

Data Fusion of Observability Signals for Assisting Orchestration of Distributed Applications

Tzanettis

Androna

Zafeiropoulos

et al. 2022

Sensors

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Nowadays, various frameworks are emerging for supporting distributed tracing techniques over microservices-based distributed applications. The objective is to improve observability and management of operational problems of distributed applications, considering bottlenecks in terms of high latencies in the interaction among the deployed microservices. However, such frameworks provide information that is disjoint from the management information that is usually collected by cloud computing orchestration platforms. There is a need to improve observability by combining such information to easily produce insights related to performance issues and to realize root cause analyses to tackle them. In this paper, we provide a modern observability approach and pilot implementation for tackling data fusion aspects in edge and cloud computing orchestration platforms. We consider the integration of signals made available by various open-source monitoring and observability frameworks, including metrics, logs and distributed tracing mechanisms. The approach is validated in an experimental orchestration environment based on the deployment and stress testing of a proof-of-concept microservices-based application. Helpful results are produced regarding the identification of the main causes of latencies in the various application parts and the better understanding of the behavior of the application under different stressing conditions.

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“…In this article, we restrict our analysis of related works (cf. Section V) to those addressing simultaneously patterns and software quality aspects in the scope of microservices design, but such a systematic review could also look in more detail into works as those done by Li et al [36], Reis et al [37], Bogner et al [38], [39], Soldani et al [40] and Waseem et al [41], which study practices and quality aspects in the context of microservices. Even if not necessarily leaning on pattern literature and on how patterns are perceived by professionals, we believe that some of the results of these studies could be used to improve existing pattern knowledge.…”

Section: Future Workmentioning

confidence: 99%

Designing Microservice Systems Using Patterns: An Empirical Study on Quality Trade-Offs

Vale¹,

Correia²,

Guerra³

et al. 2022

Preprint

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The promise of increased agility, autonomy, scalability, and reusability has made the microservices architecture a de facto standard for the development of large-scale and cloud-native commercial applications. Software patterns are an important design tool, and often they are selected and combined with the goal of obtaining a set of desired quality attributes. However, from a research standpoint, many patterns have not been widely validated against industry practice, making them not much more than interesting theories. To address this, we investigated how practitioners perceive the impact of 14 patterns on 7 quality attributes. Hence, we conducted 9 semi-structured interviews to collect industry expertise regarding (1) knowledge and adoption of software patterns, (2) the perceived architectural trade-offs of patterns, and (3) metrics professionals use to measure quality attributes. We found that many of the trade-offs reported in our study matched the documentation of each respective pattern, and identified several gains and pains which have not yet been reported, leading to novel insight about microservice patterns.

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Enjoy your observability: an industrial survey of microservice tracing and analysis

Cited by 58 publications

References 21 publications

Visualizing Microservice Architecture in the Dynamic Perspective: A Systematic Mapping Study

Visualizing Microservice Architecture in the Dynamic Perspective: A Systematic Mapping Study

Data Fusion of Observability Signals for Assisting Orchestration of Distributed Applications

Designing Microservice Systems Using Patterns: An Empirical Study on Quality Trade-Offs

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