Microservice Performance Degradation Correlation

Samardzic, Marko; Sajina, Romeo; Tanković, Nikola; Grbac, Tihana Galinac

doi:10.23919/mipro48935.2020.9245234

Cited by 3 publications

(7 citation statements)

References 6 publications

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“…Of the two main methods of analysis, dynamic analysis is used more often than static analysis. Using dynamic techniques, several different approaches become feasible that cannot be done via static techniques, for example, performance analysis and optimization techniques as well as other metrics-based analyses [12,32,36,39,40]. A specific subset of dynamic techniques is commonly applied to fault analysis and root cause analysis: log analysis and execution trace analysis are perfect for this task, as they examine traces directly related to program execution [35,40,[42][43][44].…”

Section: Rq1: Methods and Techniques Usedmentioning

confidence: 99%

“…Jiang et al's proposed scheme [35] uses multiple trackers on logs, sensors, and internal metrics to set up an intelligent microservice monitoring scheme, which can help keep track of anomalies in a system and warn clients of these anomalies before they develop into failure cases. An article by Samardzic et al [40] uses log analysis as well, basing its results on runtime logs collected from six real-world microservices commonly used in the retail domain to determine how microservice runtime performance degrades. An algorithm proposed by Jin et al [43] relies on execution traces.…”

Section: Dynamic Analysismentioning

confidence: 99%

“…Bogner et al [39] analyze runtime data of microservices to calculate several maintainability metrics relating to the microservice coupling, cohesion, complexity, and size. Samardzic et al [40] take a different approach; they analyze performance metrics to identify performance degradation in microservices, a key indication that the current design is not sustainable.…”

Section: Microservice Evolutionmentioning

confidence: 99%

“…The authors developed an automated optimization framework that can adopt any optimization algorithm such as genetic algorithms, Bayesian optimization, etc. Samardžić et al [40] analyzed run time logs of six microservices in the retail area to explore performance degradation in microservices. They examined log entries to detect events and dependencies among the time series data.…”

Section: Quality Attribute Analysismentioning

confidence: 99%

“…Antipatterns and code smells that threaten sustainability have also been addressed [27][28][29]31], as has the issue of accumulating technical debt [63,65]. In addition, some works improve the evolutionary outlook of a system by addressing maintainability metrics [39] or performance degradation [40].…”

Section: Rq2: Goals Addressed By the Papersmentioning

confidence: 99%

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On Microservice Analysis and Architecture Evolution: A Systematic Mapping Study

et al. 2021

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Microservice architecture has become the leading design for cloud-native systems. The highly decentralized approach to software development consists of relatively independent services, which provides benefits such as faster deployment cycles, better scalability, and good separation of concerns among services. With this new architecture, one can naturally expect a broad range of advancements and simplifications over legacy systems. However, microservice system design remains challenging, as it is still difficult for engineers to understand the system module boundaries. Thus, understanding and explaining the microservice systems might not be as easy as initially thought. This study aims to classify recently published approaches and techniques to analyze microservice systems. It also looks at the evolutionary perspective of such systems and their analysis. Furthermore, the identified approaches target various challenges and goals, which this study analyzed. Thus, it provides the reader with a roadmap to the discipline, tools, techniques, and open challenges for future work. It provides a guide towards choices when aiming for analyzing cloud-native systems. The results indicate five analytical approaches commonly used in the literature, possibly in combination, towards problems classified into seven categories.

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Section: Rq1: Methods and Techniques Usedmentioning

confidence: 99%

Section: Dynamic Analysismentioning

confidence: 99%

Section: Microservice Evolutionmentioning

confidence: 99%

Section: Quality Attribute Analysismentioning

confidence: 99%

Section: Rq2: Goals Addressed By the Papersmentioning

confidence: 99%

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On Microservice Analysis and Architecture Evolution: A Systematic Mapping Study

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Architecture for IoT applications based on reactive microservices: A performance evaluation

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Comparison of Representative Microservices Technologies in Terms of Performance for Use for Projects Based on Sensor Networks

Plecinski

Bokla

Klymkovych

et al. 2022

Sensors

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Reading and analyzing data from sensors are crucial in many areas of life. IoT concepts and related issues are becoming more and more popular, but before we can process data and draw conclusions, we need to think about how to design an application. The most popular solutions today are microservices and monolithic architecture. In addition to this choice, there is also the question of the technology in which you will work. There are more and more of them on the market and in each of them it is practically possible to achieve similar results, but the difference lies in how quickly it will be possible and whether the approach invented will turn out to be the most optimal. Making the right decisions at the beginning of application development can determine its path to success or failure. The main goal of this article was to compare technologies used in applications based on microservice architecture. The preparation of a book lending system, whose server part was implemented in three different versions, each using a different type of technology, helped to achieve this goal. The compared solutions were: Spring Boot, Micronaut and Quarkus. The reason for this research was to investigate projects using sensor networks, ranging from telemedicine applications to extensive sensor networks collecting scientific data, or working in an environment with limited resources, e.g., with BLE or WIFI transmitters, where it is critical to supply energy to these transmitters. Therefore, the issue of efficiency and hence energy savings may be a key issue depending on the selected programming technology.

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Microservice Performance Degradation Correlation

Cited by 3 publications

References 6 publications

On Microservice Analysis and Architecture Evolution: A Systematic Mapping Study

On Microservice Analysis and Architecture Evolution: A Systematic Mapping Study

Architecture for IoT applications based on reactive microservices: A performance evaluation

Comparison of Representative Microservices Technologies in Terms of Performance for Use for Projects Based on Sensor Networks

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