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Jindo: Smart Microservice Monitoring and Development Tool

by Mehmet Göktürk, Imran Kazdal, Ahmet Faruk Biskinler
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 183 - Number 17
Year of Publication: 2021
Authors: Mehmet Göktürk, Imran Kazdal, Ahmet Faruk Biskinler
10.5120/ijca2021921512

Mehmet Göktürk, Imran Kazdal, Ahmet Faruk Biskinler . Jindo: Smart Microservice Monitoring and Development Tool. International Journal of Computer Applications. 183, 17 ( Jul 2021), 17-24. DOI=10.5120/ijca2021921512

@article{ 10.5120/ijca2021921512,
author = { Mehmet Göktürk, Imran Kazdal, Ahmet Faruk Biskinler },
title = { Jindo: Smart Microservice Monitoring and Development Tool },
journal = { International Journal of Computer Applications },
issue_date = { Jul 2021 },
volume = { 183 },
number = { 17 },
month = { Jul },
year = { 2021 },
issn = { 0975-8887 },
pages = { 17-24 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume183/number17/32018-2021921512/ },
doi = { 10.5120/ijca2021921512 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:19:56.103745+05:30
%A Mehmet Göktürk
%A Imran Kazdal
%A Ahmet Faruk Biskinler
%T Jindo: Smart Microservice Monitoring and Development Tool
%J International Journal of Computer Applications
%@ 0975-8887
%V 183
%N 17
%P 17-24
%D 2021
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Recent developments and programming trends made microservice architecture quite a popular approach for enterprise information systems. Classical monolithic mega-applications are slowly being replaced with microservice based container clusters. Advantages such as scalability, maintainability an suitability for continuous development and harmony with agile software teams make them a favorable choice. Yet there are some disadvantages regarding their operation, management and development. Especially in large institutions where large number of microservices are developed and put into service, monitoring them in runtime becomes burden as well as keeping them in harmony with each other. Developers may face serious difficulties sometime after an enterprise microservice transformation. Lack of adequate monitoring, difficulties in understanding the underlying program control logic can cause serious problems and disruptions as well as unacceptable performance. Furthermore, microservice development is not enterprise wide controlled process yet. In this work, an integrated enterprise scale microservice monitoring and production system has been introduced. Smart features relying on machine learning techniques are used to monitor performance of microservices predictively on a heterogenous enterprise scale environment. Moreover, through a development control and template code generation feature, microservices that are being developed within the institution are put into tighter control. The system named as Jindo, included additional features related to security and maintenance as well. The results obtained suggest thatsystem managers and developers were affected very positively and enterprise application performance can be enhanced through Jindo system.

References
  1. Dragoni, Nicola, Saverio Giallorenzo, Alberto Lluch Lafuente, Manuel Mazzara, Fabrizio Montesi, Ruslan Mustafin, and Larisa Safina. "Microservices: yesterday, today, and tomorrow." In Present and ulterior software engineering, pp. 195-216. Springer, Cham, 2017.
  2. Hassan, Sara, Nour Ali, and Rami Bahsoon. "Microservice ambients: An architectural meta-modelling approach for microservice granularity." In 2017 IEEE International Conference on Software Architecture (ICSA), pp. 1-10. IEEE, 2017.
  3. Rademacher, Florian, Jonas Sorgalla, and Sabine Sachweh. "Challenges of domain-driven microservice design: a model-driven perspective." IEEE Software 35, no. 3 (2018): 36-43.
  4. Pahl, Claus, and Pooyan Jamshidi. "Microservices: A Systematic Mapping Study." In CLOSER (1), pp. 137-146. 2016.
  5. Asik, Tugrul, and Yunus Emre Selcuk. "Policy enforcement upon software based on microservice architecture." In 2017 IEEE 15th International Conference on Software Engineering Research, Management and Applications (SERA), pp. 283-287. IEEE, 2017.
  6. Haselböck, Stefan, Rainer Weinreich, and Georg Buchgeher. "An Expert Interview Study on Areas of Microservice Design." In 2018 IEEE 11th Conference on Service-Oriented Computing and Applications (SOCA), pp. 137-144. IEEE, 2018.
  7. Naily, Moh Afifun, Maya Retno Ayu Setyautami, Radu Muschevici, and Ade Azurat. "A framework for modelling variable microservices as software product lines." In International Conference on Software Engineering and Formal Methods, pp. 246-261. Springer, Cham, 2017.
  8. Edling, Erik, and Emil Östergren. "An analysis of microservice frameworks." (2017).
  9. Seifermann, Valentin. "Application performance monitoring in microservice-based systems." Bachelor's thesis, 2017.
  10. Esposito, Christian, Aniello Castiglione, and Kim-Kwang Raymond Choo. "Challenges in delivering software in the cloud as microservices." IEEE Cloud Computing 3, no. 5 (2016): 10-14.
  11. Di Francesco, Paolo, Patricia Lago, and Ivano Malavolta. "Migrating towards microservice architectures: an industrial survey." In 2018 IEEE International Conference on Software Architecture (ICSA), pp. 29-2909. IEEE, 2018.
  12. Thönes, Johannes. "Microservices." IEEE software 32, no. 1 (2015): 116-116.
  13. Nikiforov, Roman. "Clustering-based Anomaly Detection for microservices." arXiv preprint arXiv:1810.02762 (2018).
  14. Zasadziński, Michał, Marc Solé, Alvaro Brandon, Victor Muntés-Mulero, and David Carrera. "Next stop" noops": Enabling cross-system diagnostics through graph-based composition of logs and metrics." In 2018 IEEE International Conference on Cluster Computing (CLUSTER), pp. 212-222. IEEE, 2018.
  15. Zwietasch, Tim. "Online failure prediction for microservice architectures." Master's thesis, 2017.
  16. Thalheim, Jörg, Antonio Rodrigues, Istemi Ekin Akkus, Pramod Bhatotia, Ruichuan Chen, Bimal Viswanath, Lei Jiao, and Christof Fetzer. "Sieve: Actionable insights from monitored metrics in microservices." arXiv preprint arXiv:1709.06686 (2017).
  17. Wu, Li, Johan Tordsson, Erik Elmroth, and Odej Kao. "Microrca: Root cause localization of performance issues in microservices." In NOMS 2020-2020 IEEE/IFIP Network Operations and Management Symposium, pp. 1-9. IEEE, 2020.
  18. Eismann, Simon, Cor-Paul Bezemer, Weiyi Shang, Dušan Okanović, and André van Hoorn. "Microservices: A Performance Tester's Dream or Nightmare?." In Proceedings of the ACM/SPEC International Conference on Performance Engineering, pp. 138-149. 2020.
  19. Mateus-Coelho, Nuno, Manuela Cruz-Cunha, and Luis Gonzaga Ferreira. "Security in Microservices Architectures." Procedia Computer Science 181 (2021): 1225-1236.
  20. Gkikopoulos, Panagiotis, Josef Spillner, and Valerio Schiavoni. "Monitoring Data Distribution and Exploitation in a Global-Scale Microservice Artefact Observatory." arXiv preprint arXiv:2006.01514 (2020).
  21. Knoche, Holger. "Sustaining runtime performance while incrementally modernizing transactional monolithic software towards microservices." In Proceedings of the 7th ACM/SPEC on International Conference on Performance Engineering, pp. 121-124. 2016.
  22. Lavin, Alexander, and Subutai Ahmad. "Evaluating Real-Time anomaly detection algorithms--The Numenta anomaly benchmark." In 2015 IEEE 14th International Conference on Machine Learning and Applications (ICMLA), pp. 38-44. IEEE, 2015.
  23. Ueda, Takanori, Takuya Nakaike, and Moriyoshi Ohara. "Workload characterization for microservices." In 2016 IEEE international symposium on workload characterization (IISWC), pp. 1-10. IEEE, 2016.
Index Terms

Computer Science
Information Sciences

Keywords

Microservice service monitoring model driven development ide software development

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