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A Bird’s Eye View of Microservice Architecture from the Lens of Cloud Computing

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Advancements in Smart Computing and Information Security (ASCIS 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 2040))

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Abstract

In past couple of years, cloud computing has emerged as one of the fastest growing technologies across the globe. In order to keep pace with the advancements taking place in the cloud computing paradigm and to cater the needs of current businesses, there is a continuous evolution in the architectural patterns for building the distributed systems as well. Microservices is one of those architectural patterns which has emerged as an advanced variant of Service Oriented architectural style. Microservices architecture is entirely an amalgamation of notions like domain-driven design, continuous integration continuous delivery, DevOps, containerization, highly scalable and agile systems. As a part of the study, an exhaustive survey is carried out around the ecosystem of microservices architecture. This paper aims at exploring the recent development in microservice architectural pattern, emerging trends and the potential research gaps. The paper outlines the survey of the efforts done by various researchers in discrete aspects of microservice like design and implementation of applications in different domains based on microservices, strategies to empower maintainability and scalability of microservices, security aspects of microservices, strategies for data management and fault tolerance in microservices, orchestration of microservice and frameworks to achieve event sourcing in microservice architecture. The findings of this survey will set a path ahead for addressing the current challenges in various aspects of microservices architecture discussed in the study and further innovations to the same.

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References

  1. Wu, C., Peng, Q., Xia, Y., Jin, Y., Zhentao, H.: Towards cost-effective and robust AI microservice deployment in edge computing environments. Futur. Gener. Comput. Syst. 141, 129–142 (2023)

    Article  Google Scholar 

  2. González-Aparicio, M.T., Younas, M., Tuya, J., Casado, R.: A transaction platform for microservices-based big data systems. Simul. Model. Pract. Theory 123, 102709 (2023)

    Article  Google Scholar 

  3. Zhou, X., et al.: Revisiting the practices and pains of microservice architecture in reality: An industrial inquiry. J. Syst. Softw. 195, 111521 (2023)

    Article  Google Scholar 

  4. Zaki, J., Islam, S.M.R., Alghamdi, N.S., Abdullah-Al-Wadud, M., Kwak, K.-S.: Introducing cloud-assisted micro-service-based software development framework for healthcare systems. IEEE Access 10, 33332–33348 (2022). https://doi.org/10.1109/ACCESS.2022.3161455

    Article  Google Scholar 

  5. Debauche, O., Mahmoudi, S., Manneback, P., Lebeau, F.: Cloud and distributed architectures for data management in agriculture 4.0: review and future trends. J. King Saud Univ. – Comput. Inf. Sci. 34(9), 7494–7514 (2022). ISSN 1319–1578. https://doi.org/10.1016/j.jksuci.2021.09.015

  6. Nasab, A.R., Shahin, M., Raviz, S.A.H., Liang, P., Mashmool, A., Lenarduzzi, V.: An empirical study of security practices for microservices systems. J. Syst. Softw. 198, 111563 (2023). ISSN 0164–1212, https://doi.org/10.1016/j.jss.2022.111563

  7. Chen, Y., Xu, D., Chen, N., Wu, X.: FRL-MFPG: propagation-aware fault root cause location for microservice intelligent operation and maintenance. Inf. Softw. Technol. 153, 107083 (2023). ISSN 0950–5849. https://doi.org/10.1016/j.infsof.2022.107083

  8. Cinque, M., Della Corte, R., Pecchia, A.: Micro2vec: anomaly detection in microservices systems by mining numeric representations of computer logs. J. Netw. Comput. Appl. 208, 103515 (2022). ISSN 1084–8045. https://doi.org/10.1016/j.jnca.2022.103515

  9. Jacob, S., Qiao, Y., Ye, Y., Lee, B.: Anomalous distributed traffic: Detecting cyber security attacks amongst microservices using graph convolutional networks. Comput. Secur. 118, 102728 (2022). ISSN 0167–4048. https://doi.org/10.1016/j.cose.2022.102728

  10. Atitallah, S.B., Driss, M., Ghzela, H.B.: Microservices for data analytics in IoT applications: current solutions, open challenges, and future research directions. Procedia Comput. Sci. 207, 3938–3947 (2022). https://doi.org/10.1016/j.procs.2022.09.456

  11. Sadek, J., Craig, D., Trenell, M.: Design and implementation of medical searching system based on microservices and serverless architectures. Procedia Comput. Sci. 196, 615–622 (2022). ISSN 1877–0509. https://doi.org/10.1016/j.procs.2021.12.056

  12. Chen, J., Huang, H., Chen, H.: Informer: irregular traffic detection for containerized microservices RPC in the real world. High-Confidence Comput. 2(2), 100050 (2022). ISSN 2667–2952

    Google Scholar 

  13. Camilli, M., Janes, A., Russo, B.: Automated test-based learning and verification of performance models for microservices systems. J. Syst. Softw. 187, 111225 (2022). ISSN 0164–1212. https://doi.org/10.1016/j.jss.2022.111225

  14. Nguyen, H.X., Zhu, S., Liu, M.: A survey on graph neural networks for microservice-based cloud applications. Sensors 22(23), 9492 (2022)

    Article  Google Scholar 

  15. Söylemez, M., Tekinerdogan, B., Tarhan, A.K.: Challenges and solution directions of microservice architectures: a systematic literature review. Appl. Sci. 12(11), 5507 (2022)

    Article  Google Scholar 

  16. https://www.marketwatch.com/press-release/microservice-architecture-market-research-report-by-type-installation-application-region---global-forecast-to-2028---cumulative-impact-of-covid-19-2022-12-23

  17. Gu, H., Yang, S., Gu, M., Yuan, M.: Research on online teaching platform system based on microservice architecture. In: MATEC Web of Conferences, vol. 355, p. 03058. EDP Sciences (2022)

    Google Scholar 

  18. Hassan, S., Bahsoon, R., Buyya, R.: Systematic scalability analysis for microservices granularity adaptation design decisions. Softw. Pract. Exp. 52(6), 1378–1401 (2022)

    Article  Google Scholar 

  19. Makris, A., Tserpes, K., Varvarigou, T.: Transition from monolithic to microservice-based applications: challenges from the developer perspective. Open Res. Europe 2, 24 (2022)

    Article  Google Scholar 

  20. Sellami, K., Ouni, A., Saied, M.A., Bouktif, S., Mkaouer, M.W.: Improving microservices extraction using evolutionary search. Inf. Softw. Technol. 151, 106996 (2022)

    Article  Google Scholar 

  21. Li, Z., Shang, C., Jianjie, W., Li, Y.: Microservice extraction based on knowledge graph from monolithic applications. Inf. Softw. Technol. 150, 106992 (2022)

    Article  Google Scholar 

  22. Ponce, F., Soldani, J., Astudillo, H., Brogi, A.: Smells and refactorings for microservices security: a multivocal literature review. J. Syst. Softw. 192, 111393 (2022)

    Article  Google Scholar 

  23. Pei, L., Peng, L.: Design and implementation of course selection system based on springcloud micro-service architecture. In: 2021 3rd International Conference on Applied Machine Learning (ICAML), Changsha, China, pp. 132–135 (2021). https://doi.org/10.1109/ICAML54311.2021.00035

  24. Duan, T., et al.: Design and implementation of intelligent automated testing of microservice application. In: 2021 IEEE 5th Information Technology, Networking, Electronic and Automation Control Conference (ITNEC), Xi'an, China, pp. 1306–1309 (2021). https://doi.org/10.1109/ITNEC52019.2021.9587260

  25. Yang, K.-K., Li, Y., Lang, Q.-M., Zhang, Y.-S., Guo, S.-Z.: Design of information sy stem model management system based on micro-service. In: 2021 4th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE), Changsha, China, pp. 632–636 (2021). https://doi.org/10.1109/AEMCSE51986.2021.00131

  26. Vassiliou-Gioles, T.: Quality assurance of micro-services - when to trust your micro-service test results? In: 2021 IEEE 21st International Conference on Software Quality, Reliability and Security Companion (QRS-C), Hainan, China, pp. 01–06 (2021). https://doi.org/10.1109/QRS-C55045.2021.00024

  27. Jin, W., Qian, J., Zhang, Q., Gao, X., Xu, Y.: Research and application of MES technology architecture in tobacco industry based on micro service. In: 2021 IEEE International Conference on Power, Intelligent Computing and Systems (ICPICS), Shenyang, China, pp. 222–225 (2021). https://doi.org/10.1109/ICPICS52425.2021.9524169

  28. Campbell, A., Thorpe, S., Edwards, T., Panther, C., Ramsey, S., White, D.: Towards an integrated micro-services architecture for campus environments. In: 2021 IEEE 7th International Conference on Collaboration and Internet Computing (CIC), Atlanta, GA, USA, pp. 125–128 (2021). https://doi.org/10.1109/CIC52973.2021.00023

  29. Mateus-Coelho, N., Cruz-Cunha, M., Ferreira, L.G.: Security in microservices architectures. Procedia Comput. Sci. 181, 1225–1236 (2021). ISSN 1877–0509. https://doi.org/10.1016/j.procs.2021.01.320

  30. Waseem, M., Liang, P., Shahin, M., Di Salle, A., Márquez, G.: Design, monitoring, and testing of microservices systems: the practitioners’ perspective. J. Syst. Softw. 182, 111061 (2021). ISSN 0164–1212. https://doi.org/10.1016/j.jss.2021.111061

  31. Hannousse, A., Yahiouche, S.: Securing microservices and microservice architectures: a systematic mapping study. Comput. Sci. Rev. 41, 100415 (2021). ISSN 1574–0137. https://doi.org/10.1016/j.cosrev.2021.100415

  32. Aksakalli, I.K., Çelik, T., Can, A.B., Teki̇nerdoğan, B.: Deployment and communication patterns in microservice architectures: a systematic literature review. J. Syst. Softw. 180, 111014 (2021). ISSN 0164–1212. https://doi.org/10.1016/j.jss.2021.111014

  33. Nasab, A.R., et al.: Automated identification of security discussions in microservices systems: industrial surveys and experiments. J. Syst. Softw. 181, 111046 (2021). ISSN 0164–1212. https://doi.org/10.1016/j.jss.2021.111046

  34. Daoud, M., El Mezouari, A., Faci, N., Benslimane, D., Maamar, Z., El Fazziki, A.: A multi-model based microservices identification approach. J. Syst. Arch. 118, 102200 (2021). ISSN 1383–7621. https://doi.org/10.1016/j.sysarc.2021.102200

  35. de Nardin, I.F., et al.: On revisiting energy and performance in microservices applications: a cloud elasticity-driven approach. Parallel Comput. 108, 102858 (2021). ISSN 0167–8191. https://doi.org/10.1016/j.parco.2021.102858

  36. Laigner, R., Zhou, Y., Vaz Salles, M.A., Liu, Y., Kalinowski, M.: Data management in microservices: State of the practice, challenges, and research directions. arXiv preprint arXiv:2103.00170 (2021)

  37. Auer, F., Lenarduzzi, V., Felderer, M., Taibi, D.: From monolithic systems to Microservices: an assessment framework. Inf. Softw. Technol. 137, 106600 (2021). ISSN 0950–5849. https://doi.org/10.1016/j.infsof.2021.106600

  38. Xue, G., Deng, S., Liu, D., Yan, Z.: Reaching consensus in decentralized coordination of distributed microservices. Comput. Netw. 187, 107786 (2021) ISSN 1389–1286. https://doi.org/10.1016/j.comnet.2020.107786

  39. de Toledo, S.S., Martini, A., Sjøberg, D.I.K.: Identifying architectural technical debt, principal, and interest in microservices: a multiple-case study. J. Syst. Softw. 177, 110968 (2021). ISSN 0164–1212. https://doi.org/10.1016/j.jss.2021.110968

  40. Vayghan, L.A., Saied, M.A., Toeroe, M., Khendek, F.: A Kubernetes controller for managing the availability of elastic microservice based stateful applications. J. Syst. Softw. 175, 110924 (2021). ISSN 0164–1212. https://doi.org/10.1016/j.jss.2021.110924

  41. Li, S., et al.: Understanding and addressing quality attributes of microservices architecture: a systematic literature review. Inf. Softw. Technol. 131, 106449 (2021). ISSN 0950–5849. https://doi.org/10.1016/j.infsof.2020.106449

  42. Henning, S., Hasselbring, W.: Theodolite: scalability benchmarking of distributed stream processing engines in microservice architectures. Big Data Res. 25, 100209 (2021). ISSN 2214–5796. https://doi.org/10.1016/j.bdr.2021.100209

  43. Apolinário, D.R., de França, B.B.: A method for monitoring the coupling evolution of microservice-based architectures. J. Brazil. Comput. Soc. 27(1), 17 (2021)

    Article  Google Scholar 

  44. Miller, L., Mérindol, P., Gallais, A., Pelsser, C.: Securing workflows using microservices and metagraphs. Electronics 10(24), 3087 (2021)

    Article  Google Scholar 

  45. Overeem, M., Spoor, M., Jansen, S., Brinkkemper, S.: An empirical characterization of event sourced systems and their schema evolution—Lessons from industry. J. Syst. Softw. 178, 110970 (2021)

    Article  Google Scholar 

  46. Tilak, P.Y., Yadav, V., Dharmendra, S.D., Bolloju, N.: A platform for enhancing application developer productivity using microservices and micro-frontends. In: 2020 IEEE-HYDCON, Hyderabad, India, pp. 1–4 (2020). https://doi.org/10.1109/HYDCON48903.2020.9242913

  47. Avritzer, A.: Challenges and approaches for the assessment of micro-service architecture deployment alternatives in DevOps: a tutorial presented at ICSA 2020. In: 2020 IEEE International Conference on Software Architecture Companion (ICSA-C), Salvador, Brazil, pp. 1–2 (2020). https://doi.org/10.1109/ICSA-C50368.2020.00007

  48. Stutz, A., Fay, A., Barth, M., Maurmaier, M.: Choreographies in microservice-based automation architectures: next level of flexibility for industrial cyber-physical systems. In: 2020 IEEE Conference on Industrial Cyberphysical Systems (ICPS), Tampere, Finland, pp. 411–416 (2020). https://doi.org/10.1109/ICPS48405.2020.9274719

  49. Kuryazov, D., Jabborov, D., Khujamuratov, B.: Towards decomposing monolithic applications into microservices. In: 2020 IEEE 14th International Conference on Application of Information and Communication Technologies (AICT), Tashkent, Uzbekistan, pp. 1–4 (2020). https://doi.org/10.1109/AICT50176.2020.9368571

  50. Chandrasena, S.: Generalized micro-service architecture for web based database management systems. In: 2020 20th International Conference on Advances in ICT for Emerging Regions (ICTer), Colombo, Sri Lanka, pp. 274–275 (2020). https://doi.org/10.1109/ICTer51097.2020.9325482

  51. Luntovskyy, A., Shubyn, B.: Highly-distributed systems based on micro-services and their construction paradigms. In: 2020 IEEE 15th International Conference on Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering (TCSET), Lviv-Slavske, Ukraine, pp. 7–14 (2020). https://doi.org/10.1109/TCSET49122.2020.235378

  52. Haque, A., Rahman, R., Rahman, S.: Microservice-based architecture of a software as a service (SaaS) building energy management platform. In: 2020 6th IEEE International Energy Conference (ENERGYCon), Gammarth, Tunisia, pp. 967–972 (2020). https://doi.org/10.1109/ENERGYCon48941.2020.9236617

  53. Lee, S., Son, S., Han, J., Kim, J.: Refining micro services placement over multiple kubernetes-orchestrated clusters employing resource monitoring. In: 2020 IEEE 40th International Conference on Distributed Computing Systems (ICDCS), Singapore, Singapore, pp. 1328–1332 (2020). https://doi.org/10.1109/ICDCS47774.2020.00173

  54. Rasheedh, J.A., Saradha, S.: Review of micro-services architectures and runtime dynamic binding. In: 2020 Fourth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC), Palladam, India, pp. 1130–1137 (2020). https://doi.org/10.1109/I-SMAC49090.2020.9243335

  55. Raychev, N.: Test automation in microservice architecture. IEEE Spectrum (2020)

    Google Scholar 

  56. Gong, Y., Gu, F., Chen, K., Wang, F.: The architecture of micro-services and the separation of frond-end and back-end applied in a campus information system. In: 2020 IEEE International Conference on Advances in Electrical Engineering and Computer Applications (AEECA), Dalian, China, pp. 321–324 (2020). https://doi.org/10.1109/AEECA49918.2020.9213662

  57. Lv, H., Zhang, T., Zhao, Z., Xu, J., He, T.: The development of real-time large data processing platform based on reactive micro-service architecture. In: 2020 IEEE 4th Information Technology, Networking, Electronic and Automation Control Conference (ITNEC), Chongqing, China, pp. 2003–2006 (2020). https://doi.org/10.1109/ITNEC48623.2020.9084717

  58. Lenarduzzi, V., Lomio, F., Saarimäki, N., Taibi, D.: Does migrating a monolithic system to microservices decrease the technical debt?. J. Syst. Softw. 169, 110710 (2020). ISSN 0164–1212. https://doi.org/10.1016/j.jss.2020.110710

  59. Waseem, M., Liang, P., Shahin, M.: A systematic mapping study on microservices architecture in DevOps. J. Syst. Softw. 170, 110798 (2020). ISSN 0164–1212. https://doi.org/10.1016/j.jss.2020.110798.

  60. Srirama, S.N., Adhikari, M., Paul, S.: Application deployment using containers with auto-scaling for microservices in cloud environment. J. Netw. Comput. Appl. 160, 102629 (2020). ISSN 1084–8045. https://doi.org/10.1016/j.jnca.2020.102629

  61. Sha, P., Chen, S., Zheng, L., Liu, X., Tang, H., Li, Y.: Design and implement of microservice system for edge computing. IFAC-PapersOnLine 53(5), 507–511 (2020). https://doi.org/10.1016/j.ifacol.2021.04.137

  62. Avritzer, A., et al.: Scalability assessment of microservice architecture deployment configurations: a domain-based approach leveraging operational profiles and load tests. J. Syst. Softw. 165, 110564 (2020). ISSN 0164–1212. https://doi.org/10.1016/j.jss.2020.110564

  63. Taherizadeh, S., Grobelnik, M.:Key influencing factors of the Kubernetes auto-scaler for computing-intensive microservice-native cloud-based applications. Adv. Eng. Softw. 140, 102734 (2020). ISSN 0965–9978. https://doi.org/10.1016/j.advengsoft.2019.102734

  64. Tao, L., Fan, Y., Zhang, T., Zhao, C., Yang, T.: Research and application on microservices architecture in civil affairs informatization. In: Journal of Physics: Conference Series, vol. 1575, no. 1, p. 012076. IOP Publishing (2020)

    Google Scholar 

  65. Abhijeet, K., Smitha, G.R.: Building microservices with event sourcing: a comprehensive review (2020)

    Google Scholar 

  66. Dharmaji, N.: A study of containerization as a micro service deployment model. Int. J. Res. Appl. Sci. Eng. Technol. 8, 1365–1367 (2020). https://doi.org/10.22214/ijraset.2020.5216

  67. Kayal, P.: Kubernetes: towards deployment of distributed iot applications in fog computing. In: Companion of the ACM/SPEC International Conference on Performance Engineering, pp. 32–33 2020

    Google Scholar 

  68. Pandey, K.K., Joshi, D.: Challenges in realizing the software applications based on micro services architecture. Int. J. Adv. Sci. Technol. 29(11s), 2301–2313 (2020)

    Google Scholar 

  69. Pandey, K.K.: development of an evaluation model for micro services development platforms. Compliance Eng. J. 11(6), 51–63 (2020). ISSN NO: 0898–3577

    Google Scholar 

  70. Pandey, K.K., Joshi, D.: Solutions to challenges in realizing the software applications based on micro services architecture. Int. J. Adv. Sci. Technol. 29(7), 12687–12698 (2020)

    Google Scholar 

  71. Pandey, K.K.: Empirical and practical evaluation of micro services with containerized deployment. Compl. Eng. J. 11(6), 134–143 (2020). ISSN NO: 0898–3577

    Google Scholar 

  72. Ştefan, L.: Blockchain technologies and microservices for open learning communities. a software architecture perspective. In: Conference proceedings of» eLearning and Software for Education (eLSE), vol. 16, no. 03, pp. 126–133. Carol I National Defence University Publishing House (2020)

    Google Scholar 

  73. Song, M., Liu, Q., Haihong, E.: A mirco-service tracing system based on istio and kubernetes. In: 2019 IEEE 10th International Conference on Software Engineering and Service Science (ICSESS), Beijing, China, pp. 613–616 (2019). https://doi.org/10.1109/ICSESS47205.2019.9040783

  74. Cui, N., Hu, Y., Yu, D., Han, F.: Research and implementation of intelligent workshop IoT cloud platform based on micro-services. In: 2019 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC), Dalian, China, pp. 1–5 (2019). https://doi.org/10.1109/ICSPCC46631.2019.8960804

  75. Eismann, S., Kistowski, J., Grohmann, J., Bauer, A., Schmitt, N., Kounev, S.: TeaStore - a micro-service reference application. In: 2019 IEEE 4th International Workshops on Foundations and Applications of Self* Systems (FAS*W), Umea, Sweden, pp. 263–264 (2019). https://doi.org/10.1109/FAS-W.2019.00073

  76. Abidi, S., Essafi, M., Guegan, C.G., Fakhri, M., Witti, H., Ghezala, H.H.B.: A web service security governance approach based on dedicated micro-services. Procedia Comput. Sci. 159, 372–386 (2019). ISSN 1877–0509. https://doi.org/10.1016/j.procs.2019.09.192

  77. Yi, Z., Wang, M., Chen, R.Y., Wang, Y.S., Wang, J.: Research on application of SME manufacturing cloud platform based on micro service architecture. Procedia CIRP 83, 596–600 (2019). ISSN 2212–8271. https://doi.org/10.1016/j.procir.2019.04.091

  78. Ma, S.P., Fan, C.Y., Chuang, Y., Liu, I.H., Lan, C.W.: Graph-based and scenario-driven microservice analysis, retrieval, and testing. Future Gener. Comput. Syst. 100, 724–735 (2019). ISSN 0167–739X. https://doi.org/10.1016/j.future.2019.05.048

  79. Baboi, M., Iftene, A., Gîfu, D.: Dynamic microservices to create scalable and fault tolerance architecture. Procedia Comput. Sci. 159, 1035–1044. ISSN 1877–0509. https://doi.org/10.1016/j.procs.2019.09.271

  80. Li, S., et al.: A dataflow-driven approach to identifying microservices from monolithic applications. J. Syst. Softw. 157, 110380 (2019). ISSN 0164–1212. https://doi.org/10.1016/j.jss.2019.07.008

  81. Yu, Y., Yang, J., Guo, C., Zheng, H., He, J.: Joint optimization of service request routing and instance placement in the microservice system. J. Netw. Comput. Appl. 147, 102441 (2019). ISSN 1084–8045, https://doi.org/10.1016/j.jnca.2019.102441

  82. Di Francesco, P., Lago, P., Malavolta, I.: Architecting with microservices: a systematic mapping study. J. Syst. Softw. 150, 77–97 (2019). ISSN 0164–1212. https://doi.org/10.1016/j.jss.2019.01.001

  83. Zhelev, S., Rozeva, A.: Using microservices and event driven architecture for big data stream processing. In: AIP Conference Proceedings, vol. 2172, no. 1, p. 090010. AIP Publishing LLC (2019)

    Google Scholar 

  84. De Alwis, A.A.C., Barros, A., Fidge, C., Polyvyanyy, A.: Availability and scalability optimized microservice discovery from enterprise systems. In: Panetto, H., Debruyne, C., Hepp, M., Lewis, D., Ardagna, C.A., Meersman, R. (eds.) OTM 2019. LNCS, vol. 11877, pp. 496–514. Springer, Cham (2019). https://doi.org/10.1007/978-3-030-33246-4_31

    Chapter  Google Scholar 

  85. Song, M., Zhang, C., Haihong, E.: An auto scaling system for API gateway based on kubernetes. In: 2018 IEEE 9th International Conference on Software Engineering and Service Science (ICSESS), Beijing, China, pp. 109–112 (2018). https://doi.org/10.1109/ICSESS.2018.8663784

  86. Fu, G., Sun, J., Zhao, J.: An optimized control access mechanism based on micro-service architecture. In: 2018 2nd IEEE Conference on Energy Internet and Energy System Integration (EI2), Beijing, China, pp. 1–5 (2018). https://doi.org/10.1109/EI2.2018.8582628

  87. Premchand, A., Choudhry, A.: Architecture simplification at large institutions using micro services. In: 2018 International Conference on Communication, Computing and Internet of Things (IC3IoT), Chennai, India, pp. 30–35 (2018). https://doi.org/10.1109/IC3IoT.2018.8668173

  88. Lin, W., Ma, M., Pan, D., Wang, P.: FacGraph: frequent anomaly correlation graph mining for root cause diagnose in micro-service architecture. In: 2018 IEEE 37th International Performance Computing and Communications Conference (IPCCC), Orlando, FL, USA, pp. 1–8 (2018). https://doi.org/10.1109/PCCC.2018.8711092

  89. Hong, X.J., Yang, H.S., Kim, Y.H.: Performance analysis of RESTful API and RabbitMQ for microservice web application. In: 2018 International Conference on Information and Communication Technology Convergence (ICTC), Jeju, Korea (South), pp. 257–259 (2018). https://doi.org/10.1109/ICTC.2018.8539409

  90. Xie, Y., Zhou, X., Xie, H., Li, G., Tao, Y.: Research on the architecture and key technologies of integrated platform based on micro service. In: 2018 IEEE 3rd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC), Chongqing, China, pp. 887–893 (2018). https://doi.org/10.1109/IAEAC.2018.8577921

  91. Alshuqayran, N., Ali, N., Evans, R.: Towards micro service architecture recovery: an empirical study. In: 2018 IEEE International Conference on Software Architecture (ICSA), Seattle, WA, USA, pp. 47–4709 (2018). https://doi.org/10.1109/ICSA.2018.00014

  92. Soldani, J., Tamburri, D.A., Van Den Heuvel, W.J.: The pains and gains of microservices: a systematic grey literature review. J. Syst. Softw. 146, 215–232 (2018). ISSN 0164–1212. https://doi.org/10.1016/j.jss.2018.09.082

  93. Wan, X., Guan, X., Wang, T., Bai, G., Choi, B.Y.: Application deployment using microservice and docker containers: framework and optimization. J. Netw. Comput. Appl. 119, 97–109 (2018). ISSN 1084–8045. https://doi.org/10.1016/j.jnca.2018.07.003

  94. Hiraman, B.R.: A study of apache kafka in big data stream processing. In: 2018 International Conference on Information, Communication, Engineering and Technology (ICICET), pp. 1–3. IEEE (2018)

    Google Scholar 

  95. Wauer, M., Sherif, M.A., Ngomo, A.C.N.: Towards a semantic message-driven microservice platform for geospatial and sensor data. In: GeoLD-QuWeDa@ ESWC, pp. 47–58 (2018)

    Google Scholar 

  96. Djogic, E., Ribic, S., Donko, D.: Monolithic to microservices redesign of event driven integration platform. In: 2018 41st International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), pp. 1411–1414. IEEE (2018)

    Google Scholar 

  97. Containerized Microservices Architecture. https://www.academia.edu/49354877/Containerized_Microservice_architecture

  98. Kumar, S.S., Shastry, P.M.M.: Database-per-service for e-learning system with micro-service architecture. In: 2017 International Conference on Smart Technologies for Smart Nation (SmartTechCon), Bengaluru, India, pp. 705–708 (2017). https://doi.org/10.1109/SmartTechCon.2017.8358462

  99. Nguyen, P., Nahrstedt, K.: MONAD: self-adaptive micro-service infrastructure for heterogeneous scientific workflows. In: 2017 IEEE International Conference on Autonomic Computing (ICAC), Columbus, OH, USA, pp. 187–196 (2017). https://doi.org/10.1109/ICAC.2017.38

  100. Bhamare, D., Samaka, M., Erbad, A., Jain, R., Gupta, L., Chan, H.A.: Multi-objective scheduling of micro-services for optimal service function chains. In: 2017 IEEE International Conference on Communications (ICC), Paris, France, pp. 1–6 (2017). https://doi.org/10.1109/ICC.2017.7996729

  101. Vural, H., Koyuncu, M., Guney, S.: A systematic literature review on microservices. In: Gervasi, O., et al. (eds.) ICCSA 2017. LNCS, vol. 10409, pp. 203–217. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-62407-5_14

    Chapter  Google Scholar 

  102. Di Francesco, P., Malavolta, I., Lago, P.: Research on architecting microservices: trends, focus, and potential for industrial adoption. In: 2017 IEEE International Conference on Software Architecture (ICSA), pp. 21–30. IEEE (2017)

    Google Scholar 

  103. Guo, D., Wang, W., Zeng, G., Wei, Z.: Microservices architecture based cloudware deployment platform for service computing. In: 2016 IEEE Symposium on Service-Oriented System Engineering (SOSE), Oxford, UK, pp. 358–363 (2016). https://doi.org/10.1109/SOSE.2016.22

  104. Chelladhurai, J., Chelliah, P.R., Kumar, S.A.: Securing docker containers from denial of service (DoS) attacks. In: 2016 IEEE International Conference on Services Computing (SCC), San Francisco, CA, USA, pp. 856–859 (2016). https://doi.org/10.1109/SCC.2016.123

  105. Napoleão, B., Felizardo, K.R., de Souza, E.F., Vijaykumar, N.L.: Practical similarities and differences between systematic literature reviews and systematic mappings: a tertiary study. In: SEKE, vol. 2017, pp. 85–90 (2017)

    Google Scholar 

  106. Richardson, C., Smith, F.: Microservices: From Design to development

    Google Scholar 

  107. Newman, S.: Building Micro services. O’Reilly Media, Inc., Boston (2015)

    Google Scholar 

  108. Kitchenham, B., Charters, S.: Guidelines for performing systematic literature reviews in software engineering. Engineering 2, 1051–1052 (2007)

    Google Scholar 

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Authors and Affiliations

  1. Department of Computer Science, Sarvajanik University, Surat, 395001, India

    Nidhi Vaniyawala

  2. Department of Information and Communication Technology, Gujarat University, Veer Narmad South, Surat, 395007, India

    Kamlendu Kumar Pandey

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  1. Nidhi Vaniyawala
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  1. Marwadi University, Rajkot, India

    Sridaran Rajagopal

  2. Marwadi University, Rajkot, Gujarat, India

    Kalpesh Popat

  3. Marwadi University, Rajkot, Gujarat, India

    Divyakant Meva

  4. Marwadi University, Rajkot, Gujarat, India

    Sunil Bajeja

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Vaniyawala, N., Pandey, K.K. (2024). A Bird’s Eye View of Microservice Architecture from the Lens of Cloud Computing. In: Rajagopal, S., Popat, K., Meva, D., Bajeja, S. (eds) Advancements in Smart Computing and Information Security. ASCIS 2023. Communications in Computer and Information Science, vol 2040. Springer, Cham. https://doi.org/10.1007/978-3-031-59107-5_6

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