A study on application container resource efficiency

A study on application container resource efficiency

Nowadays, the IT service environment develops in a dynamic, rapid, and unpredictable way. Microservices andapplication containers in this process have a significant impact on new generation IT service models. The fact that theyhave important capabilities such as modelability, presentability as service, and restructurability, are reasons for preferringthem in many areas. Moreover, microservices can meet various needs of IT personnel. As it is known, all server systemcomponents, such as CPU, network, hard-drive I/O, affect energy consumption. At this point, microservices also play animportant mediator role in resource management. Energy consumption of microservice-based applications is lower thanthat of the traditional approaches. However, there are still cases of recoverable and unnecessary consumption at somepoints. Microservices can be monitored and controlled using many methods. Thus, this provides us with opportunities torecover the wasted energy resources considerably. In this article, the effects of container-based microservice architectureson the energy consumption of the system and how to reduce these effects are presented. For this purpose, a methodology,which has 3 approaches (disconnect, pause, stop), and a tracing mechanism are proposed. The results show that thismethodology has a considerable effect on energy efficiency.

___

  • [1] Le VD, Neff MM, Stewart RV, Kelley R, Fritzinger E, Dascalu SM, Harris FC. Microservice-based architecture for the NRDC. IEEE 13th International Conference on Industrial Informatics, Cambridge, UK, 2015; 1659-1664.
  • [2] Engler DR, Kaashoek MF, O’Toole J. Exokernel: an operating system architecture for application-level resource management. ACM symposium on Operating systems principles, New York, USA 1995; 251-266.
  • [3] Esposito C, Castiglione A, Choo KR. Challenges in delivering software in the cloud as microservices. IEEE Cloud Computing, New York, USA, 2016; 3: 10-14.
  • [4] Bratterud A, Walla A, Haugerud H, Engelstad PE, Begnum K. IncludeOS: A minimal, resource efficient unikernel for cloud services. IEEE 7th International Conference on Cloud Computing Technology and Science, Vancouver, Canada, 2015; 250-257.
  • [5] Xavier B, Ferreto T, Jersak L. Time provisioning evaluation of KVM, Docker and Unikernels in a Cloud Platform. 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, Cartagena, Colombia, 2016; 277-280.
  • [6] Rahman M, Gao J. A reusable automated acceptance testing architecture for microservices in behavior-driven development. IEEE Symposium on Service-Oriented System Engineering, San Francisco Bay, CA, USA, 2015; 277- 280.
  • [7] Kang H, Le M, Tao S. Container and microservice driven design for cloud infrastructure DevOps. IEEE International Conference on Cloud Engineering, Berlin, Germany, 2016; 202-211.
  • [8] Villamizar M, Garces O, Castro H, Verano M, Salamanca L, Casallas R,Gil S. Evaluating the monolithic and the microservice architecture pattern to deploy web applications in the cloud. 10th IEEE International Conference on Computing Colombian Conference, Cartagena, Colombia, 2015; 583-590.
  • [9] Butzin B, Golatowski F, Timmermann D. Microservices approach for the internet of things. IEEE 21st International Conference on Emerging Technologies and Factory Automation, Berlin, Germany, 2016.
  • [10] Barais O, Bourcier J, Bromberg Y, Dion C. Towards microservices architecture to transcode videos in the large at low costs. International Conference on Telecommunications and Multimedia, Heraklion, Crete, Greece, 2016.
  • [11] Inagaki T, Ueda Y, Ohara M. Container management as emerging workload for operating systems. IEEE International Symposium on Workload Characterization, Providence, RI, USA, 2016; 65-74.
  • [12] Villamizar M, Garcés O, Ochoa L, Castro H, Salamanca L, Verano M, Casallas R, Gil S, Valencia C, Zambrano A, Lang M. Infrastructure cost comparison of running web applications in the cloud using AWS lambda and monolithic and microservice architectures. 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, Cartagena, Colombia, 2016; 179-182.
  • [13] Malavalli D, Sathappan S. Scalable microservice based architecture for enabling DMTF profiles. 11th International Conference on Network and Service Management, Washington, DC, USA, 2015; 428-432.
  • [14] Ueda T, Nakaike T, Ohara M. Workload characterization for microservices. IEEE International Symposium on Workload Characterization, Providence, RI, USA, 2016; 85-94.
  • [15] Jaramillo D, Nguyen D, Smart R. Leveraging microservices architecture by using Docker technology. SoutheastCon 2016.
  • [16] Hai NH. A dynamic link speed mechanism for energy saving interconnection networks. PhD, The University of Barcelona, Barcelona, Spain, 2014.
  • [17] Beloglazov A. Energy-efficient management of virtual machines in data centers for cloud computing. PhD, The University of Melbourne, Australia, 2013.