INCREASING THE EFFICIENCY OF THE VIRTUAL DEVELOPMENT ENVIRONMENT FOR DISTRIBUTED SOFTWARE DEVELOPMENT
Abstract
Virtual distributed environments are widely used for distributed development of software systems, which enable the use of virtualization technologies to create a model of project and to automate processes of synchronization and integration of its components. The virtual development environment allows us to avoid the differences between the local environments of developers and between the local environments and the final platform, and greatly simplifies the installation and configuration of environments during the implementation of systems in operation. The article studies the system of organization of virtual development environments in Vagrant. Alternatively, Docker technology was considered. Using the example of a project aimed at developing an open digital platform for mass psychological research, parameter estimates were made and mechanisms and technologies to improve the efficiency of the cloud virtual environment were proposed. A set of basic criteria for evaluating the effectiveness of the configuration of the development environment has been defined to be: rapid deployment; increase in speed and decrease in the volume of resources used; increase in the speed of data exchange between the host machine and the virtual machine. The results of experimental estimates of the parameters that define the formulated efficiency criteria are given as: processor utilization involved (percentage); the amount of RAM involved (GB); virtual machine startup time (seconds); the time to complete the building of the Build component and to reassemble the Watch component (seconds). To improve the efficiency, a file system access driver based on the NFS protocol is considered. According to the results of experimental assessments, a significant increase in productivity and speed of operation was revealed when using a single virtual machine and the driver based on the NFS. Thus, the set of criteria and estimation methods has been defined and the mechanisms have been proposed for increasing the efficiency of the virtual development environment in the distributed development of large software systems.
References
[2] Giannakopoulos I., Konstantinou I., Tsoumakos D., Koziris N. Cloud application deployment with transient failure recovery. Journal of Cloud Computing. 2018; 7(1):11. (In Eng.) DOI: 10.1186/s13677-018-0112-9
[3] Spanaki P., Sklavos N. Cloud Computing: Security Issues and Establishing Virtual Cloud Environment via Vagrant to Secure Cloud Hosts. In: Daimi K. (eds) Computer and Network Security Essentials. Springer, Cham, 2018, pp. 539-553. (In Eng.) DOI: 10.1007/978-3-319-58424-9_31
[4] Hashimoto M. Vagrant: Up and Running: Create and Manage Virtualized Development Environments. O'Reilly Media Inc., 2013. 156 pp. (In Eng.)
[5] Nam Pham Nguyen Xuan, Sungmin Lim, and Souhwan Jung. 2017. Centralized management solution for vagrant in development environment. Proceedings of the 11th International Conference on Ubiquitous Information Management and Communication (IMCOM '17). ACM, New York, NY, USA, 2017. Article 37, 6 pp. (In Eng.) DOI: https://doi.org/10.1145/3022227.3022263
[6] Thompson C. Vagrant Virtual Development Environment Cookbook. Packt Publishing Ltd., 2015. 250 pp. (In Eng.)
[7] Mouat A. Using Docker: Developing and Deploying Software with Containers. O'Reilly Media Inc., 2016. 358 pp. (In Eng.)
[8] Sammons G. Learning Vagrant: Fast Programming Guide. CreateSpace Independent Publishing Platform, 2016. 68 pp. (In Eng.)
[9] Peacock M. Creating Development Environments with Vagrant. Packt Publishing Ltd., 2015. 153 pp. (In Eng.)
[10] Iuhasz G., Pop D., Dragan I. Architecture of a Scalable Platform for Monitoring Multiple Big Data Frameworks. Scalable Computing: Practice and Experience. 2016; 17(4):313-321. (In Eng.) DOI: 10.12694/scpe.v17i4.1203
[11] Nikulchev E., Ilin D., Kolyasnikov P., Belov V., Zakharov I., Malykh S. Programming Technologies for the Development of Web-Based Platform for Digital Psychological Tools. International Journal of Advanced Computer Science and Applications. 2018; 9(8):34-45. (In Eng.) DOI: 10.14569/IJACSA.2018.090806
[12] Kashyap S., Min C., Kim T. Opportunistic spinlocks: Achieving virtual machine scalability in the clouds. ACM SIGOPS Operating Systems Review. 2016; 50(1):9-16. (In Eng.) DOI: 10.1145/2903267.2903271
[13] Saikrishna P.S., Pasumarthy R., Bhatt N.P. Identification and Multivariable Gain-Scheduling Control for Cloud Computing Systems. IEEE Transactions on Control Systems Technology. 2017; 25(3):792-807. (In Eng.) DOI: 10.1109/TCST.2016.2580659
[14] Li J., Xue S., Zhang W., Ma R., Qi Z., Guan H. When I/O Interrupt Becomes System Bottleneck: Efficiency and Scalability Enhancement for SR-IOV Network Virtualization. IEEE Transactions on Cloud Computing. 2017. pp. 1-1. (In Eng.) DOI: 10.1109/TCC.2017.2712686
[15] Zabell S.L. On Student's 1908 Article “The Probable Error of a Mean”. Journal of the American Statistical Association. 2008; 103(481):1-7. (In Eng.) DOI: 10.1198/016214508000000030
[16] Chen M., Bangera G.B., Hildebrand D., Jalia F., Kuenning G., Nelson H., Zadok E. vNFS: Maximizing NFS Performance with Compounds and Vectorized I/O. ACM Transactions on Storage. 2017; 13(3):21. (In Eng.) DOI: 10.1145/3116213
[17] Kane S.P., Matthias K. Docker: Up & Running: Shipping Reliable Containers in Production. O'Reilly Media Inc, 2018. 352 pp. (In Eng.)
[18] Peinl R., Holzschuher F., Pfitzer F. Docker Cluster Management for the Cloud - Survey Results and Own Solution. Journal of Grid Computing. 2016; 14(2):265-282. (In Eng.) DOI: 10.1007/s10723-016-9366-y
[19] Krieger M.T., Torreno O., Trelles O., Kranzlmüller D. Building an open source cloud environment with auto-scaling resources for executing bioinformatics and biomedical workflows. Future Generation Computer Systems. 2017; 67:329-340. (In Eng.) DOI: 10.1016/j.future.2016.02.008
[20] Dani A.S. JavaScript by Example. Packt Publishing, 2017. 334 pp. (In Eng.)
This work is licensed under a Creative Commons Attribution 4.0 International License.
Publication policy of the journal is based on traditional ethical principles of the Russian scientific periodicals and is built in terms of ethical norms of editors and publishers work stated in Code of Conduct and Best Practice Guidelines for Journal Editors and Code of Conduct for Journal Publishers, developed by the Committee on Publication Ethics (COPE). In the course of publishing editorial board of the journal is led by international rules for copyright protection, statutory regulations of the Russian Federation as well as international standards of publishing.
Authors publishing articles in this journal agree to the following: They retain copyright and grant the journal right of first publication of the work, which is automatically licensed under the Creative Commons Attribution License (CC BY license). Users can use, reuse and build upon the material published in this journal provided that such uses are fully attributed.
