The Role of DevOps Automation in Improving Enterprise Database Reliability
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Abstract
The paper discusses how DevOps automation can be used to enhance the reliability of enterprise databases. The method of the research was quantitative, and the data were obtained through the use of a structured questionnaire among the IT professionals. The points that are considered during the study are the level of automation, uptime of the system, rate of errors and response time. Correlation and regression were used in the statistical analysis to gain an insight into the association between variables. The findings indicate that an increased degree of DevOps automation results into improved database reliability and database performance. These results point to the fact that automation minimizes errors, enhances systems stability, and facilitates monitoring, thus making it a valuable strategy, as far as contemporary database management of enterprises is concerned.
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References
[1] Jabbari, R., Bin Ali, N., Petersen, K., & Tanveer, B. (2016, May). What is DevOps? A systematic mapping study on definitions and practices. In Proceedings of the scientific workshop proceedings of XP2016 (pp. 1-11). https://doi.org/10.1145/2962695.2962707
[2] Rajkumar, J., & Vivekanandan, D. (2012). Implementing automated End-to-End testing in an agile environment. Rajkumar | Software Engineering and Technology. https://www.ciitresearch.org/dl/index.php/set/article/view/SE062012001
[3] Cecchet, E., Candea, G., & Ailamaki, A. (2007). Middleware-based Database Replication: The Gaps between Theory and Practice. arXiv (Cornell University). https://doi.org/10.48550/arxiv.0712.2773
[4] Mohammed, I. A. & Osmania University. (2011). A comprehensive study of the A Road Map for Improving DEVOPS Operations in software Organizations [Journal-article]. International Journal of Current Science, 1(3), 40–41. https://rjpn.org/ijcspub/papers/IJCSP11C1007.pdf
[5] Brunnert, A., Andre, V. H., Willnecker, F., Danciu, A., Hasselbring, W., Heger, C., Herbst, N., Jamshidi, P., Jung, R., Joakim, V. K., Koziolek, A., Kroß, J., Spinner, S., Vögele, C., Walter, J., & Wert, A. (2015). Performance-oriented DevOps: a research agenda. arXiv (Cornell University). https://doi.org/10.48550/arxiv.1508.04752
[6] Erich, F., Amrit, C., & Daneva, M. (2014). Report: Devops literature review. University of Twente, Tech. Rep. https://www.researchgate.net/profile/Chintan-Amrit/publication/267330992_Report_DevOps_Literature_Review/links/544ba33f0cf2bcc9b1d6bd8a/Report-DevOps-Literature-Review.pdf
[7] Virmani, M. (2015, May). Understanding DevOps & bridging the gap from continuous integration to continuous delivery. In Fifth international conference on the innovative computing technology (intech 2015) (pp. 78-82). IEEE. 10.1109/INTECH.2015.7173368
[8] McCarthy, M. A., Herger, L. M., Khan, S. M., & Belgodere, B. M. (2015, June). Composable DevOps: automated ontology based DevOps maturity analysis. In 2015 IEEE international conference on services computing (pp. 600-607). IEEE. 10.1109/SCC.2015.87
[9] Kodali, S. (2016). Automation of production servers using DevOps (puppet) tools. https://repository.stcloudstate.edu/mme_etds/64
[10] Wettinger, J., Andrikopoulos, V., & Leymann, F. (2015, March). Automated capturing and systematic usage of devops knowledge for cloud applications. In 2015 IEEE International Conference on Cloud Engineering (pp. 60-65). IEEE. 10.1109/IC2E.2015.23