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Analysis of Devops Tools using the Traditional Data Mining Techniques

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2017
R. Vaasanthi, V. Prasanna Kumari, S. Philip Kingston

R Vaasanthi, Prasanna V Kumari and Philip S Kingston. Analysis of Devops Tools using the Traditional Data Mining Techniques. International Journal of Computer Applications 161(11):47-49, March 2017. BibTeX

	author = {R. Vaasanthi and V. Prasanna Kumari and S. Philip Kingston},
	title = {Analysis of Devops Tools using the Traditional Data Mining Techniques},
	journal = {International Journal of Computer Applications},
	issue_date = {March 2017},
	volume = {161},
	number = {11},
	month = {Mar},
	year = {2017},
	issn = {0975-8887},
	pages = {47-49},
	numpages = {3},
	url = {},
	doi = {10.5120/ijca2017913319},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


DevOps - a portmanteau of Development and Operations is a set of practices focused on using latest generation tools to automate the configuration process for system resources and application components [2]. Process efficiency improves from hours and days to seconds and minutes. IT performance strongly correlates with well-known DevOps practices such as use of Version Control and Continuous Delivery. The longer an organization has implemented — and continues to improve upon — DevOps practices, the better it performs [7]. And better IT performance correlates to higher performance for the entire organization. Today, enormous amount of tools are present in DevOps space.


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Data mining, DevOps and Classification